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End User Applications

End User Applications. What to build. Metadata Management. Enterprise Reporting. Data Extraction Data Cleansing Data Integration Data Improvement. External Data. Datamarts. OLAP Query. Data Mining. Data Transformation. Operational Data Store. Data Warehouse. Source

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End User Applications

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  1. End User Applications What to build

  2. Metadata Management Enterprise Reporting Data Extraction Data Cleansing Data Integration Data Improvement External Data Datamarts OLAP Query Data Mining Data Transformation Operational Data Store Data Warehouse Source Systems Information Delivery Project Management & Quality Assurance Operations & Systems Management Framework Architecture (Kerr McGee)

  3. The Role of End User Applications Desktop tools / do-it-yourself queries Ad hoc power user End user applications Push-button knowledge worker Standard report customer Operational reporting environment

  4. Application Template • Provides the layout and structure of a report that is driven by parameters • Users set parameters from pick lists or drop down menus

  5. Cognos PowerPlay – web reports/slicing and dicing/data analysis, based on cubes.

  6. Template Design Steps • Identify an initial template set. 10 – 20 high value templates. • Collect report candidates. What are the important report requests? • Consolidate report categories. Based on data needs and type of report. • Prioritize the list.

  7. Common Report Types • How’s business? • What are the trends? • What’s unusual? • What is driving those exceptions? • What if …? • Make a business decision. • Implement the decision.

  8. Note • Do not recreate the past. • Old reports often do not reconcile • Recreating old reports gains little

  9. Template Management • Navigation. How do you find the one you want? • Shop standards. • Naming standards for templates and columns • Look and feel • Template creation • Definition and layout • Match with dimensional model • Review with users

  10. Application Development • Environments • Web based • Direct template access • Structured/menu based template access • Custom coded

  11. Data Requirements It is hard to evaluate forms and templates without meaningful data. Problems to manage include: • Meaningless descriptions • Duplicate dimensions or dimension access keys • Incorrect dimensional relationships • Data not matching legacy reports. May be a legacy problem.

  12. Managing the process • Remember the milestones • First demo 25% • System test with all modules 25% • Validated in simulated production 25% • Documented and delivered final system 25%

  13. Managing (cont.) • Code is not self-documenting • Use a bug reporting database or log • Acknowledge bug reports from users and testers • Place a high premium on testing and repairing

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