portman hotel london - giievent › irmu333172 › catalog.pdf‘unleash the power of analytics with...

In Association with: Hosted By:

Benefits of Attending:

irmuk.co.uk/edbi2015Strategic IT Training Ltd www.irmuk.co.uk

17th Annual Conference

2-5 November 2015Radisson Blu

Portman HotelLondon

Case Studies and Contributors Include:

• Barclays• Standard Life• Rolls-Royce• Visa Europe• Ford Motor

Company• Intel• United Utilities• PwC• BT• IBM• GE Capital• Premier Farnell• GeoPlace• Microsoft• The Guardian• John Lewis• XL Catlin• BetFair

• Computer Weekly

• GE Oil & Gas• Forrester• ComputerWorld• Cambridge

Assessment• Mater Health

Services• Flynn O’Driscoll

Business Lawyers• FromHereOn• Roche• The Copyright

Licensing Agency• BUPA• Ecolab• Coats UK• Capgemini

Group

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Claudia ImhoffIntelligent Solutions

Peter AikenData Blueprint

& VCU

Rick van der Lans R20/Consultancy

Jan HenderyckxInpuls

Mike FergusonIntelligent Business

Strategies

Louise MillerHead of UK Customer

Data, Standard Life

Eulogio BarraganEnterprise Data

Analytics Strategy GE Oil & Gas

Jason PerkinsDecision Support Chief Architect

BT

Mark WoodwardAnalytics & Insights

Manager Intel

Sanjay JacobGlobal Head, Cloud & Enterprise Businesses

Microsoft

• Claudia Imhoff• Peter Aiken• Rick van der Lans• Mike Ferguson• Jan Henderyckx• Martin Sykes• Barry Devlin• Alec Sharp• John Ladley• Nicola Askham• Sue Geuens• Donna Burbank

• Chris Bradley• Lee Edwards• Jon Evans• Erik Fransen• Brian McKenna• Nigel Turner• Mike Simons• Martha Bennett• Kamran Ashraf• Steve Jones• Michelle Teufel• James Kerr

Speakers Include:

• Learn From Your Peers. The conference provides an interactive forum where Data and BI Professionals can meet, discuss and debate how best to rise to the challenges faced by their organisations today and in the future. The 2014 conference attracted delegates from 28 countries.

• Five Conference Tracks with More Than 60 Sessions with a Focus on Case Studies. Learn from other organisations past successes and challenges from over 30 case studies. The five tracks include a dedicated track to Big Data.

• World Class Contributors. Broaden your knowledge and gain insights from internationally renowned experts including Claudia Imhoff, Peter Aiken, Rick van der Lans, Mike Ferguson, Jan Henderyckx, Alec Sharp, Martin Sykes, Barry Devlin, John Ladley and many more....

• Fifteen Pre-Conference Workshops. Choose from an unparalleled range of workshops on specific topics to get you quickly up-to-speed or fine tune your performance on Data and BI Essentials. Choose from introductory or advanced workshops.

• Post-Conference Workshops. New This Year! For the first time, there will be four full day post conference workshops. Enhance your in-depth knowledge and skills on Enterprise Data Management and BI best practices.

• CDMP Certification. On 2 November attendees will have the opportunity to take a refresher course and take the exams that lead to certification.

• Data and BI Solution Providers. Discuss your Data & BI challenges with the world’s leading solution providers.

• Attendee Satisfaction. Of those that replied 99% of the 2014 attendees said that they would recommend attending this conference to a colleague.

Sponsors:

Supported By & Media Sponsors:

Technology Evaluation Centers

CDO Forum4 NovemberAttendance By Invitation Only

We are pleased to announce the 17th Annual Conference on Enterprise Data and Business Intelligence, 2-5 November 2015, London. This is the leading independent and most authoritative data management gathering in Europe. New speakers and new presentations are featured along with many of the established experts in their field. The conference includes 15 pre-conference workshops and new this year are four full day post conference workshops. Delegates will have 5 conference tracks to choose from – two tracks on BI/DW, two tracks on Enterprise Data and an entire track devoted to Big Data. Conference sessions include:Advanced and Predictive Analytics, Agile Modelling, Analytically-Driven Enterprise, BI & DW BI Requirements, Big Data, Business Analysis Techniques, Cloud-Based Search and Data Analysis Communicating with Stakeholders, Data Driven Business, Data Governance, Data Governance Strategy for BI, Data Privacy and Protection, Data Science, Data Visualisation, Driving Your Data Governance Program, Enterprise Data Addressing, Enterprise Data Analytics, Enterprise Data Quality, Global Data Strategy, Hadoop and NoSQL, Implementing EDM Strategies, Information Governance, Legal Analysis of Big Data, Logical Data Warehouse, Master Data as a Business Driver, Open Data, Sustaining Data Quality, The Case for the CDO, The Power of Analytics, Using Big Data & Analytics and many more....Some of the featured organisations include Barclays, Standard Life, Rolls-Royce, Visa Europe, Ford Motor Company, United Utilities, Intel, Roche, PricewaterhouseCoopers, BT, IBM, GE Capital, The Copyright Licencing Agency, GE Oil and Gas, Forrester, Premier Farnell, GeoPlace, Microsoft, The Guardian, John Lewis, XL Catlin, Betfair, Computer Weekly, Capgemini, ComputerWorld UK, Cambridge Assessment, Mater Health Services, Ecolab, Coats UK, Storebrand ASA and many more....

Our four keynotes will challenge you and are guaranteed to invite discussion and a different way of thinking about data. Claudia Imhoff will be presenting ‘Unleash the Power of Analytics with the Extended Data Warehouse’. Peter Aiken will be presenting ‘The Case for the Chief Data Officer: Thinking Differently about Data Assets’. Alec Sharp will challenge you to think outside the box with ‘The Multi–Skilled Influencer – Getting Out of the Data Box to Achieve Data Management Goals’ and finally, best selling author of ‘Legacy’, James Kerr, goes deep into the heart of the world’s most successful sporting team, the legendary All Blacks of New Zealand, to reveal some powerful and practical lessons for leading change. This five track conference will focus on aspects such as: trends, design guidelines, product overviews and comparisons, best practices, and new evolving technologies. Networking with other professional colleagues and learning what is effective in other organisations around the world is another important reason to attend. In 2014, the conference attracted delegates from 28 countries. Our event features speakers from many countries with a wide variety of backgrounds, experience and knowledge. Finally, for the first time, we are running the CDO Forum on 4 November – attendance by invitation only.We look forward to seeing you in London in November, THE place where BI, Information Management and Data Professionals can meet and share their experiences, problems and solutions. We hope you will join us for what promises again to be an exciting and immensely valuable experience.

Jeremy HallManaging Director

Unleash the Power of Analytics with the Extended Data Warehouse Claudia Imhoff, President, Intelligent Solutions

Analytics are today’s business weapon of choice. Changing business environments and competitive pressures have driven companies to seek a new edge from innovative technologies such as Hadoop, specialized data stores, and the cloud. This expanding and constantly evolving set of data sources means

the enterprise data warehouse can no longer be the singular physical location for all large-scale information management. The Extended Data Warehouse (XDW) has emerged as the best architecture to enable companies to leverage all their data, and thereby unleash the full power of analytics. In this keynote Claudia will explore these critical questions:• What is the Extended Data Warehouse Architecture?• What are the use cases for each of the components in the extended

data warehouse?

• And what should you consider to ensure your success in this evolution?

The Case for the Chief Data Officer: Thinking Differently About Data Assets Peter Aiken, Data Blueprint and VCUReflections on Chief Information Officers (CIOs), combined with decisive

performance measurements, indicate that IT management has been asked to do a job that it cannot do well. Data are assets that deserve to be managed as professionally and aggressively as comparable organizational assets. Studies show that approximately 10% of organizations achieve a positive return on their investments in data. In the face of the accelerating

“data explosion,” this leaves most organizations unprepared to leverage a non-degrading, strategic asset. The redress assigns this vital, lacking function to its rightful owner and driver, the business. Transformation may require some organizational discomfort. We are confident organizations that successfully create CDOs will achieve improved organizational performance results. And further that these will directly and obviously come from better organizational data management stemming from the CDO leadership. Delegates will learn why the CDO should be:• Dedicated solely to Data Asset Leveraging• Unconstrained by an IT Project Mindset

• Reporting directly to the Business

The Multi–Skilled Influencer – Getting Out of the Data Box to Achieve Data Management GoalsAlec Sharp, Senior Consultant, Clariteq Systems Consulting

Sometimes, to hit the target, you have to aim slightly away from it. And sometimes, to achieve a goal, you have to aim for a completely different one. That’s how it is with Enterprise Data Management - in many cases, success has come from contributing to other initiatives. The catch? This requires skills not usually associated with pure data

management, plus a measure of trust and opportunism. We’ll look at many of these, backed up by real-life examples, with a focus on three in particular. In addition to showing how data management goals have been supported by applying these techniques, we’ll provide some useful tips and frameworks for each of them: • Business Process Change: Business processes work on “things” (a Part, a

Product, an Issue, etc.) which typically move through the process as data; we’ll look at techniques to make the “data” perspective valuable.

• Application Requirements: Use Cases and User Stories are well known techniques that many Business Analysts struggle with; we’ll look at an entity-based approach that overcomes some of the usual difficulties, especially in Agile settings.

• Facilitation: Questions that are standard practice for facilitators (“What do you mean by...”) can surface familiar data management issues of consistency and communication, particularly with senior management teams.

Exceptional Success Requires Exceptional Circumstances - the Success Secrets of the All BlacksJames Kerr, Author of ’Legacy’

James Kerr, bestselling author of ‘Legacy’, goes deep into the heart of the world’s most successful sporting team, the legendary All Blacks of New Zealand, to reveal some powerful and practical lessons for leading change. His keynote speech asks - what are the secrets of success - sustained success? How do you achieve

world-class standards, day after day, week after week, year after year? How do you handle pressure? How can a strong sense of purpose deliver higher performance? How do the best in the world adapt to stay the best in the world? The answer to these questions took the All Blacks from an exceptional 75% winning record over 100 years, to an extraordinary 86% over the years Kerr studied them - and they went last season undefeated. Kerr looks at how they did it and what it can teach us about leading a business, a team and a life. Insightful, informative and inspiring.

Conference Overview & Keynotes

View full conference programme on irmuk.co.uk/edbi20152

Welcome

Keynotes

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2 NOVEMBER 2015 - Pre-Conference Workshops

DW/BI DW/BI DW/BI Enterprise Data Enterprise Data Enterprise Data Enterprise Data Big Data

09:30-12:45

Business Intelligence & Data

Warehousing: A Primer Erik Fransen, Centennium

09:30-12:45

Designing the Logical Data Warehouse

Rick van der Lans, R20/Consultancy

09:30-12:45

Stories and Data VisualizationMartin Sykes,

Cambridge Assessment

09:30-19:00FULL DAY

Preparation for the Certified Data

Management Professional Chris Bradley,

Independent Consultant and DAMA

09:30-12:45

Data Quality: Getting Back to

Basics Sue Geuens, EPI-USE and DAMA

International

09:30-12:45The Human Side of Data Modelling – Communicating with Stakeholders and Other Mere

Mortals Alec Sharp, Clariteq Systems Consulting

09:30-12:45Driving Your

Data Governance Program: Best

Practices, Direction and Advice

John Ladley, IMCue Solutions

09:30-12:45Enriching

Customer Master Data Using Big

Data and Analytics Mike Ferguson,

Intelligent Business Strategies

DW/BI DW/BI DW/BI Enterprise Data Enterprise Data Enterprise Data Enterprise Data Big Data

14:00-17:15BI Requirements:

Deliver What Your Organization Needs, Not What It

Wants John Ladley,

IMCue Solutions

14:00-17:15Creating an

Analytically-Driven Enterprise –How to Implement an

Analytics Program Claudia Imhoff,

Intelligent Solutions

14:00-17:15Building a Data Driven Business:

Delights and Dangers

Barry Devlin, 9sight Consulting

CDMP Examinations -

three 90 minute sessions

14:00-17:15Making Enterprise

Data Quality a Reality

Nigel Turner, Global Data Strategy

14:00-17:15Business Analysis

Techniques for Data Professionals

Alec Sharp, Clariteq Systems Consulting

14:00-17:15Master Data as a Business Driver:

Little Data Can Make the

Difference Jan Henderyckx, Inpuls

14:00-17:15Explaining the Hadoop and

NoSQL LabyrinthRick van der Lans, R20/

Consultancy

3 NOVEMBER 2015 - Conference Day 1 & Exhibits

09:00-09:10 Joint Conference Chair Introductions: Rick van der Lans, R20/Consultancy & Sue Geuens, DAMA International

09:10-10:10 KEYNOTE: Unleash the Power of Analytics with the Extended Data Warehouse, Claudia Imhoff, Intelligent Solutions

10:10-10:35 Break and Exhibit

DW/BI DW/BI Enterprise Data Enterprise Data Big Data

10:35-11:25 Data Visualisation - An Introduction

Cathy Nockles & Jess Mufazzil, PwC

Pragmatic Data Governance in a Heterogeneous BI

Environment Julian Clemas-Howard, BetFair

Success Stories in Building a Global Data Strategy

Donna BurbankGlobal Data Strategy

A Team Approach to Data Quality

Shane Downey & Sue Gardiner, Mater Health Services

Ten Big Myths of Big Data Rick van der Lans, R20/Consultancy

11:30-12:20

Digging for Buried Treasure in Open Data

Geoffrey Roberts, Democrata & Simon Laws, IBM

Analytics in a Digital Age – The Good, Bad and Ugly Lessons Learned in

Adapting to New Business Requirements

Kamran Ashraf, Visa Europe

Data Dad, Data Mum, Data Parent

Andy Moore, Rolls-Royce

Panel: Data Privacy and Protection in the Epoch of Data

as an Economic ‘Fuel’ Brian McKenna, Computer Weekly,

Julia Porter, The Guardian, Ashley Rhodes, John Lewis,

Barry Connolly, Flynn O’Driscoll Business Lawyers, Daragh O Brien

CastlebridgeAssociates Liz Coll, Citizens Advice

Implementing Strategies to Make Enterprise Data

Management Cohesive Within the Enterprise Roberto Maranca

GE Capital

12:20-13:50 Lunch, Exhibit and Industry Innovation Sessions

12:50-13:15 Improving BI Delivery Using Data Virtualization Gordon Griffin, Voyanta The Monetisation of Big Data: Finding Value and Profit Jake Freivald, Information Builders

13:20-13:45 Ensuring the Business Requirements Are Met by Your Business Intelligence Project Mike Rochford, Advanced 365

13:50-14:50 KEYNOTE: Exceptional Success Requires Exceptional Circumstances - the Success Secrets of the All Blacks, James Kerr, Author of ’Legacy’

14:55-15:45 GE Oil & Gas Enterprise Data Analytics

Eulogio Barragán, GE Oil & Gas

Agile Modelling with Data Vault: Cases and Best Practices

Erik Fransen, Centennium

How to Be a Data Superstar Lee Edwards, Ford Motor Company

My Journey Through Data Governance

Garry Manser, Barclays

Managing Big Data - Stopping the Lake Becoming a Swamp

Steve Jones, Capgemini


16:15: 17:05

Leveraging Change Initiatives to Drive BI

Michelle Teufel, Premier Farnell

Closing Leads Faster and Increasing Profits Quentin Villon, Qualifa

Battle Plan: A Practical Guide to Sustainable Data Quality

Improvement Jon Evans & Gethin Swann-Price,

EQUILLIAN

Vendor Data Management for a Global Organisation Suresh Daniel, Coats UK

Panel: Beyond Big Data, Delivering Real Time Actionable

Business Intelligence to Your Organisation

Moderator: Mike Simons, ComputerWorld Panellists: Ian West, Cognizant;

Jake Freivald, Information Builders; Michal Klaus, Ataccama

Peter Thomas, BUPA

17:05-18:30 Drinks Reception and Exhibits 18:30 - 20:00 Room 101, DAMA UK

4 NOVEMBER 2015 - Conference Day 2 & Exhibits

08;15- 08:45 DGPO Meeting, John Ladley

09:00-10:00 KEYNOTE: The Case for the Chief Data Officer: Thinking Differently About Data Assets: Peter Aiken, Data Blueprint and VCU


DW/BI DW/BI Enterprise Data Enterprise Data Big Data

10:30-11:20 Advanced and Predictive Analytics for the Smart

Enterprise Mike Ferguson, Intelligent Business

Strategies

Data Visualization and the Balance Between Not Enough

and Too Much Mike Foster, Ecolab Europe GmbH &

Michael Foley, Evalueserve

Data Quality and Data Governance are the

Foundations to a Customer Driven Company

Louise Miller, Standard Life

Service Associations - What’s The Point?

John Daniels, United Utilities & Matt Beare, Beare Essentials Ltd

Turn Big Data into Business Success

Martha Bennett, Forrester

11:25-12:15 On Data Lakes, Reservoirs and Possible Swamps

Barry Devlin, 9sight Consulting

R as a Business Intelligence Tool - A Case Study from the

Insurance Industry Mark Chisholm, XL Catlin

The Power of Open Data Jason Perkins, BT

Is the Data asset REALLY Different?

Chris Bradley, Independent Consultant & DAMA

Harnessing Big Data for Revenue Growth, Mark Woodward, Intel

12:15-13:45 Lunch, Exhibit and Industry Innovation Sessions

12:45-13:10 Big Data and the Data Quality Imperative Ed Wrazen, Trillium Software

13:15-13:40 One Size Doesn’t Fit All – Dashboards for Strategic, Operational & Analysis Needs Peter Baxter, Yellowfin Data Governance - A Practical Approach, Semanta, Speaker TBC

13:45-14:45 KEYNOTE: The Multi–Skilled Influencer – Getting Out of the Data Box to Achieve Data Management Goals, Alec Sharp, Clariteq Systems Consulting

14:50-15:40 High Performance Cloud-Based Search, Data Management

and Analysis at the Copyright Licensing Agency

Adam Sewell, The Copyright Licensing Agency & Nathaniel Suda, Advanced 365

Accelerating Data-Driven Innovation in the Automobile

Industry Speaker/Company TBC

Leverage Internal and External Data with Linked

Data Principles for Integrated Reporting

Martin Schiesser, Firefly Information Management

Case Study: HR Test System - Data, Data Consistency and Privacy & Data Management.

Rafal Kosinski, Roche

A New Data Science Economy Sanjay Jacob, Microsoft Corporation


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5 NOVEMBER 2015 - Post-Conference Workshops

DW/BI Enterprise Data Enterprise Data Big Data 09:00-16:30 Maximising Business Value Using

Predictive Analytics, Self-Service And Collaborative BI

Mike Ferguson, Intelligent Business Strategies

Evolving Your Information Architecture: What? Why? How?

Peter Aiken, Data Blueprint & VCU

Getting to the Next Maturity Level With Information Governance: Delivering

Accuracy and Trust Jan Henderyckx, Inpuls

Driving a Data Culture with Data Science

Jon Woodward, Andrew Fryer, Amy Nicholson, Microsoft

16:10-17:00When is a Data Warehouse

Not Really a Data Warehouse? John Ladley, IMCue Solutions

Why You Need a Data Governance Strategy to

Support Your BI Nicola Askham, The Data Governance

Coach

An Enterprise Data Approach to Addressing

Simon Barlow, GeoPlace

Creating a Sustainable Analytics and Insight

Environment Jan Henderyckx, Inpuls

Legal Analysis of Managing Big Data

Barry Connolly, Flynn O’Driscoll Business Lawyers


Pre-Conference Workshops

BUSINESS INTELLIGENCE

Business Intelligence and Datawarehousing: A Primer Erik Fransen, Centennium

Both Business Intelligence and Data Warehousing have been around for almost three decades now and have definitely changed the way companies create and apply management information. The Data Warehouse facilitates the registration and unification of business data and in itself is able to create high business value. The data warehouse is the data driven fundament for Business Intelligence. Business Intelligence, the process of creating information products and insights through reporting and analytic, leverages the huge amounts of data by both data driven and goal driven analyses. Business Intelligence creates even more business value as it adds the relevant context to the business data. In this Workshop you will learn the basics of Data Warehousing and Business Intelligence. Topics covered include:• Data Warehousing and Business

Intelligence: basics and current state • The Agile Data Warehouse: registering all

the data, all the time, in all forms • Big Data Modelling the Data Warehouse

for agility: how to?• Master and Meta Data Management: the

glue that holds everything together • Business Intelligence: from reporting to

analytics, making the most out of the data warehouse Best practices for organising BI

Designing the Logical Data WarehouseRick van der Lans, R20/Consultancy

The classic data warehouse architecture has had a long and successful run, but we’re starting to stretch its abilities to the limit. The logical data warehouse is a modern alternative. It has an architecture consisting of less physical data stores, requires less redundant storage of data, is more suitable for operational BI, and is much more flexible. Mature technology in the form of data virtualization servers exists to develop a logical data warehouse. Products from Cisco, Denodo, Informatica, and RedHat, have proven that large BI systems can be developed using data virtualization. The logical data warehouse offers several practical benefits, including that it’s more agile, it makes adoption of big data easier and more seamless, it allows a management the self-service BI component, it can more easily exploit new data storage technologies such as Hadoop and NoSQL, and is more suited for operational BI applications. This workshop explains the architecture of a logical data warehouse and discusses numerous tips, tricks, and guidelines for designing and developing one.

Stories and Data VisualizationMartyn Sykes, Cambridge Assessment

The evidence proves that stories trump data when it comes to persuasion. Stories are easier to understand and relate to. Even so, many people are reticent to tell stories because they believe “the facts” will speak for themselves. Refusal to recognize the power of storytelling places you at risk of having your good information lose attention to less-worthy content.

In this workshop we will look at a few examples, but more importantly, review the techniques to be able to develop and deliver a story to communicate your data. A good data visualization, delivered with a compelling story can blow right through your audience’s mental filters, connect emotionally and increase information retention. If people can remember your content they can act on it.• Go beyond seeing other people’s examples to

understanding how to create your own data driven stories.

• Learn the science of stories for effective communication and influence.

• Link stories and data visualization techniques to increase your impact.

BI Requirements: Deliver What Your Organization Needs, Not What it WantsJohn Ladley, IMCue Solutions

It is a familiar scenario. Requirements are gathered, a solution is deployed, and the business says “This is not what we asked for.” For too long BI departments have struggled to deliver what the business needs vs. what the business wants. This is a result of applying traditional software development approaches and a stunning lack of business and IT alignment. Yet it is well known that aligning stated business objectives with business intelligence requirements improves both the top line and bottom line of the organization.

John will present the process and techniques to use a “metrics driven” framework to improve clarity but also speed up the business information requirements gathering process. Attendees will learn an approach to rapidly gather business requirements effectively and make the most out of your BI investments.

In this workshop you will learn:• How to align your business with BI projects • How to define unambiguous requirements• How to capture most of your required BI

requirements and metrics in an astonishingly short time

Creating an Analytically-Driven Enterprise – How to Implement an Analytics ProgramClaudia Imhoff, Intelligent Solutions

Analytics have become the darling of vendors, consultants, and the press. In addition, data scientists are now highly sought after by many enterprises. Yet, the adoption rate for analytics and BI is still hovering between 20 and 30% in most enterprises. Why? What is the problem? How can we improve the adoption of these critical decision support functions? What is needed to implement a successful analytics program?

These are some of the questions to be answered in this timely presentation by Dr. Claudia Imhoff.

Getting an analytics program up and running requires the following considerations:

• The need for analytics and enterprise strategy for acceptance

• Education – not just training

• The new way we work

• The data scientist, data priest, data interpreter, data engineer – who wins

• Best Practices in Data discovery and data visualization

Building a Data Driven Business: Delights and DangersBarry Devlin, 9sight Consulting

Data driven business is becoming increasingly important as social media and the Internet of Things offer ever larger quantities of data about people’s thoughts and behaviours, creating new business opportunities for interacting with customers, anticipating their needs and responding proactively to them. This same data allows invasion of personal privacy, customer alienation and market destruction. These opportunities and pitfalls demand much broader thinking and planning than traditional BI projects. This workshop covers:

• Business drivers and sample use cases for a data driven business

• Architectural approaches, evolution vs. revolution

• Positioning data, information, knowledge and meaning

• Context-setting information and the evolution of metadata

• Technology choices, focus areas for new tools, hype to avoid

• Defining a roadmap to and implementing a data driven business

ENTERPRISE DATA

Workshop Preparation for the Certified Data Management Professional (CDMP) Exams Plus Examinations x three 90 minute sessions Chris Bradley, Information Strategist Independent Consultant & DAMA

This workshop covers an overview of the process, tips and techniques of successful CDMP exam taking. In this interactive and informative session, you will learn:

• What is the CDMP certification process

• The DAMA-DMBOK & CDMP data exams alignment

• What topics comprise each exam’s body of knowledge

• Concepts and terms used in the CDMP exams • A Self-assessment of your knowledge and skill

through taking the sample exams.

EXAM: You will need to bring your own unencrypted Windows-based laptops – exams run off the USB drive• Three times 90 minute examination

sessions (in the afternoon). • Each exam is 90 minutes in length and

has 110 multi-choice questions

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• Your score is immediately known after exam is taken

• Exam fees for EDBI attendees are ‘pay if you pass’ ($285 each exam) for this class session.

Data Quality: Getting Back to BasicsSue Geuens, EPI-USE and DAMA International

When not talking about Data Governance or Master Data or Data Architecture, the topic of conversation is most likely to turn to Data Quality. A question Sue says she is often asked is whether quality is really important. And if it is, then the How? Where? When? and Who? become the next questions. In a similar manner to Sue’s Practical Data Governance workshop, she turns her mind to providing the answers to these basic questions with practical knowledge, some solid implementation “projects” and lots of down to earth advice. A number of group activities are planned to allow you to get the best out of the session and to leave with an idea of your own next steps! And yes, she will touch on Big Data and her thoughts around how to manage quality in so much data your head spins!

The Human Side of Data Modelling – Communicating with Stakeholders and Other Mere Mortals Alec Sharp, Clariteq Systems Consulting

Above all, data models should be seen as a means of enabling communication among different stakeholders, including decision-makers, content experts, business analysts, and designers. Unfortunately, the communication often gets lost, either in the clouds, in the weeds, or somewhere off to the side. Whether the modeller has drifted too quickly into abstraction and generalization, or has taken the “deep dive for detail,” the result is the same – confused, frustrated, or detached subject matter experts. The inevitable result? – inaccurate or incomplete models!

It doesn’t have to be this way - simple techniques, consistently and regularly applied, will go a long way to ensuring involvement, buy-in, and communication. Drawing on almost 35 years of successful data modelling experience, this presentation will describe core techniques, backed up by practical examples, for helping people appreciate, use, and possibly even want to build data models.

Topics include:• Unclear on the concept – how to think about

concept modelling;

• “Role induction” for clients – skip the “tutorial” on data modelling and Just Do It!;

• Conventions for comprehension – guidelines for data model graphics;

• “Scripts” for growing the model – the value of consistency;

• “Play well with others” - integrate data modelling with other techniques;

• Systems archaeology – show them what they’ve got, and why they don’t like it;

• Both sides now – presentation techniques for data modellers.

Driving Your Data Governance Program: Best Practices, Direction and Advice John Ladley, IMCue Solutions

If you believe information is truly an asset, then

engaging the entire business is mandatory. If managing information assets is a business issue, then data governance is a business program. Research shows none of the critical success factors for data governance have anything to do with technology

When business leaders are called upon to “do governance,”, they need to learn about concepts like stewardship, data quality, culture change and information management, all while still accomplishing their day-to-day responsibilities.

This workshop will walk the attendees through the assessment, definition, design and deployment of a data governance program from a business view. This presentation is intended for business leaders or managers that are new to data governance, or for data governance functions that are having trouble sustaining themselves. The workshop will cover:

• How to define Data Governance as a business program – from alignment to operations

• How to address the most critical success factors for DG

• Understand the basic core functions that MUST be executed to be sustainable

• Review a list of key metrics you can deliver immediately to show progress and success

Making Enterprise Data Quality a Reality Nigel Turner, Global Data Strategy

Many organisations are recognising that tackling data quality (DQ) problems requires more than a series of tactical, one off improvement projects. By their nature many DQ problems extend across and often beyond an organisation. So the only way to address them is through an enterprise wide programme of data governance and DQ improvement activities embracing people, process and technology. This requires very different skills and approaches from those needed on many traditional DQ projects.

If you attend this workshop you will leave more ready and able to make the case for and deliver enterprise wide data governance & DQ across your organisation. This highly interactive workshop will also give you the opportunity to tackle the problems of a fictional (but highly realistic) company who are experiencing end to end data quality & data governance challenges. This will enable you to practise some of the key techniques in a safe, fun environment before trying them out for real in your own organisations.

Run by Nigel Turner, the workshop will draw on his extensive personal knowledge of initiating & implementing successful enterprise DQ and data governance in major organisations, including British Telecommunications and several other major organisations. The approaches outlined in this session really do work.

The workshop will cover:• What differentiates enterprise DQ from

traditional project based DQ approaches

• How to take the first steps in enterprise DQ

• Applying a practical Data Governance Framework

• Making the case for investment in DQ and data governance

• How to deliver the benefits – people, process & technology

• Real life case studies – key do’s and don’ts

• Practice case study – getting enterprise DQ off

the ground in a hotel chain

• Key lessons learned and maxims for success

Business Analysis Techniques for Data Professionals – Getting Involved in Business Processes and Applications Alec Sharp, Clariteq Systems Consulting

Enterprise data management objectives are often met by stepping outside of a pure “data” focus and getting involved with other critical enterprise initiatives. In particular, data management professionals will benefit from skills in business process change, and requirements definition for custom-developed or purchased applications.

This workshop presents a practical, proven, and integrated set of model-based techniques for working with business processes and requirements. At enterprises of all sizes they have been relevant to the business, useful to developers, and surprisingly popular with Agile teams. (Come to the workshop to find out why!)

We’ll open with a quick review of bad advice in the world of business analysis (think “effective written requirements”), the consequences of applying it, and why it just doesn’t work. Next, we’ll look at methods for discovering, scoping, assessing, mapping, and redesigning business processes. Then, we’ll cover related techniques for discovering, documenting, and verifying application requirements using business service specifications (essential in a SOA environment,) and a unique form of use cases. In both cases, we’ll see how to make business-friendly concept models (conceptual data models) and useful logical data models a vital technique. Some of the questions that will be answered include:

• How can I develop useful models of end-to-end processes within my natural lifetime?

• When should I stop modelling the process and shift to other forms to capture requirements?

• Why separate use cases into external (use case) and internal (services) perspectives?

• How can I stay at the right level? How do I avoid the “deep dive for detail?”

• What’s the role of our old friend, data modelling, in all of this?

Master Data as a Business Driver: Little Data Can Make the Difference Jan Henderyckx, Inpuls

Big Data and Analytics are omni-present in many organisations and the mantra of statistical relevance is often used as an excuse for neglecting “little” data. If all your big data is in a data lake you still need to understand what the patterns and insight are describing. The context of these insights will be provided by the data for which you care to manage the life cycle. Proper management of the life-cycle of the business entities and their relationships can give a significant boost to your business outcomes. Unfortunately many master - and reference data projects are not providing the benefits that are anticipated. This workshop focussing on the elements that are essential for delivering effective MDM projects.

Is multi-domain the best approach for handling all your master data or should you look at the next model which is graph based models that have the ability to link and manage just about anything?

“Excellent event, would thoroughly recommend it to all data professionals. Would actively encourage potential delegates to attend pre-conference sessions, very informative sessions. The opportunity to listen and interact with so many like minded data professionals in one place.”Jimmy McGrath, Information Development and Improvement Manager, Care Quality Commission

“Really great event with an interesting and useful mix of speakers and topics.”Ellie Fitzpatrick, Data Governance Manager, Yorkshire Building Society Group

“The ability to validate the know and learn the unknown at the same time is the best reason to attend.”Garry Manser, VP Data Stewardship, Barclays

“Second time at this Conference, will be back but next time with my team!”Derek Lennox, Data Governance Manager, National Australia Bank Group

“Good variety, good to have different views on same subjects. Informative, can now “join the dots”

on capabilities for my organisation. Plenty of information, lots of food for thought.”Teresa Bateman, Solution Architect, Tesco Plc

“The conference continues to provide a comfortable and effective platform where we can learn new things, be reminded and refreshed in things we already knew and feel part of a data community which has similar challenges to ourselves.”Andy Moore, Process Specialist, Rolls-Royce

“I have greatly enjoyed this event. The material is very useful to me. I enjoyed discussing data management issues with like-minded professionals.”Rhonda Freeman, Autotrader

“Very good event, well organised and relevant particularly virtualisation, cloud and data strategy sessions.”Gerrard Deegan, Enterprise Data Architect, Ministry of Defence

“Great way to learn best practices, gain new insights and get ideas for change in your own organisation.”Weird van der Kooi, Sr. Data Manager, Nuon Vattenfall

“Another great event, learnt new and interesting challenges.”

Neil Storkey, Global BI Data Manager, British American Tobacco

“An excellent event which really helped me understand the new trends in DW/BI, Data management and Information System Quality. The couple of new things I have learned from this conference are the operational BI and the importance of metadata. I will recommend this event to my fellow professionals.”Sheraz Mustaq, Saudi Aramco

“I would attend this event over and over again. It’s worth all the effort! I must commend the organiser for a well done job. So far, this event marks the best of conference experiences in the past 10 years.”Abraham Afolabi, Data Manager, EC Harris LLP

“I was glad to find like minded professionals confirm several decisions I have made. Also glad to find several thought provoking and extremely useful nuggets that I can take back with me.” Overall value of event - 10/10.Chris Duffield, Principal Developer, Transport for London

“A very enjoyable and useful event. This is the first conference I have attended but I would certainly like

to attend further conferences. The venue and staff were excellent and it was very well organised.”David Jordan, Data Analyst, Land Registry

“The event was very energising... seeing other companies on the same journey, with the same issues was good to see. Some good take always... nuggets that will be employed back at work. Enjoyable event.”David West, Group Data Architect, Barclays Bank

“Extremely well organized, lectures were thought provoking. Many ideas I will take back to my organization. A lot more I now want to read about. I will recommend this conference to more business units next year. Thoroughly enjoyed it!”Neil Shah, Information & Data Risk Analyst, Capital one Bank

• Project Management

• Setting the right scope

• Defining the business case

• MDM and RDM design principles

• People, Process and technology

• Establishing a MDM organisational component

• How to bring the proper life-cycle management into your organisation?

• Do you need a MDM COE?

• Roles and responsibilities for managing the life-cycle

• Master Data and Reference Data Architecture Patterns

• Rule/Policy workflow based synchronisation, Registry Style, Virtual MDM, Enterprise MDM, Hybrid MDM

• Integrating with analytics

• Modelling the master and reference data

• How much common vocabulary is mandatory

• Dealing with different codesets

• Handling temporal aspects

• Market Overview

• Subject specific solutions

• Party MDM

• Product MDM

• Analytical MDM

• Subject agnostic Solutions

• Hierarchy Management

• Reference and code management

• Model Driven Architecture

• Graph-based Solutions

BIG DATA

Enriching Customer Master Data Using Big Data and Analytics Mike Ferguson, Intelligent Business Strategies

This workshop discusses how you can use Big Data and advanced analytical technologies to enrich customer master data for better customer engagement. It focuses on the different data sources you can use to get new customer insight, the types of data they provide and the analytics needed to produce new customer insight to enrich what you already know. It then discusses how to use that insight to improve customer engagement

• How well do you know your customers today?

• The role of customer master data

• Identifying new sources to enrich what you know about customers

• Assessing the characteristics of new customer data sources

• Using Big Data platforms and analytics to capture customer behaviour and previously unknown relationships

• Matching and integrating new insights with customer master data in a Big Data environment

• Identifying next best actions using predictive analytics on enriched customer data

• Leveraging next best actions for personalised customer engagement

Explaining the Hadoop and NoSQL Labyrinth Rick van der Lans, R20/Consultancy

MapReduce, Sqoop, Spark, Tez, Yarn, MongoDB, Cassandra, … and the list goes on. Many new data storage technologies have been introduced lately. Some with enormous scalability and performance capabilities. Their price/performance ratio for developing big data systems is unquestionable. But this tidal wave of new modules, technologies, and products have turned into a labyrinth.

Organisations need in-depth and extensive studies to be able to make well-substantiated decisions on which products they need to invest in.

This workshop explains:• The roles of all these new modules and

products

• Why do they exist, what are their strengths and weaknesses, when should be used and not used?

• A complete and critical picture is painted of all the new technologies for developing big data systems.


Pre-Conference Workshopsir

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Group Booking Discounts:

2-3 Delegates – 10 per cent

4-5 Delegates – 20 per cent

6 + Delegates – 25 per cent



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Maximising Business Value Using Predictive Analytics, Self-Service And Collaborative BI Mike Ferguson, Intelligent Business Strategies

An Overview of Predictive Analytics and Machine Learning

As we move into the era of smart business, looking back in time is not enough to make good decisions. Companies have to also model the future to forecast and predict so that they can anticipate problems and act in a timely manner to compete. Predictive analytics is a therefore a key part of any BI initiative and should be integrated into analysis, reporting and dashboards. This session introduces predictive analytics and how shows how it can be used in analysis and in business optimisation

• What are predictive analytics?

• Technologies and methodologies developing predictive analytical models

• Using supervised learning to develop predictive models for automatic classification

• Clustering data using unsupervised learning algorithms

• Deploying predictive analytical models in analytical databases

• Implementing predictive analytics in-Hadoop

• Accessing in Hadoop machine learning algorithms from data mining tools

• Integrating predictive analytics with event stream processing for automated analysis of high velocity events

Self-Service Data Discovery and Visualisation Tools

Self-service Data Discovery and Visualisation tools are frequently sold into business departments so that local business analysts can start building their own BI applications without having to wait for IT. This means that development often starts without any IT guidance and quickly spreads to other parts of the business with little thought for integration or re-use. The result is that inconsistency and chaos can quickly set in. This session looks at best practices in deploying Self-service Data Discovery and Visualisation tools to maximise business benefit in existing BI/DW environments

• What are Self-service Data Discovery and Visualisation tools?

• Interactive analysis and automatic charting using in-memory data

• The Self-service Data Discovery and Visualisation tools marketplace e.g. Qlik Sense, Tableau, Tibco Spotfire, SAP Lumira, Information Builders, SAS Visual Analytics, Yellowfin

• Accessing predictive analytics from self-service BI tools

• Accessing Big Data from self-service BI tools using SQL on Hadoop

• Best practice steps in deploying self-service BI applications

Sharing BI Content through Collaborative BI and Storytelling

One of the key requirements in the smart enterprise is being able to easily access and share BI content with others both inside and outside the enterprise. To make this possible, BI platforms need to simplify user interfaces while adding collaborative and storey telling capabilities. This session looks at how collaborative computing and BI come together to

facilitate easier sharing and communication of insight. • The challenge to older hierarchical ways of

working• The Facebook revolution – New technologies

for enterprise collaboration• Why use enterprise collaboration and social

computing?• Analytical communities in the enterprise• Decision making at strategic, tactical and

operational levels• Why Collaborative BI? • Requirements for collaborative and social BI• Types of user - information producers vs.

information consumers• Collaborative BI authoring for information

producers • Using collaborative BI for joint decision making

and knowledge sharing • Empowering the masses to create, share, search

and collaborate over BI and related content• Collaborative BI technologies, e.g. Antivia, IBM

Cognos Business Insight, LyzaSoft, , Panorama Necto, Tableau, SAP Lumira, Yellowfin

• Using portals together with collaborative BI

Mobile BI – Extending the Reach to New Devices

Now that mobile devices have made great strides in their rich user interfaces, one of the hottest new areas is business intelligence is Mobile BI. This session looks at how modern mobile devices can now connect to BI platforms to access insight from inside or outside the enterprise. It also looks at how dis-connected users are now supported and how mobile workers can participate in collaborative BI environments and act on business insight to improve business performance.

• Popular Mobile BI use cases

• What should be in a Mobile BI Strategy

• Types of BI user and mobile device usage

• How have BI platforms been extended to support mobile BI?

• The mobile BI marketplace

• Authoring mobile BI content

• Dos and Don’ts on Building content for mobile devices

• Mobile BI Security – what to look for

• Evaluating mobile BI for the information consumer

• What can a user do with mobile BI

• Accessing dashboards and alerts from a mobile device

• Alerting and KPI drill down off a mobile device

• Using predictive analytics for mobile BI action recommendations

• Catering for disconnected access to BI content

• Integrating mobile BI with other applications and services

• Integrating mobile BI into a collaborative BI environment

• Acting on Mobile BI via integration with operational business processes and applications

Evolving Your Information Architecture: What? Why? How? Peter Aiken, Data Blueprint

All organizations have information architectures. The question is how effectively do organizations use them. This tutorial teaches how to evolve and use your organization’s information architecture. It describes the information architecture’s strategic drivers and how to enhance components of the information architecture so they can become more useful without having to ask for budget and other resources. Other important related learning objectives include how to:

• Build repository functionality without justifying the cost of a traditional repository.

• Justify data-centric development practices and architectural solutions.

• Use existing legal and financial motivations to guide individual efforts.

• Employ architectural patterns and data profiling to jump start efforts to surface, understand, and make use of discoverable architectural components.

Upon completion of this tutorial, attendees will be in a position to develop and make use of the organization’s information architecture components in today’s environment.

Getting to the Next Maturity Level with Information Governance: Delivering Accuracy and Trust Jan Henderyckx, Inpuls

We have evolved from the age of automation to the information age. Proper information management and insights have become a linchpin that act as a catalyst for the execution of your business strategies. Information can be supporting or defining your business model. Having the data in your organisation is not enough as the true value comes from your ability to turn the data into operational information and insights that allow you to create business value and make strategic and tactical decisions. Aligning your information requirements with strategic business objectives is critical.

• Linking your business strategy to information flows

• Architecting the business semantics

• Information Enablement, establishing the information capabilities

• Capabilities required to support your information strategy:

• Persistency: Column Based Storage, Appliances, In-memory Computing, NOSQL, Hadoop, ..

• Positioning the information management patterns; virtualisation, Extract-Transform-Load, Enterprise Application Integration, Web services, Enterprise Service Bus, Change Data Capture, …

• Managing the information life cycle: ILM platforms

• Managing Accuracy and Trust

• Delivering quality and security

• Getting the business buy-in

Driving a Data Culture with Data Science Jon Woodward, Business Lead – BI & Analytics, Andrew Fryer, Evangelist – Data Science, Amy Nicholson, Evangelist – Data Science, Microsoft

Unlock the Value of Data Culture with Data Science and Machine Learning: Data culture within your organisation can deliver significant competitive advantage, drive additional revenue and savings, and help find creative consensual solutions to real-world company-wide concerns by enabling all employees to make better, fact-based decisions that enhance rather than clash with their intuition and instincts.

Getting Started with Data Culture: Executives from Finance, HR, Marketing, Operations, Sales as well as board-level IT ought to embrace putting data and data-driven next-generation business applications at the core of their strategic thinking.

Data is growing exponentially and it’s now possible to mine and unlock insights from it in new, often unexpected, yet at-last reliable, accurate and verifiable ways. Data science and machine learning have matured to the point of being relatively easy to use, and have left the domain of pure experimentation. Now is the best time to discuss and to consider the value and the opportunity of this combination of algorithmic thinking, statistics, data mining, predictive analytics, big data, and the more mundane issues of data quality in your organisation. Companies that carefully balance a portfolio of strategic and high potential data science projects with the key operational and supporting needs of day-to-day use of data will gain a competitive advantage from these approaches whilst managing the risk to their operations.

Data Dividend: IDC research, commissioned by Microsoft, shows that better outcomes from data and analytics projects correlate with greater competitiveness of an organization in its industry or enhanced ability to fulfil its mission in the public sector. Although correlation does not equate to causation, a growing body of research shows financial and productivity benefits directly linked to better data-driven decision making enabled by business analytics solutions.

Four characteristics distinguish leaders in analytics—the use of more diverse data types and sources beyond social media to include the Internet of Things (IoT), adoption of more diverse analytical and self-service tools, methods, and metrics suited to broad range of users from data scientists to business analysts and executives, distribution of insights to a more diverse audience of business users, and the right-time application of most timely data.

Business success is determined not by whether an organization invests in business analytics, but by how it invests in them and supports those initiatives. Leadership in business analytics requires competencies in data management, technology, human capital, process management, and strategy, budgeting, and resource allocation.

In this one day workshop learn the key issues to consider when embarking on Driving a Data Culture with a focus on leveraging Data Science within your organisation. We will also get hands on with the Azure Machine Learning tool and look at the Cortana Analytics Suite to understand the art of the possible.

BUSINESS INTELLIGENCE

CASE STUDIES

Pragmatic Data Governance in a Heterogeneous BI Environment Julian Clemas-Howard, Consultant Data Architect, Betfair PLC

Betfair operates in a very competitive market and in order to assist its decision makers maintain its competitive edge EDS is transitioning to a more distributed model for acquiring, storing and publishing Belfair’s enterprise data. Agility in presenting the right data to the right people at the right time as well as agility in developing new services is key to this transition. This talk will explore the ways data modelling technology is supporting EDS in this process which include:

• Providing the framework to allow stakeholders to create glossaries definitions and rules of business terms linked to real-world data objects.

• Have the ability to represent data artefacts not held in a traditional RDMBS

• Map all data objects to a Logical Data Model

• Use of data models to support the Agile development process.

• Data Lineage tracking

Analytics in a Digital Age – The Good, Bad and Ugly Lessons Learned in Adapting to New Business Requirements Kamran Ashraf, Head of Analytics & Insight, Visa Europe

There is an upheaval occurring in the payments industry – new entrants, propositions and ways to pay. Digital disruption will be a key factor in the evolution of the industry and this session will focus on why market players are succeeding or failing to leverage data and analytics as key enablers to deliver value:

• Card Issuers: Adapting the traditional banking channel delivery model to customers’ digital propensity

• Acquirers: Prioritising digital onboarding and value added services in a changing payments eco-system

• Merchants: Aligning today’s technology enabled customer with an omni-channel shopping experience

GE Oil & Gas Enterprise Data AnalyticsEulogio Barragán, Enterprise Data Analytics Strategy, GE Oil & Gas

GE is driving a new Industrial Revolution using data analytics to transform operations in order to increase productivity and profitability. This expertise has been turned inward to pilot a programme to drive big data solutions across GE’s sourcing globally.

Bespoke tools have been developed to provide first stage hindsight on how transactions have happened historically and insight into transactions across the whole of GE Oil & Gas to provide

foresight analytics by aggregating data across all platforms. Procurement analytics will allow GE Oil & Gas to look at all the transactions that have been made, give a variety of options and make robust recommendations to optimize purchasing globally.

This session will be a walk-through GE’s Enterprise Analytics journey covering some of the key technologies including an overview of:

• Enterprise data needs across GE and use cases

• Technology landscape and applicability to specific cases

• Lessons learned and vision

Leveraging Change Initiatives to Drive BIMichelle Teufel, Global Head of Information Mgmt, Premier Farnell

Change is good! Premier Farnell is currently going through an organisational transformation from a regional to fully global business. And while for some this can be a distressing time, for Information Management it is the perfect opportunity to transform the culture in parallel with the organisation. Seizing the Opportunity! Through participation in the transformation activities of process redesign and globalising KPIs, we are driving traction and adoption of best practice through the application of Business Intelligence capabilities and Information Management principles.

Learn how Premier Farnell leveraged organizational wide change to:

• Prove the incremental value in BI

• Obtain long term investment in tools and capabilities

• Establish discipline and governance of our Information Assets

Accelerating Data-Driven Innovation in the Automobile IndustrySpeaker/Company TBC

Data Visualization and the Balance Between Not Enough and Too MuchMike Foster, VP, BI and Analytics, Ecolab Europe Michael Foley, Senior Consultant, Evalueserve

This session describes how to create an executive scorecard that works for different levels of management? What is the best way to present data in order to drive business decision making? How to determine what is a Key Performance Indicator or just an Indicator? How do you keep management engaged and interacting with the dashboard on a regular basis?

Mike and Michael will discuss the following challenges: Data spread across the organization in different systems, in different formats, with different owners. Too many data points across many areas of the business and across many geographies. Data processes that are not mature. A management team that doesn’t have a long history of data driven decision making.

Key Learnings:

• Defining measurable and actionable metrics is the first step

• Designing the right vehicle for sharing the data – visual, easy to use, interactive, high-level and drill down capability at the same time


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• Flexibility – visualization tools have their limitations – innovative thinking and knowledge of tools are essential ingredients

• Driving adoption, evolving over time, pushing action & decisions

R as a Business Intelligence Tool - A Case Study from the Insurance Industry Mark Chisholm, Actuarial Analyst, XL Catlin

This presentation describes how R can be used as a business intelligence tool in the insurance industry by demonstrating how actuaries use R to create predictive models and provide interactive data visualisation. The cost of acquiring R, its flexible graphics capabilities and the abundance of open source package add-ons make it a useful addition to the BI suite.

One of the uses of R is to perform predictive modelling and review performance analytics. Techniques such as generalised linear modelling are easy to implement, and these can be used a starting point for conversations with underwriters. It also produces high quality charts, and the Shiny package extends this functionality by allowing the end user to interactively explore and visualise data through a web browser.

Attendees will learn:

• How R and associated packages relate to other business intelligence tools

• Examples of use cases for which R is a good fit

• How R works with data visualisation

High Performance Cloud-Based Search, Data Management and Analysis at the Copyright Licensing AgencyAdam Sewell, IT Director, The Copyright Licencing Agency Nathaniel Suda, Consulting Director, Advanced 365

The Copyright Licensing Agency issue licences to a wide range of education, public sector and commercial organisations to permit legal copying and reuse of published materials from books, magazines, journals and other sources. Advanced assisted CLA with an innovative project to develop a new cloud-based platform to give customers the ability to search and acquire additional rights instantly. Developed using sophisticated search technologies utilising their large database of titles, API’s were also provided to integrate with third-party systems to ensure a seamless experience for customers. Supporting the high performance front-end search tool is a datamart which also provides sophisticated reporting and analysis tools to enable the CLA to ensure rightsholders receive fair compensation for use of their work and provide valuable insight into usage and trends.

Delegates will learn:• Discussion of the business decision-making

process for use of cloud technologies in high-performance and business critical applications

• A real-world example where business intelligence and search tools are used to generate revenue streams

• Considerations for project success, especially with regards to multiple technologies, vendor partnership, and business stakeholder engagement

BEST PRACTICE

Data Visualisation - An IntroductionCathy Nockles, Senior Manager, UK Data Assurance Team, PwC Jess Mufazzil, Manager, UK Advanced Risk & Compliance Analytics, PwC

Cathy and Jess from PwC’s Data Assurance and Advanced Risk & Compliance Analytics practices will give an introduction to data visualisation. They will give an overview of some of the current and emerging tools available to visualise datasets large and small, along with emerging trends amongst their vendors and users. Next, they will highlight best practice design guidelines for refining your visualisations to convey their intended message with maximum impact and clarity, which can be applied regardless of platform to create successful and compelling presentations whether your visualisation is intended as a springboard for discussion or you wish to take a more directive approach. They will then discuss hot topics in data visualisation that businesses are currently focussing on to get the most value out of their existing data assets. Finally, they will deliver a live demonstration of some of their own recent visualisation work they have designed and delivered.

From the session delegates will learn:

• Factors to consider when choosing a visualisation tool and what the current trends are for vendors in the visualisation tool space;

• An awareness of visualisation best practice, including hints and tips to creating a successful and compelling visualisation; and

• Hot topics in data visualisation and how these can be used to deliver business value.

Digging for Buried Treasure in Open DataGeoffrey Roberts, Democrata Simon Laws, IBM

Open data is starting to be realized as an asset that can provide value across many different dimensions. Uses range from finding the nearest public toilet, understanding how our tax money is spent, or using infrastructure data from the Ordnance Survey to create more context relevant applications. Geoff will talk about how he is de-risking major infrastructure projects and the end-to-end process of creating, scoping and executing a proof of concept using open data to predict where archaeological artifacts might be found.

Agile Modelling with Data Vault: Cases and Best PracticesErik Fransen, Managing Consultant, Centennium

Data Vault is a popular data modelling method for enterprise data warehouses and is gaining year after year more attention and momentum throughout the world. Flexible, auditable and extendable data warehouses integrated with upcoming Big Data platforms constitute the new data delivery platform. Centennium has built many successful data vault data warehouses since 2007 and has extensive knowledge of designing and implementing data vault data warehouses. In this session we will share our best practices and discuss actual data vault cases within Finance, Government, Utility and Healthcare.

After this session you will be able to:

• Understand the need for agile data modelling for enterprise data warehouses

• Name the key components of data vault and understand how the data vault method and automation deliver agile data warehouses

• Understand the overall business case for data vault and name use cases in which data vault and automation create business value

Closing Leads Faster and Increasing Profits Quentin Villon, Senior Business Analyst, Qualifa

Capturing business data and manually producing activity and insight reports to showcase B2B telemarketing lead generation company Qualifa’s capabilities was time consuming and prone to errors. Using a spreadsheet, this was a two-hour daily activity resulting in a 20mb spreadsheet. Reports were circulated a day after the activity took place, so performance could only be acknowledged rather than influenced. Generating commission reports was a 48-hour task monthly. Producing campaign insight reports that highlighted Qualifia’s capabilities required several days to produce and the output was not reusable, despite it being a fundamental function to client acquisition.

Learn how Qualifa is using big data analytics software to realize a 43% increase in productivity and save approximately 50 hours per month on standard tasks.

• How business users can easily produce useful dashboards on top of complex data models

• What were the biggest challenges?

• Using BI as a competitive advantage

Advanced and Predictive Analytics for the Smart EnterpriseMike Ferguson, Managing Director, Intelligent Business Strategies

For most organisations, using descriptive BI to look at past business activity is no longer enough. The demand is now for deeper insight to predict the future and to guide the business into making the right decisions. This session looks at how organisations can use predictive analytics and incorporate them into existing environments

• An introduction to advanced and predictive analytics

• Types of analytic algorithms and their uses

• The importance of data preparation

• Approaches to using advanced and predictive analytics, e.g. in-database, in-Hadoop, in-stream and in-memory

• Using analytics in self-service BI tools and analytics applications via predictive APIs

• Big Data analytics use cases

• Getting started – do’s and don’ts, model management, alignment with business objective and organisational issues

Conference Sessions

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On Data Lakes, Reservoirs and Possible Swamps Barry Devlin, Founder and Principal, 9sight Consulting

New technology, especially in the Hadoop space, has become increasingly popular in recent years. To make sense of these tools, vendors, consultants and customers have begun to sketch architectures to position and fit the function together. Thus, we have seen the digging of Data Lakes and the emergence of architectural diagrams of Data Reservoirs and Refineries. However, this is still very early days. The definitions remain as varied as their sources and their claims controversial.

This session sheds light on these new analytics architectures:

• What is a Data Reservoir or Lake and how does it compare to a Data Warehouse?

• What is a Data Refinery and what is its relationship to ETL?

• What are the benefits and drawbacks of these new architectural components

• Do Reservoirs and Refineries replace or complement traditional architectural thinking?

• What technologies and tools are needed?

When is a Data Warehouse Not Really a Data Warehouse?John Ladley, President, IMCue Solutions

In memory and “Big Data” technologies are doing more than enable sophisticated analytics. It is possible that, given the correct circumstances, a data warehouse is no longer needed. At minimum, you need to consider that data warehouse may not be a mandatory component of your information architecture. This session will cover the various types of alternatives that are bringing us full circle back to a time when the data warehouse was an option.

• New technology – What are the new technologies that will cause fundamental changes in information architecture?

• How do I know – what are the circumstances that may affect my current data architecture?

• How do I determine if I need to adopt these new technologies, or should stand pat with current DW – type approaches?

Why You Need a Data Governance Strategy to Support your BI Nicola Askham, The Data Governance Coach

When you think of Business Intelligence the obvious thing is to focus on the wonderful reports and dashboards that can be created to support your business. However if the data you are analysing and reporting on is not of good quality then the value of the reports is seriously undermined. Join Nicola Askham, The Data Governance Coach in this session as she explains:

• Why you need a Data Governance Strategy to support your BI activities

• The importance of a Data Governance strategy

• How to begin creating your strategy

ENTERPRISE DATA

CASE STUDIES

A Team Approach to Data Quality Shane Downey, Manager Data Services, Mater Health Services Sue Gardiner, Practice Manager, Ambulatory & Outpatient Services, Mater Health Services

The healthcare landscape in Australia is rapidly evolving. Changes to the way hospitals are funded have meant significant changes to the way the Mater Hospital captures and reports on activity. During this presentation you will learn: • How the Mater used data to change business

practices resulting in a 65% improvement in data quality and completeness

• What data governance measures were put in place

• Future plans to make data quality fun!

Data Dad, Data Mum, Data ParentAndy Moore, Process Specialist – Information Management, Rolls Royce

Being a Parent is tremendously rewarding, helping to shape your child to be someone who enjoys life and brings value to others. Alongside joys and successes, Being a Parent can bring you difficulties and worries. Being a Parent is a responsibility which must be taken seriously.

Read again. Find and replace Parent with Data Manager and child with data.

Following on from a previous presentation looking at “The Marriage of Business and Data”, Andy will explore how insight gained from Being a Parent can be applied to our roles in the management of data, drawing on some examples from Rolls-Royce.

How to Be a Data SuperstarLee Edwards, Strategy Analyst, Ford Motor Company

Lee will provide a look at the main characteristics displayed by great data people and ideas on how to develop them.

In the ever busy corporate environment, personality and approach can be the key to getting noticed and succeeding in your goals. This session builds upon a real example of integrating data from across Europe and the US, augmenting examples of practical techniques with winning characteristics and strategies that have been learned during twenty years working to tame and improve data.

Delegates will learn:

• 20 things that all great data people do

• How to spot and exploit opportunities for personal development

• Tips on what has worked (and what didn’t)

My Journey Through Data Governance Garry Manser, VP Data Stewardship, Barclays

Having worked with data for a number of years Garry has seen various attempts at implementing data governance in a myriad of organisations. This presentation will take you through his experiences, the good times, the bad times and the surreal ones.

Garry will share the errors he has seen made and also the errors he made himself but more importantly what he learned from them and how he fixed the issues. Rather than be process and framework based, this presentation will cover the sometimes forgotten factor of data governance, the people in our organisations and how we can use them, characters and all, to support the implementation and business as usual activities of Governance. Examples will include identifying data owners and stewards, through governance forums and revising processes.

Specifically it will cover:

• Identifying mistakes that can be made when implementing data governance

• How a bad experience can be made good

• Why people are the most important asset…….

• ….. and how to use them correctly.

Vendor Data Management for a Global Organisation Suresh Daniel, Coats UK

The majority of blue chip organisations have embarked on their vendor data management journey and yield the benefit. Compelling business cases to manage vendor data as a corporate asset vary based on individual business requirements. Rapid improvements in the data and analytics technology space has demanded control on vendor data DNA, this will escalate further as governments try to impose regulation to control data and to automate banking transactions. Delegates will learn:• Vendor data related business scenarios that

deliver your ROI• Various approaches to manage your vendor data• Trade-off between rapid agile deployment options

and vendor data management journey • Lessons learned

Data Quality and Data Governance are the Foundations to a Customer Driven CompanyLouise Miller, Head of UK Customer Data, Standard Life

To deliver their strategic objective to become a customer driven company, Standard Life needs to deliver unique, differentiated customer experiences, informed by greater understanding of what customers need now and in the future, and what part Standard Life can play in shaping their journey for them. Delivering this experience requires robust, holistic and dynamic data, available for all those who require it, which can respond to the needs of the business to deliver key insights and drive customer understanding. Data quality and data governance are the foundations to the success of this programme. Standard Life’s key objectives are to drive:

• Improved customer experience

• Improved business decision making

• Reduce risk

• Reduce costsService Associations - What’s The Point? John Daniels, Data Delivery Lead, Business Architecture, United Utilities Matt Beare, Beare Essentials Ltd

To deliver an improved experience for their customers United Utilities have two over-arching strategies:


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• Improved knowledge base for their Customers and where they are located

• Improved knowledge base of their Assets and the service they provide.

The additional strategic link is to effectively manage which assets serve which customers for what purpose. This will enable United Utilities to:

• Provide a consistent link between customers and assets

• Trace up and down the service chain to manage the impact assessment of planned works and respond proactively to service incidents

• Provide greater insight into strategic investment programmes

In this presentation John and Matthew will look to:

• Discuss the data enrichment needs and the location aware methodology they have adopted to deliver this strategy, and

• Demonstrate examples of how that data can then be used to the advantage of the business and the benefit of the Customer.

The Power of Open DataJason Perkins, Decision Support Chief Architect, BT

Join Jason to hear about the opportunities and transformation that is possible for your organisation from the increasing open data being made available in both UK and the rest of the world. You will be taken on a journey through real world studies using open data as part of an expanding information eco-system. You will hear how they adapted the best of traditional Data Management frameworks, patterns and agile methods including;

• Emerging Open use cases - Competition and benchmarking, Innovation and Performance, productivity & variance

• Open Information architecture – How open data aligns with traditional BI architecture and big data architecture; Information maturity model and Data modelling (traditional & adaptive techniques)

• Open data technical architecture & Information usage patterns

Case Study: HR Test System - Data, Data Consistency and Privacy & Data Management Rafal Kosinski, Expert, Data Manager, Roche

In most ERP environments the implementation of a new solution requires reliable testing before deployment to the production system. In most cases the achievement of this takes place only with the right data in the test system. Data Management in such a system should take into account not only data availability for testing but also data privacy and consistency. Since application users utilize the test system extensively, Data Management plays a crucial role in the successful test performance there. Meeting users’ expectations related to test data and at the same time being compliant with legal aspects is a serious challenge for data managers. From this case study you will learn:

• What are the conflicts between users’ expectations and organization’s data policy

• How the proper data for the test system is being constructed in global HR system CHRIS at Roche

• What are the main challenges for data

management and how to cope with those

An Enterprise Data Approach to Addressing Simon Barlow, Head of Information Management, GeoPlace

GeoPlace is one of the UK’s foremost managers of complex address-based national spatial datasets. They manage the National Address Gazetteer of over 40 million records – analysing and synchronising 2,599,000 changes and carrying out a total of 3,440 data validation checks every 6 weeks. They work with hundreds of stakeholders across the country on a daily basis to derive an increase in data quality and classify data through its entire life cycle, from plot to postal to demolition.

As well as building and managing the National Address Gazetteer, GeoPlace has audited, cleaned, analysed and matched hundreds of millions of records from the public and private sectors ranging from small local datasets to nationwide taxation, census, customer records, licensing and command and control systems.

During this presentation, Simon will demonstrate how an enterprise approach to address management and practices such as data audits and compliance with data standards enforces quality, enabling organisations to derive greater worth from their data holdings. Using case studies, Simon will present examples of how inconsistent data management results in lost revenue and poorer service provision and how enforcing data quality optimises the long term value of data assets.

BEST PRACTICE

Success Stories in Building a Global Data StrategyDonna Burbank, Managing Director, Global Data Strategy

More and more businesses in today’s information-driven economy understand the need to use data for strategic advantage. Unfortunately, while these organizations understand the critical importance of developing a global data strategy, many don’t know where to begin. This session de-mystifies the building blocks of a global data strategy, and highlights a number of real-world success stories from organisations who have developed successful data strategies. Topics include:

• Aligning data strategy with business motivations & drivers

• Defining the core building blocks of a successful data strategy

• Using the DMBoK as a strategic guide

• Success Stories in Global Data Strategies from organisations in Energy, Telcom, Pharmaceuticals, and Financial Services

Is the Data asset REALLY Different?Chris Bradley, Information Strategist, Independent Consultant & DAMA

How many times have we heard it said “Data is an asset” and that “it’s got to be managed professionally”, and even from the data community that “few people in the business understand us”

and so on? However successful organizations have managed various critical types of assets for many years People, Money, Property and so on.

• So just what is so different about the “data” asset?

• Is it really so unlike from other types of assets?

• Does this asset demand a different approach to its management?

In this session we will discuss the notion that Information is at the heart of all businesses and that the Information Architecture provides the unifying language, lingua franca, the common vocabulary upon which everything else is based.

We will also discuss the problem that the way in which data modelling is being taught in many academic institutions and it’s perception in many organizations does not reflect the real value that data models can realize in helping companies develop & exploit their information architectures effectively.

And of course the question “is the data asset REALLY different” will be discussed in detail by:

• Comparing the “data” asset with 7 other asset classes:

• Identifying and discussing 5 characteristics of “assets”

• Assessing the 7 asset types against the 5 asset characteristics to see if any patterns emerge

• Comparing the data asset against the 5 characteristics for assets; and then

• Determining if the data asset is so different from the other asset types

Finally IF there is a big difference, what actions should organizations take to manage this asset effectively?

Panel Discussion: Data Privacy and Protection in the Epoch of Data as an Economic ‘Fuel’ Moderator: Brian McKenna, Business Applications Editor, Computer Weekly Panellists: Julia Porter, The Guardian Ashley Rhodes, Customer Data Manager, John Lewis Barry Connolly, Solicitor, Flynn O’Driscoll Business Lawyers Daragh O Brien, Managing Director & Lead Consultant, Castlebridge Associates Liz Coll, Digital Policy Manager, Citizens Advice

Is the European Union’s proposed General Data Protection Regulation likely to make life easier for companies? Will it add a layer of complexity that will harm the economic performance of companies active in the Union? Or, on the contrary, will it simplify a current bureaucratic morass of privacy and data protection laws specific to each member state?

Whatever will be the implications of European data protection regulation, there will be plenty of work for data management professionals to do. Moreover, as companies and other organizations, increasingly turn to customer data as an asset to be exploited, what ethical choices should govern their practice? Just because you can – thanks to new data-focused technologies and techniques – does not mean you


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should.

And for individuals, can they realistically own their own data? And, if they can, how can they gain materially from that ‘ownership’?

This panel will tackle the most pressing issues concerning data protection and privacy from legal, business, and data professional viewpoints. Battle Plan: A Practical Guide to Sustainable Data Quality ImprovementJon Evans, Information Strategist, EQUILLIAN Gethin Swann-Price, Information Architect, EQUILLIAN

The constant battle against errant data requires commitment, determination and stamina – but can manpower alone win the data quality war? Ask any battle-scarred data steward that question and the answer is clear – without a good understanding of the various techniques for improving data quality, and how to apply each to its maximum advantage, their efforts will be short-lived.

In this enlightening talk, Equillian’s Jon Evans and Gethin Swann-Price explore the ingredients of a data quality battle plan – the essential weapons that every organisation needs to deploy to support its data quality troops and ensure long-term success.

The session will provide delegates with plenty of practical know-how, including:

• An assessment of the relative merits of different data quality techniques

• A progressive approach for controlling the trajectory of data quality

• A logical framework for continuous data quality improvement

Leverage Internal and External Data with Linked Data Principles for Integrated Reporting Martin Schiesser, Founder & CEO, Firefly Information Management

Data is now regarded as one of the most important assets of an organization. The increasing volume and detail of information captured by and about organizations, the rise of social media, and the Internet of Things will fuel an exponential growth in data for the foreseeable future. Because of growth, mergers & acquisitions and changes in company structure, organizations are not able to manage their data most effectively to create value. This makes it difficult to stay on top of an integrated data management solution. Rather than just consolidating data sources in a data warehouse, the linked data approach is a paradigm change to semantically integrate structured and unstructured company data with other systems and sources within and also outside the organization. The presentation will show the synergies at the use case integrated reporting how you can leverage these principles

• Understanding the fundamentals on how to establish semantic MDM as a data layer for integrated reporting in an enterprise

• Showing client use case integrated reporting to integrate web data & big data

with master data

• Leveraging the pros & cons of cloud master data solutions – how to start small & scale up

Creating a Sustainable Analytics and Insight Environment Jan Henderyckx, Managing Partner, Inpuls

Too often we see people embark on a data insight journey without addressing the data management fundamentals. The end result is a group of data scientists that are disconnected from the business and that could expose data that could even lead to fines and compliance breaches.

Having a data lab up and running does not equal a sustainable integration into the operational and strategic fabric an organisation.

• Setting the scene: Defining a sustainable Information centric organisation

• Environmental aspects of data lab adoption

• Positioning Information Governance in a CDO context: Information innovation as a driver

• Drowning in the data lake or having a breach? Data Governance as a safeguard

BIG DATA

CASE STUDIES

Implementing Strategies to Make Enterprise Data Management Cohesive Within the EnterpriseRoberto Maranca, Enterprise Data Lead, GE Capital

Roberto will discuss how GE Capital, the financial arm of General Electric (with 50K employees it represents one third of GE Revenues and it is present in 50+ jurisdictions), implemented strategies to make Enterprise Data Management cohesive within the enterprise.

• Designing a program that brings together stakeholders and functions

• Effectively communicating the goals of a data management program to aid a strategic business goals

• How to launch a data management initiative as a joint effort between data management and business groups

In 2013 GEC committed to a global Enterprise Data Management initiative and appointed its first CDO in 2014.

BEST PRACTICE

Ten Big Myths of Big Data Rick van Lans, R20/Consultancy

It always happens when a topic becomes trendy, when everyone gets involved: confusion rules. This has clearly happened with today’s biggest trend: big data. Many blogs, articles and books have been written on the topic, and countless sessions have been presented discussing its merits. But not all paint the right picture. In this critical session the ten following tenacious myths on big data are discussed.

• Analytics demands big data

• Big data is textual and unstructured data

• More data is better

• Analytics together with big data are disruptive

• Store everything, because we can – the coming of data lakes

• It’s big data when it doesn’t fit in a relational database

• Eighty percent of all data is unstructured

• Big data is big information

• Big data complements the data warehouse

• Big data is Hadoop!

Managing Big Data - Stopping the Lake Becoming a SwampSteve Jones, Global Vice President, Big Data, Capgemini

Garbage in, Garbage out. This truism is not new only for Big Data but it has become significantly more impactful as the move has begun away from traditional schema based approaches to more flexible and dynamic file system approaches. Many companies are finding that early stage successes rapidly become mid-term failures as data poured into Hadoop can no longer be managed and marshaled effectively, creating a cycle of reduced effectiveness and increased cost. This session covers how Big Data changes the way that information needs to be managed, how traditional approaches like MDM need to change and how new technologies and methods such as machine learning and business meta-data become crucial to the long term viability of a heterogeneous Big Data infrastructure. In the session people will learn:

• How governance needs to change for Big Data

• How the drive to smaller insight projects changes the way you deliver

• What foundations you need to build today to ensure long term success

Panel Discussion: Beyond Big Data, Delivering Real Time Actionable Business Intelligence to Your Organisation Moderator: Mike Simons, Associate Editor, CIO.co.uk, ComputerWorld UK and Techworld Panellists: Ian West, VP, Enterprise Information Management Practice, UK & Ireland, Cognizant Jake Freivald, Vice President, Product Marketing Information Builders Michal Klaus, CEO, Ataccama Peter Thomas, Head of Business Intelligence, BUPA

Don’t be blinded by the Big Data hype and don’t be disillusioned that the promise of Big data has for many, not yet been fulfilled. The challenges facing every organisation and the data and technology professionals within them are to identify data worth analysing, matching data to business functions and determining which data will deliver real results. Join this session to hear from some of the most innovative companies explaining how they use Big Data to drive commercial opportunities and business transformation.

Turn Big Data into Business Success Martha Bennett, Principal Analyst BI/Big Data, Forrester

What’s so big about big data? Vendors use the term


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for marketing, while buyers think of a new project or digital technology. Forrester defines big data as the practices and technologies that close the gap between the data available and the ability to turn that data into business insights.

Closing that gap and achieving long-term success requires you to think and act differently. You must find ways to become more predictive, so that you can serve empowered customers.

Join Martha to learn what impact the big data explosion will have on your business, what the real opportunities and risks are, and how you can become more predictive to better serve your customers.

Harnessing Big Data for Revenue GrowthMark Woodward, Analytics & Insights Manager, Intel

In today’s business climate, more and more organisations need to understand how they can make sense of and derive value from a diverse range of data sources. The technology world is becoming ever more complex and as it does, the different ways in which data can originate and be collected is becoming equally complex. In this session, you will hear about industry best practices as well as real, high-value proof points on how Intel tackles this challenge and some of the success stories achieved internally. Key Takeaways:

• How to internalise your own data for real business ROI

• A look at how to turn Business Intelligence into a Competitive Advantage

• Intel’s vision for Big Data

A New Data Science Economy Sanjay Jacob, Global Head, Cloud & Enterprise Businesses, Strategic Industries, Microsoft Corporation

Which customers are most likely to buy your products and services? What marketing mix will maximize revenue? Which personalized treatment plans are best for patients? How does one predict and fix elevators, trains and roads before they need repair? How will citizens respond to Government proposals?

Agile organizations are harnessing large volumes of data (Big Data) to generate advanced insights. Software and the rise of cloud services have given rise to revolutionary new economies. Only a few years ago, it would have been hard to imagine developers authoring a million apps for smartphones. Cloud-centric economies are permanently changing the way people author, create and share in the knowledge economy. The next big software economy will be the Data Science Economy – one where data scientists build predictive models and intelligent services that can be published and monetized as easily as apps for the mobile phone. Attend this session to learn how you can generate advanced data-driven insights.

Legal Analysis of Managing Big DataBarry Connolly, Solicitor, Flynn O’Driscoll Business Lawyers

The collection and processing of data in an ever increasing volume, variety and velocity has advanced at a rate that legal regulators could never have anticipated. One significant area of friction is the interface between Big Data and Data Protection Law. This session will review the proposed General Data Protection Regulation, in particular:

• How certain aspects of the law apply to Big Data

• How the proposed regulation impacts Big Data management.

However, legal regulation should not be seen as inherently restrictive. As the value that can be derived from Big Data is immense, this session will also highlight law available to protect that value. Intellectual property (IP) may be generated in collecting and processing Big Data. Such IP can protect much of the inherent value in Big Data analysis. Organisations, with substantial investments in Big Data projects, should be aware of this IP, such as:

• Copyright as it may apply to Big Data analysis

• Database rights surrounding the processing of Big Data

INDUSTRY INNOVATION SESSIONS

Big Data and the Data Quality Imperative Ed Wrazen, VP Product Management, Big Data, Trillium Software

Successful Big Data initiatives rely on accurate, complete data, but the information they draw on is often not validated when it enters an organization. In this session we will look at the challenges big data brings to an organization, and how data quality principles are adapting to ensure business goals and return on investments in big data are realised. We will cover:

• Challenges of big data

• Turning data lakes into reservoirs

• How data quality tools are adapting

• Why data governance disciplines remain crucial

Improving BI Delivery using Data Virtualization Gordon Griffin, Chief Technology Officer Voyanta

Voyanta provides SaaS to commercial real estate investors, lenders and asset managers. Designed to provide a complete 360 degree view of asset portfolios, putting new insights at the fingertips and highlighting key risks, Voyanta enables competitive advantage and superior investment performance for its customers. This session describes how Voyanta re-engineered their BI and data transformation architecture to keep pace with rapid data expansion and a continual demand for new reports and data transformations. Based on data virtualization, their new architecture provides a more flexible platform enabling faster delivery of data and more flexible data architecture and transformation.

The Monetisation of Big Data: Finding Value and Profit Jake Freivald, Vice President, Product Marketing, Information Builders

This valuable session uses actual case studies to illustrate how organisations are innovating, changing and growing their business with big data. The presentation will discuss the data requirements and the front-end analytic applications used to deliver game changing big data initiatives. The data requirements covered include the sourcing of data from sensor machinery, business data, industry data, research data and social media. The application

requirements will consider internal analysis, external delivery and revenue generating opportunities.

One Size Doesn’t Fit All – Dashboards for Strategic, Operational & Analysis Needs Peter Baxter, Managing Director - EMEA, Yellowfin

Dashboards are frequently cited as the most important technology for implementing business driven BI and analytics. However, many analysts agree that the majority of today’s BI dashboards fail to address the business needs.

Join us, as we discuss how you can ensure you are building dashboards that create real value for your business.

Attend this session to:• Understand the three different types of

dashboards your business needs• Discover the importance of delivering dashboards

to the right people, at the right time• Realise the power of sharing your insights

Ensuring the Business Requirements Are Met By Your Business Intelligence Project Mike Rochford, Business Development Manager Advanced 365In our experience, there are two main reasons why BI projects fail, either the IT team don’t understand the business requirements, or the business fails to define the requirements for the IT team to deliver. During the session I’ll be covering how to build a plan for your BI project to ensure success, and how to approach the various elements that need to be included in the plan.

Data Governance - a Practical Approach Speaker TBC, SemantaA case study describing how Data Governance can be established from the bottom-up over a few months. Be inspired by successful real-life services (like Google, Wikipedia, Twitter) and combine and adapt them to deal with the complexity of a Corporation. We provide you with the tools to set the rules for tasks dealing with data and information and specify their ownership. We allow you to describe the information environment in an e2e context, bring it to users in a visual form and manage its life-cycle easily and transparently. The case study will show:

• How to create an Information Portal that supports business users in becoming self-reliant in finding, understanding and analysing enterprise information and data.

• How to work with metadata from different sources and display them to business users in their context.

• How to manage the life-cycle of information objects


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