the journey to trusted data and better decisions

Copyr igh t © 2012 , SAS Ins t i tu te Inc . A l l r i gh ts reserved .

The Journey to Trusted Data and Better Decisions Trusted data is the key enabler to critical decisions about customers, products and operations.

Felix Liao Solutions Manager, Data Management – SAS Rick Andrews Senior DQ Specialist, Business Intelligence Centre of Excellence – Telstra


http://www.flickr.com/photos/21662985@N05/7003498639/sizes/l/in/photostream/

Business Analytics is the engine and Data is the Oil of the 21st Century Accurate Decision Making Requires Trusted Data Trusted Data needs End-to-End Governance


VOLUME VARIETY VELOCITY

TODAY THE FUTURE

DA

TA S

IZE

Todays Challenges


The Data Continuum Managing Data from Click-to-Insight-to-Value. Eg. Single Customer View

Data Integration & Transformation

Data Quality Services

Business Dictionary

Lineage Relationships

Master Data Governance

Business Rules Repository

Monitoring Dashboards

Business User DQ Analyst Data Steward

IT and Business Collaboration

360 Degree View of Customer

Personalised Real Time Marketing

Offers

Contact & Channel Optimisation

Social Network &

Media Analysis


The Journey to Better Decision Making: Data Governance Maturity Model

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A JOURNEY TO TRUSTED DATA

RICK ANDREWS 21 MAY 2012

A JOURNEY TO TRUSTED DATA | RICK ANDREWS | 21 MAY 2012

ABOUT YOUR SPEAKER

RICK ANDREWS, SENIOR DATA QUALITY SPECIALIST BUSINESS INTELLIGENCE CENTRE OF EXCELLENCE, TELSTRA.

RICK HAS BEEN WORKING FOR OVER 25 YEARS IN THE TELECOMMUNICATIONS INDUSTRY, DESIGNING AND MANAGING APPLICATIONS TO DELIVER IMPROVED CUSTOMER EXPERIENCE.

THE PAST 10 YEARS HAVE SEEN A PARTICULAR FOCUS ON DATA QUALITY PROGRAMS BRINGING EXPERIENCE TO DELIVER KEY INSIGHT INTO THE GOVERNANCE AND METHODOLOGY REQUIRED TO ACHIEVE SUCCESS.

RICK HOLDS A MASTERS OF BUSINESS ADMINISTRATION SPECIALISING IN INFORMATION SYSTEMS, WITH A BACKGROUND IN ELECTRICAL ENGINEERING.

CONTENT

-  About Telstra -  The Information Journey – Information Factory -  The Challenge – Data Trust -  The Solution – A Data Quality Firewall -  Data Quality Firewall Framework – Overview -  Initial Dimensions of Data Quality -  Initial Data Quality Measure Matrix -  How It Works - Simple Version -  Data Quality Firewall – Project Approach -  Data Management – A Holistic Approach


TELSTRA IS AUSTRALIA'S LEADING FULL SERVICES TELECOMMUNICATIONS AND INFORMATION SERVICES COMPANY, WITH ONE OF THE BEST KNOWN BRANDS IN THE COUNTRY.

TELSTRA OFFERS A FULL RANGE OF PRODUCTS AND SERVICES TO MEET THE NEEDS OF OUR CUSTOMERS. OUR TELECOMMUNICATIONS SERVICES PROVIDE VAST GEOGRAPHICAL COVERAGE THROUGH BOTH OUR FIXED AND MOBILE NETWORK INFRASTRUCTURE - SERVICING MANY MILLIONS OF AUSTRALIAN CUSTOMERS.

IN 2010-11, SALES REVENUE WAS $25.0 BILLION AND REPORTED EBITDA WAS $10.2 BILLION.

IN 2010-11, TELSTRA GENERATED $5.5 BILLION OF FREE CASH FLOW AND PAID $3.5 BILLION IN DIVIDENDS TO SHAREHOLDERS.

TELSTRA HAS ONE OF THE LARGEST SHAREHOLDER BASES IN AUSTRALIA, WITH 1.4 MILLION SHAREHOLDERS AND MILLIONS MORE INVESTING THROUGH SUPERANNUATION FUNDS.

TELSTRA EMPLOYS ALMOST 40 THOUSAND PEOPLE AROUND THE WORLD.


ABOUT TELSTRA

IN 2010-2011 TELSTRA:

HANDLED 3.6 BILLION LOCAL CALLS, 5.4 BILLION NATIONAL LONG DISTANCE MINUTES, 9.9 BILLION TEXT MESSAGES AND MORE THAN 13.5 BILLION MOBILE VOICE TELEPHONE MINUTES.

PROVIDED 8.4 MILLION FIXED LINE AND 12.3 MILLION MOBILE SERVICES, INCLUDING WHOLESALE SERVICES.

COMMENCED WEEKEND TECHNICIAN SERVICES, WITH AROUND 80 THOUSAND WEEKEND APPOINTMENTS USED BY CUSTOMERS.

LAUNCHED 24/7 CONTACT CENTRES, WITH MORE THAN 5 MILLION CALLS MADE TO US AFTER HOURS.

IMPLEMENTED TELSTRA.COM IMPROVEMENTS WHICH HAVE ENABLED MORE THAN 300 THOUSAND CUSTOMERS TO ACTIVATE INTERNATIONAL ROAMING ONLINE.


ABOUT TELSTRA’S SERVICE

THE INFORMATION JOURNEY INFORMATION FACTORY


BUSINESS EVENTS occur & raw data is created

1

PROCESSES to extract, transform and load data are

applied by computer systems in the Enterprise Data Warehouse

3

FINISHED INFORMATION in the form of reports, self-serve

access, analytics access, etc. is delivered to the business to

enable decision making

4

TRUST QUALITY is critical to

data & information usage & business

adoption

5

Subassemblies of INFORMATION such as employee & product

hierarchy, market analysis, etc. may be combined

2

CORPORATE DASHBOARD

SELF SERVE ANALYTICS

Accurate

Complete

Timely

Trusted

Relevant Understood Engineered

THE CHALLENGE DATA TRUST


It’s hard to manage and trust data when you don’t know exactly where its come from or what quality it is

SOURCE SYSTEMS LEGACY REPORTING PLATFORMS

CANNED REPORTIN

G

SQL DATA EXTRACT

BUSINESS CHALLENGES

Reconciliation overhead

Data quality Timeliness

Manual Collation

Reliability

Continuous improvement culture

Trust in data

THE SOLUTION A DATA QUALITY FIREWALL


PROPOSED SOLUTION

Introduction of a Data Quality Firewall into Enterprise Data Warehouse to provide proactive detection and alarming of data quality issues from receipt of data from source systems to presentation in the BI and Analytics layer

ANTICIPATED RESULT

Improve the communication of data health to all EDW users:   Provide a business centric view   Provide an IT operational centric view

Accurate Complete Timely

Trusted

Relevant Understood Engineered

Key behavioural elements valued by

users & considered the ‘tipping point’ for

EDW adoption & usage

FIREWALL MEASURES

Systematic measure based data analysis

By design, not accident, the data is structured

LEVELS OF MATURITY

ENHANCE THROUGH CONTINUOUS IMPROVEMENT

PROFILE, MEASURE & MONITOR TO ENABLE YOU TO MANAGE YOUR DATA

NO VISIBILITY OF DATA LINEAGE OR QUALITY

DATA MANAGEMENT - ALARM, FIX, ENRICH, SUSPEND OR BLOCK DATA

DATA QUALITY FIREWALL FRAMEWORK OVERVIEW


You Can't Manage What You Don't Measure

INITIAL DIMENSIONS OF DATA QUALITY


Correct references to related entities (Referential Integrity, Entity Integrity)

Entities exist only once within a data set

Conformance to business rules for the entity (excluding Referential Integrity)

Data is not missing and is of sufficient breadth and depth for its specified use

Time elapsed since real world entity was recorded or business event occurred

Data is sufficiently up-to-date for the task at hand

INTEGRITY Accurate

UNIQUENESS Accurate

VALIDITY Accurate

COMPLETENESS

Complete

CURRENCY Timely

TIMELINESS Timely

INITIAL DATA QUALITY MEASURE MATRIX


TIER 0 SOURCE TO STAGING

TIER 1 STAGING TABLES

TIER 2 STAGING TO ADS

TIER 3 ADS TABLES

TIER 4 ACCESS LAYER

INTEGRITY N/A N/A

UNIQUENESS N/A

VALIDITY N/A N/A

COMPLETENESS N/A

CURRENCY N/A N/A

TIMELINESS N/A N/A N/A

HOW IT WORKS SIMPLE VERSION


Outputs

DQ Rules Engine Items To Be Tested

EDW

Schedule

DATA QUALITY FIREWALL PROJECT APPROACH


Framework Integration into SDLC

Tool Selection & Installation Dashboard Retrofit

COMPLETED Sept 2010

COMPLETED Nov 2010

COMPLETED Jan 2011

COMPLETED Jan 2012 IN PROGRESS

The framework explains the firewall concept and purpose. It outlines the high level DQ measures & control points (Tiers) that will be implemented. Framework complete, business case approved & socialised.

Input DQ controls into the Software Development Lifecycle to address new initiatives / new data sources i.e. •  Data Profiling •  Batch Load Patterns •  DQ Firewall Measures •  Testing, etc

1.  Ascertained options from the Gartner Magic Quadrant for Data Quality Tools

2.  Approached top 4 vendors to respond informally to our problem statement & DQ Firewall Framework

3.  Completed tool selection process

4.  Worked through procurement process

5.  SAS Dataflux software installed

1.  SAS Dataflux training held in Jan 2011

2.  Working with Teradata / SAS to deliver foundation build (Feb–Mar 2011)

3.  Deliver the 1st EDW Currency Dashboard in May 2011

4.  Deliver Tiers 0 – 4 by Jan 2012

1.  Construct DQ Tier Control measures for all data within the EDW

2.  Create alarms and automated resolution workflow

3.  Understand current pervasive DQ issues and build rules to ensure that the issue is proactively identified

DATA MANAGEMENT A HOLISTIC APPROACH


The Data Quality Firewall won’t deliver trust in isolation

THANK YOU FOR YOUR ATTENTION



Sales Force Automation

Database Marketing

IT-driven projects

Duplicated, inconsistent data

Inability to adapt to business change

Data Warehouse

ERP

CRM

LOB influences IT projects

Little cross-functional

collaboration High cost to maintain multiple applications

Proactive monitoring of data quality

Enterprise view of certain domains

Data is an asset

Master Data for Customer,

Product, Materials, Employees, Assets

Business requirements drive IT projects

Personalised customer

relationships

Repeatable, automated business processes

Business Process Automation

The Data Governance Maturity Model

25% 57% 13% 5%


The Opportunity Benefits Span the Enterprise

Financial Risk Productivity Compliance


Principles for Success

•  Understand where you are today

•  Foundation in data quality & governance •  Leverage proven methodology and framework

•  Focus on the business value and outcome

Trusted Data Helps Make Better Decisions

Accurate Decision Making Requires

Trusted Data

Trusted Data needs End-to-End Governance


In Closing

•  Copies of presentation at booth

•  First 20 to the SAS booth will gets copies of The Data Asset book

•  Rick and myself will be available in the next break to answer any questions you may have