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Selecting BI Tool - Proof of Concept - Андрій Музичук
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Selecting BI Tool - Proof of Concept - Андрій Музичук

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A large number of tools and techniques have been developed over the years to support managerial decision making. Thus process of selecting appropriate BI tool turns to be an issue. Implementing and …

A large number of tools and techniques have been developed over the years to support managerial decision making. Thus process of selecting appropriate BI tool turns to be an issue. Implementing and deploying a BI initiative can be lengthy, expensive and failure pron. The Proof of concept method can be used by stakeholders to avoid unnecessary losses.

In the presentation, the description of Proof of Concept method is provided based on the example of selecting among Microsoft stack, MicroStrategy and Business Object Bi tools. The example includes above mentioned technologies overview, reports modeling process, reports development process, report integration in SharePoint, performance testing as well as the decision making model and summary for final tools selection.

Published in: Education, Technology, Business

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  • 1. Selecting BI Tools: Proof Of Concept presenter: Andriy Muzychuk Product manager at Malkos, PhD.
  • 2. Agenda• Introduction• Business Intelligence (BI) overview Definition, history, BI today BI components• Business Performance Management (BPM)and BI• BI solution phases• Proof of Concept (POC) for selecting BI tool• Example
  • 3. IntroductionChanging business environment and computerized support Business Decisions Organization Environment and Responses Factors Supports Strategy AnalyzeGlobalization Partners’ collaboration PredictionsCustomer Demand Opportunities Real-time response DecisionsGovernment regulation Pressure / AgilityMarket Conditions Increased productivity IntegratedCompetitions computerized DS New vendors... New business models BI ...
  • 4. BI Definition and ObjectivesBusiness Intelligence (BI) is an umbrella term thatcombine architecture, tools, databases, analyticaltools, application, and methodologiesBI main objectivesq To enable interactive access to dataq To enable manipulation of dataq To give ability to conduct appropriate analysis
  • 5. BI History 1970s Early 1980s Mid 1990s 2005s Management Executive Information Information BI BI Systems SystemsMIS capabilities EIS capabilities BI capabilities BI capabilities | Ad hoc reporting| Static two dimensional | Forecasting and | EIS capabilities reports prediction | EIS capabilities + | Artificial capabilities| No analytic | Trend Analysis | Power analytic capabilities | Drill down to details “A broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise user to make better decisions” - Gartner, 1990
  • 6. BI Today Querying and ETL reporting Metadata DW DSS Financial Reporting Datamarts Spreadsheet OLAP (MS Excel) Dashboards and Scorecards BI Workflow Alerts and Portals notification Data and text Predictive mining Analysis
  • 7. Performance ManagementCorporate Performance Management - Gartner Group(CPM)Enterprise Performance Management - Oracle(EPM)Strategic Enterprise Management (SEM) - SAPBusiness Performance Management (BPM) - BPM Standards BPM refers to the business processes, methodologies, Group metrics, and technologies used by enterprises to measure, monitoring, and manage business performance - BPM Standards Group BPM= BI + “Planning” - Calumo Group
  • 8. BI Technology mappingScope BPM Consistent corporate BPM definition of metrics, shared Organization BI measures, KPI Corporate policies and processes Team BI Self Service personal Self Service Easy discovery of data Personal BI Simple intuitive tools Developement Ad hoc organic International
  • 9. A High-Level Architecture of BI DW BA Performance Environment Environment and Strategy DataSources Build the DW Business Users Managers / Executives Organizing Access DW Summarizing Manipulate, BPM Strategies Standardizing results User Interface Browser Portal Dashboard
  • 10. Business Analysis Types Predictive analysisproactive Data mining OLAPinteractive ad hoc passive reporting presentation exploration discovery
  • 11. BI Solution Implementation Phases Phase 1 Phase 2 Phase 3∴ Define KPI∴ Decide level of BI ∴ Collect requirements > Reports ∴ Implementation ∴ Conduct POC > Dashboards > Analysis > AnalyticsPOC Implementation Phases Planning Implementation Testing Finalazing Decision Tuning Decision Model
  • 12. POC Phases DescriptionProof Of Concept PhasesPlanning Implementation Testing Finalizing Environment consideration Criteria selection Environment setting Finalizing documents Test work frame creation BI Vendor selection Prototype development Recommendations Prototype Testing Prototype planning BI Tools best practices Evaluation bottlenecks Performance testing result - Reports objectives Prototype requirements Requirements mapping documenting - Reports specifications mapping Summary report Deliverables planning Summary Analysis Report Prototype model implementation process description Optimization capabilities BI Tools comparison Test results
  • 13. Tools comparison: Forester Research Inc.
  • 14. Tools comparison: Gartner Group
  • 15. Example: MicroStrategy dashboard
  • 16. Example: PerformancePoint dashboard
  • 17. Example: Business Objects dashboard
  • 18. Example: POC Summary Report Categories Performance MicroStrategy BusinessObjects PointServices Prototype Implementation • Time Outlay • Design • Bottlenecks Integrationwith SharePoint 2010 Toolscapabilities: • Functional • Optimization T performance est • Load Time • Drill Down Tollcost
  • 19. POC Summary• Ability to test the solution in existing IT environment• Increases the developers’ understanding of the requirements before starting the real system implementation• Allows checking the design of all possible preselected tools• Allows testing the capability of the potential solution provider: functionality, connectivity, usability and performance of each BI tool• Requirements can be tested and challenged
  • 20. Thanks for attention!
  • 21. Reference1) Rita L. Sallam, James Richardson, John Hagerty, Bill Hostmann.Magic Quadrant for Business Intelligence Platforms // Gartner RASCore Research Note G00210036 , 27 January 2011 (http://www.gartner.com/technology/media-products/reprints/tableau/vol2/ar)2) Boris Evelson. The Forrester Wave™: Enterprise BusinessIntelligence Platforms, Q4 2010(http://www.microsoft.com/presspass/presskits/bi/docs/EnterpriseBIPlatforms)3) Efraim Turban, Ramesh Sharda, Dursun Delen, David King,Janine E. Aronson. Business Intelligence. A managerialApproach. – 2nd ed. - 2011

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