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Improving Insight and Decision Making Using Microsoft Business Intelligence and SQL Server 2008 Rafal Lukawiecki Strategic Consultant, Project Botticelli.

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Presentation on theme: "Improving Insight and Decision Making Using Microsoft Business Intelligence and SQL Server 2008 Rafal Lukawiecki Strategic Consultant, Project Botticelli."— Presentation transcript:

1 Improving Insight and Decision Making Using Microsoft Business Intelligence and SQL Server 2008 Rafal Lukawiecki Strategic Consultant, Project Botticelli Ltd rafal@projectbotticelli.com

2 2 Objectives Overview BI and PM Technology Platform Introduce fundamental 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 © 2009 Project Botticelli Ltd & entire material © 2009 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 Marin Bezic, Kathy Sabourin, Aydin Gencler, Bryan Bredehoeft, and Chris Dial for all the support. Thank you to Maciej Pilecki for assistance with demos.

3 3 Overview of BI and PM

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 What is Performance Management? Processes, methodologies, and technologies used by enterprises to monitor, analyze, and plan business performance.

6 6 BI in an Enterprise

7 7 “Companies in the top quartile in terms of their BPM practices … generate 2.4 times the three-year total shareholder return of the typical company in their industry” Hackett Group, reported in Business Performance Management Magazine, February 2007 BI and PM - Opinions “Business Intelligence (BI) is the #1 technology priority for CIO’s to deliver on in 2009.” Gartner EXP Worldwide Survey, January, 2009 50% of large companies “believe that a gap exists between their company's ability to formulate and communicate sound strategies and its success at implementing them.” OnPoint Consulting, reported in Business Finance Magazine, November 2006

8 8 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

9 9 Three Contexts of BI Use Personal BI Built by me, for me, used only by me Team BI Built by someone on the team, for the team’s use Organizational BI Built and maintained by IT, for use across company 11 22 33

10 10 Technology Platform

11 11 Integrated BI Platform

12 12 The Microsoft BI Platform Integrate Store ReportAnalyze

13 13 Fundamental Concepts

14 14 BI & PM in an Enterprise Data Sources Staging Area Manual Cleansing Data Marts Data Warehouse Client Access 1: Clients need access to data 2: Clients may access data sources directly 3: Data sources can be mirrored/replicated to reduce contention 4: The data warehouse manages data for analyzing and reporting 5: Data warehouse is periodically populated from data sources 6: Staging areas may simplify the data warehouse population 7: Manual cleansing may be required to cleanse dirty data 8: Clients use various tools to query the data warehouse 9: Delivering BI enables a process of continuous business improvement

15 15 Silos of Data Data Warehouse Call Center Web Apps Inventory ERPHR Finance CRM

16 16 Source Systems Process real-time transactions Contain data structures optimized for modifications Normalized schema Usually provide limited decision support Are commonly referred to as: Online transaction processing (OLTP) systems Operational systems HR Finance Inventory

17 17 Data Warehouse Characteristics Provides data for business analysis processes Grouped in subject-specific stores called Data Marts Optimized for rapid ad hoc information retrieval Integrates data from heterogeneous source systems Provides a consistent historical data store

18 18 ETL: Extract, Transform, and Load 1.Extract data from the source systems 2.Transform the data to convert it to a desired state 3.Load the data into the data warehouse ETL

19 19 Data Integration More than Just ETL Transform corporate data into meaningful and actionable information Challenges Retrieve and merge data from multiple sources Cleanse and transform the data Load the data into appropriate data stores for analysis and reporting Enterprises spend 60%–80% of their BI resources in the data integration stage

20 20 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 16 Bamborginis sold to John on 20090115.

21 21 Dimensions Describe business entities Contain attributes that provide context to numeric data Present data organized into hierarchies

22 22 Predictive Analysis PresentationExplorationDiscovery Passive Interactive Proactive Role of Software Business Insight Canned reporting Ad-hoc reporting OLAP Data mining Predictive Analysis

23 23 Data Mining Discovery of (very) hidden patterns in mountains of data Correlation search engine Recent combination of statistics, probability analysis, database technologies, machine learning, and AI

24 24 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

25 25 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

26 26 Querying a Simple Cube 5,005,000 What sales did we expect to achieve in North America for CY 2004 Q1?

27 27 Key Performance Indicator (KPI) Quantifiable measurement comparing business performance to goals Measure of overall organizational health when combined into a collection for a business scorecard Three main ways to build KPIs: Using OLAP (cubes) Directly in PerformancePoint Server Using data mining (predictive KPI)

28 28 KPI Characteristics Value Goal Status Trend

29 29 Dashboards and Scorecards Scorecard Table (pivot-like) of KPIs Dashboard Contains scorecards, reports, and other analytical visualisations

30 30 Conclusions

31 31

32 ”Our strategic Performance Management program will enable us to better drive business performance and provide an organisational context for Business Intelligence” Ran Segoli, IT Program Manager, Falck Healthcare - Need for Performance management and organizational context for BI - Data driven management, decision making - System (holistic) view, avoiding tunnel view - Rapidly changing business needs - The solution for the ”Occupatnional Health” service line was in only 3 ½ months - Over the coming period the outstanding services lines and geographies will follow - Microsofts BI Platform Suite: SQL Server, Excel, Sharepoint and Performance Point Server -Automate KPI data to online performance management - One version on business performance -Data warehouse for automating reporting - Data for analysis via excel - Highlight on data quality issues -Catalyst for further developing the enterprise domain model

33 BI Portal – Monitoring and Analysis

34 BI Portal – Scorecards

35 BI Portal – Customers

36 36 Microsoft BI and PM Solutions At: www.microsoft.com/casestudies

37 37 Summary Business Intelligence and Performance Management are the top IT priorities for businesses Data warehousing, analytics, presentation, and interactive use Rich conceptual design that makes quick and easy self- service BI applications possible

38 38 © 2009 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 © 2009 Project Botticelli Ltd & entire material © 2009 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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