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1 1 The Big Picture of Business Intelligence: Goals, Concepts, and the Platform Rafal Lukawiecki Strategic Consultant, Project Botticelli Ltd

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Presentation on theme: "1 1 The Big Picture of Business Intelligence: Goals, Concepts, and the Platform Rafal Lukawiecki Strategic Consultant, Project Botticelli Ltd"— Presentation transcript:

1 1 1 The Big Picture of Business Intelligence: Goals, Concepts, and the Platform Rafal Lukawiecki Strategic Consultant, Project Botticelli Ltd

2 2 2 Objectives Overview state of Business Intelligence in 2010 Discuss the technology platform Optionally, introduce BI concepts The information herein is for informational purposes only and represents the opinions and views of Project Botticelli and/or Rafal Lukawiecki. 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. Portions © 2010 Project Botticelli Ltd & entire material © 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 Project Botticelli Ltd as of the date of this presentation. Because Project Botticelli & Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft and Project Botticelli cannot guarantee the accuracy of any information provided after the date of this presentation. Project Botticelli makes no warranties, express, implied or statutory, as to the information in this presentation. E&OE. This seminar is based on a number of sources including a few dozen of Microsoft-owned presentations, used with permission. Thank you to Chris Dial, Tara Seppa, Aydin Gencler, Ivan Kosyakov, Bryan Bredehoeft, Marin Bezic, and Donald Farmer with his entire team for all the support.

3 3 Overview of BI and PM

4 4 4 Business Intelligence BI - Improving Business Insight “A broad category of applications and technologies for gathering, storing, analyzing, sharing and providing access to data to help enterprise users make better business decisions.” – Gartner

5 5 1. BI and Power of Visualisation 2. Balanced Scorecards

6 6 6 Business Intelligence Today Low end-user adoption rates and high reliance on IT Analyst Issues: Hard to access organizational data Reliant on IT for reporting Difficult to share insight IT Pro Issues: No time for ad-hoc BI requests Lack of control Organizational BI often expensive

7 7 7 From Organizational BI to Personal BI Enabling managed self-service BI IT Unmanaged IT Managed IT Involvement 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

8 8 8 Microsoft BI Strategy Democratizing Business Intelligence Familiar environment Integrated into Microsoft Office Built on SQL Server Improving organizations by providing business insights to all employees leading to better, faster, more relevant decisions

9 9 9 FY1FY2FY3FY4FY5

10 10 FY1FY2FY3FY4FY5

11 11 FY1FY2FY3FY4FY5 Classic Business Intelligence

12 12 FY1FY2FY3FY4FY5 Self-Service Business Intelligence Classic Business Intelligence

13 13 Microsoft Business Intelligence Shared Personal Scope Organic Intentional DevelopmentSelf-Service Performance Management Easy discovery of data Simple, intuitive tools Ad-hoc Creative and agile Consistent corporate definitions, KPIs Corporate policies and processes Contextual and accountable Empowered Aligned Personal BI Team BI Organizational BI

14 14 Three Contexts of BI Use Personal BI Built by me, for me, used only by me Team BI Built by someone on the team, shared inside a team Organizational BI Built and maintained by IT, for use across company

15 15 Technology Platform

16 16 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 visualization Contextual visualization Business Collaboration Platform Data Infrastructure & BI Platform

17 17 Big Picture: Managing Information Data Warehouse Analysis ServicesMaster Data Services ERP CRM HRMS BI Developer or Analyst Integration Services

18 18 Big Picture: Dashboards, Scorecards Knowledge Worker Cubes, Warehouse Analysis Services

19 19 Big Picture: Reporting End User Cubes, Warehouse Analysis ServicesReporting Services

20 20 PowerPivot for Excel PowerPivot for SharePoint Analysis Services Big Picture: BI Analyst, Power User

21 21 Fundamental Concepts

22 22 Enterprise Data

23 23 Silo Integration Challenge Data Warehouse Call Center Web Apps Inventory ERPHR Finance CRM SOA – Enterprise Service Bus

24 24 Source Systems Process real-time transactions Optimized for data modifications Normalized Limited decision support Commonly called: Online transaction processing (OLTP) systems Operational systems HR Finance Inventory

25 25 Data Warehouse Provides data for business analysis Grouped in subject-specific stores called Data Marts Optimized for rapid ad-hoc information retrieval Integrates heterogeneous source systems Consistent historical data store

26 26 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

27 27 Dimensions and Facts Basis of All BI 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

28 28 Dimensions Describe business entities Contain attributes that provide context to numerical data Present data organised into hierarchies

29 29 Predictive Analysis PresentationExplorationDiscovery Passive Interactive Proactive Role of Software Business Insight Canned reporting Ad-hoc reporting OLAP Data mining Predictive Analysis Self-service Analysis

30 30 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

31 31 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

32 Q1 Jan Feb Mar Accessories Parts Cars Measures Items Sold Cost Sales $ Dates Products Ритейл Cube

33 33 Dicing a Cube Ритейл 2009 Q1 Jan Feb Mar Accessories Parts Cars Measures Items Sold Cost Sales $ Dates Products

34 34 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”

35 35 Data Mining Discovery of (very) hidden patterns in mountains of data Correlation search engine Combination of statistics, probability analysis, database technologies, machine learning, and AI

36 36 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)

37 37 KPI Characteristics Value Goal Status Trend

38 38 Dashboards and Scorecards 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

39 39 Conclusions

40 40 Microsoft BI and PM Solutions At:

41 41 Summary Business Intelligence is a top IT priority for businesses Self-service analytics are quickly becoming crucial tools enhancing employees’ performance Good data warehouse design, master data management, data integration, and multidimensional design enable rich BI

42 42 © 2010 Microsoft Corporation & Project Botticelli Ltd. All rights reserved. The information herein is for informational purposes only and represents the opinions and views of Project Botticelli and/or Rafal Lukawiecki. 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. Portions © 2010 Project Botticelli Ltd & entire material © 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 Project Botticelli Ltd as of the date of this presentation. Because Project Botticelli & Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft and Project Botticelli cannot guarantee the accuracy of any information provided after the date of this presentation. Project Botticelli makes no warranties, express, implied or statutory, as to the information in this presentation. E&OE.


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