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BI the Agile Way


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Business Intelligence in Agile Development framework

Published in: Technology, Business

BI the Agile Way

  1. 1. Doing BI the Agile Way Rajesh Nadipalli Rev 3 Jan 2012
  2. 2. Presentation ObjectiveTraditional BI practices are generally slow in realization or change. Typical IT projects take over 4 months before the business gets value and change management is not quick either.Using my personal experiences, I am laying out a simple blue print for BI practice that is really Agile – both from technology and business.
  3. 3. What’s in the Presentation Recommendations for…  High Level Process Flow  Executive Sponsorship  Business Architecture  Initial Analysis  Agile Requirements  Maturity  TechnologyArchitecture  Platform Selection  Agile Development
  4. 4. High Level Process Flow Business Sprint Development Requirements (high level) Sprint 2 ValidateExecutive Business & Plan Initial Sprint Sprint Release 1 3Sponsorship Technology proposals (theme based) Sprint 4 Technology Platform (components) Update Release Backlog and work on next theme (Release) For Agile Process Overview, see these slides:
  5. 5. Executive Sponsorship In current landscape where companies are faced with data growth year-over-year is over 20%. Getting the right data into the hands of the right people in time is a challenge which is the BI promise. However, to run a successful BI practice, you need to ensure the management is on board with this strategy. It is also important that communications with sponsors is consistent and timely.
  6. 6. BusinessArchitecture
  7. 7. Business Architecture – Initial Analysis A good start from the Business side is to.. • Understand current landscape • Whatmetrics are used today • Who uses them, are they stewards for this data • How do they co-relate data across different systems • Understand the pain points • Who (roles) lacks information today • What is loss of productivity due to incorrect or delayed information • Are there multiple definitions for the same metrics • Is there a common set of governed hierarchies? • Build an ROI analysis to justify the program
  8. 8. Business Requirements (high level)Let’s take an example: You are planning to start a Portfolio Management Dashboard• Plan the Categories of Metrics • Program Health • Resource Health • Financial Health• Define Roles of users who will use your dashboard • Program Manager • Vice President • Financial Analyst• Define Data Sources • PPM system • HR system • Financial system • Budget system
  9. 9. Business Requirement Details(Single Release)• Define Hierarchies • Fiscal Calendar (Quarters, Months as it relates to your Organization) • Business Reporting (Business Unit -> VP -> Manager -> Employee) • Identify which hierarchies have good sources and which need management• Define Metrics Definition • Program Manager • Vice President • Financial Analyst• Define Data Sources • PPM system • HR system • Financial system • Budget system
  10. 10. From Metric Definition to Effectiveness Define Use Predict Effectiveness Metric has Automate Detect Name analytical collection Patterns value Metric has Description Scorecard Intelligence predictive value Business Prevent Metric has a Dashboards owner issues ROI Alerts / Formula Notifications System of Decision record making Hierarchy Maturity Model
  11. 11. TechnologyArchitecture
  12. 12. Technology Platform Selection Dashboards, DAAS Typical User needs - Operational Dashboards for canned reports, Ad-hoc query interface, data as a service Dashboards Ad-hoc DAAS Operational & Metric Data Store Operational Data Store like HDFS to host copy of all known source data; Metrics Cache would be a smaller set of computed data; MDM is governed master data Operational DS Metrics Cache MDM Data Processing Layer ETL should be easy to extend, support multi user development and connect to various sources and targets. Example Map ETL Monitoring Reduce, Pentaho ETL, Talend Source of Records Plan for databases, files, web services, internal and external SAAS providers Databases Cloud Files
  13. 13. adapted from ForresterTechnology Stack by User Functionality Advance Visualization Reporting Alerts DashboardPresentation Disconnected Usage Mobile Office Tools Ad-hoc Analytics Integration Metrics/KPIs Scorecards PlanningPerformanceManagement Performance Management Strategy and Objective Collaboration ECM Portals eLearningSupportingApplications Knowledge Management MDM Metadata Repositories Life-cycle Mgmt. Data/text/Video Mining Guided Analytics Natural Language ProcessingAnalytics OLAP Operational DSS Predictive Analytics Behavioral Targeting Web Analytics Self-Service Analytics Data Quality Report Mining Service Discovery AcceleratorsDiscovery & RegistryIntegration EAI / SOA DB Accelerators BAM/CEP BPEL/BPM/BRE ODS, DW, Data Marts EII (Enterprise Information ETL Unstructured and Web Integration) Data Integration Columnar DBMS Hierarchical/XML In-Memory AppliancesData Multidimensional OLAP Multivalve DBMS RDBMS Streaming DBMS Search Indexes Data CacheInfrastructure Network Servers Storage Cloud
  14. 14. Source: OracleCapability Maturity for a Practice
  15. 15. Sprint Development• Connect the dots with sample data • To ensure the ETL, Data and Report developers are in-sync, first create some sample data • Discuss the data flow and expected results at each step • Estimate task effort for each user story• Build Data Model & Map Reduce specifications • Create a data model • Create stubs for map reduce jobs• Parallel Development • ETL developer can work towards details of the job • Report developer can work towards the user interface• Integration • Keep sufficient time for integration and resolve issues as a team
  16. 16. Thank You