the big picture of business intelligence
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The Big Picture of Business IntelligenceTRANSCRIPT
From the Excel you know to the
Excel you don’t! Microsoft Business Intelligence Discovery Session
Amber McCormack Marketing Executive
Welcome
We appreciate your feedback
Welcome
From the Excel you know to the
Excel you don’t! Microsoft Business Intelligence Discovery Session
[email protected] [email protected]
Ian Macdonald & Jes Kirkup BI Practice Lead Senior BI Consultant
The Day
• 09.30 - Business Intelligence Overview – The big picture
• 10.15 - The Knowledge Workers Perspective – Fact based decision making
• 11.00 - Break
• 11.20 - IT and Data Management – Making sure it is right
• 12.00 - The Analyst – Deep dive discovery
• 12.45 – Summary and Next Steps
Content and Code
10 years building information solutions for clients
Best in the world twice and top UK partner
Me & Jes
25 + 10 years designing, developing, managing and marketing Business Intelligence technologies and solutions
Leading process oriented BI at Content and Code
Content and Code and me Why are we here?
Setting the Scene
• Your name
• Your role
• Your business pain
• What you need to help you overcome that pain
• What does “Business Intelligence” mean to you?
A Question:
• Who here is comfortable with the concepts of: – Data Warehouse and Data Marts
– Master Data Management
– ETL
– Dimensions and Facts
– OLAP, Cubes and UDM
– Data Mining
– KPIs
– Scorecards and Dashboards
• ?
The Big Picture of Business
Intelligence Goals, Concepts, and the Platform
Business Intelligence BI - Improving Business Insight
“A broad category of applications and technologies for gathering, storing, analysing, sharing and providing access to data to help enterprise users make better business decisions.” Gartner Group
demos 1. Business Intelligence and Power of Visualisation
Balanced Scorecards
Objective:
Performance at a glance
Complex information made easy to understand
demos What did we see?
Visualisations making information come alive
Easy to use, intuitive, relevant metrics across my business view
As much or little detail as needed
• Analyst Issues:
– Hard to access organisational data
– Reliant on IT for reporting
– Difficult to share insight
• IT Pro Issues:
– No time for ad-hoc BI requests
– Lack of control
– Organisational BI often expensive
Business Intelligence Today Low end-user adoption rates and high reliance on IT
From Organisational BI to Personal BI Enabling managed self-service BI
IT
Unm
anaged
IT
Managed
IT Involv
em
ent
Self Service
Easy to use
On and Offline
Collaborative
Empowered, Managed, Accurate
Accurate
Secure
Scalable
Up to date
Rogue “Spreadmarts”
Data Sources
Data Marts
BI and LOB Apps
Portals and Dashboards
Corporate BI
User Context
Empowered Reliant on IT
Microsoft BI Strategy Democratising Business Intelligence
• Familiar environment
• Integrated into Microsoft Office
• Built on SQL Server
Improving organisations by providing business insights to all employees leading to better, faster, more relevant decisions
Complementary BI Contexts
Personal BI Self-Service Ad-hoc Analysis
Team BI Shared, Collaborative Insight
Organisational BI
Pre-designed, aligned, approved
Business User Experience
Microsoft Business Intelligence You may already have these products
Data Infrastructure and BI Platform Analysis Services
Reporting Services
Integration Services
Master Data Services
Data Mining
Data Warehousing
Integrated Content and Collaboration Thin client experience
Dashboards & Scorecards
Search
Content Management
Compositions
Familiar User Experience Self-Service access & insight
Data exploration & analysis
Predictive analysis
Data visualisation
Contextual visualisation Business Collaboration Platform
Data Infrastructure & BI Platform
Personal BI PowerPivot for Excel 2010
Team BI PowerPivot for SharePoint 2010
& PerformancePoint Services
Organisational BI
SQL Server 2008 R2
Complementary BI Technologies
Fundamental Concepts
Enterprise Data
Silo Integration Challenge
Data Warehouse
Call Center
Web Apps
Inventory
ERP HR
Finance
CRM
SOA – Enterprise Service Bus
• Process real-time transactions
• Optimised for data modifications
– Normalised
• Limited decision support
• Commonly called:
– Online transaction processing (OLTP) systems
– Operational systems
Source Systems
HR Finance Inventory
• Provides data for business analysis
– Grouped in subject-specific stores called Data Marts
• Optimised for rapid ad-hoc information retrieval
• Integrates heterogeneous source systems
• Consistent historical data store
Data Warehouse
ETL: Extract, Transform, and Load
1. Extract data from the source systems
2. Transform data into desired form
3. Load data into the warehouse
ETL
• Fact – something that happened
– Sale, purchase, shipping...
– Transaction or an event
– Verb
– Essentially a Measure
• Dimension – describes a fact
– Customer, product, account...
– Object
– Noun
• A fact (measure) is expressed in terms of dimensions
– 42 footballs sold to John on 20100115.
Dimensions and Facts Basis of All BI
Dimensions
• Describe business entities
• Contain attributes that provide context to numerical data
• Present data organised into hierarchies
Predictive Analysis
Presentation Exploration Discovery
Passive
Interactive
Proactive
Role of Software
Business Insight
Canned reporting
Ad-hoc reporting
OLAP
Data mining
Predictive Analysis
Self-service Analysis
OLAP or Multidimensional Data
• Online Analytical Processing = Multidimensional Data
• Measures and Dimensions
• Uses a calculation engine for fast, flexible transformation of base data (such as aggregates)
• Supports discovery of business trends and statistics not directly visible in data warehouse queries
Cube (UDM) Unified Dimensional Model
• Combination of measures (from facts) and dimensions as one conceptual model
• Rich data model enhanced by – Calculations
– Key Performance Indicators (KPIs)
– Actions
– Perspectives
– Translations
– Partitions
• Formally, cube is called a UDM
Cube
2009
Q1
Jan
Feb
Mar
Accessories Parts
Cars
Measures
Dates
Products
Ритейл
Dicing a Cube
1
3
2
6
25
Ритейл
2009
Q1
Jan
Feb
Mar
Accessories Parts
Cars
Measures
Dates
Products
Ad-hoc Self-Service Analysis
• Interactive, pivot-based analysis of column-oriented large volumes of data (>>millions of rows)
• Pivots, advanced filtering (slicers), and tabular expressions
+
• OLAP-style analytics
– Almost multidimensional
– “Cubes without a cube in Excel”
• Discovery of (very) hidden patterns in mountains of data
• Correlation search engine
• Combination of statistics, probability analysis, database technologies, machine learning, and AI
Data Mining
Key Performance Indicator (KPI)
• Measurement comparing performance to goals
• Grouped into a business scorecard to show company health
– Ideally, with a balanced perspective onto groups of KPIs
• Built with:
– Using OLAP (enterprise-level KPIs)
– In SharePoint Server PerformancePoint Services (often team KPIs)
– Using data mining (predictive KPI)
KPI Characteristics
• Value
• Goal
• Status
• Trend
• Scorecard
– Table (pivot-like) of KPIs
• Dashboard
– Contains scorecards, analytical reports, and other analytical visualisations
• Create them:
– DIY: PowerPivot
– Quickly: SharePoint 2010 PerformancePoint Services
– Bespoke: custom SharePoint, Silverlight, and .NET development
Dashboards and Scorecards
Conclusions
© 2010 Microsoft Corporation & Content and Code Ltd. All rights reserved. The information herein is for informational purposes only and represents the opinions and views of Content and Code. The material presented is not certain and may vary based on several factors. Microsoft makes no warranties, express, implied or statutory, as to the information in this presentation. © 2010 Microsoft Corp. Some slides contain quotations from copyrighted materials by other authors, as individually attributed or as already covered by Microsoft Copyright ownerships. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Content and Code as of the date of this presentation. Because Content and Code & Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft and Content and Code cannot guarantee the accuracy of any information provided after the date of this presentation. Content and Code no warranties, express, implied or statutory, as to the information in this presentation. E&OE.