Driving Implementation Through a Methodology

1. Driving Implementation Through a Methodology Chapter 4

2. “Big Bang” Approach Analyze enterprise requirements Build enterprise data warehouse Report in subsets or store in data marts

3. “Big Bang” Approach:Advantages and Disadvantages • Advantages: - The only real advantage is where the warehouse is being built as part of another major project or program such as reengineering and they are dependent on each other - Having a “big picture” of the data warehouse before starting the data warehousing project • Disadvantages: - Involves a high risk, takes a longer time - Runs the risk of needing to change requirements

4. Incremental Approach to Warehouse Development Strategy • Multiple iterations • Shorter implementations • Validation of each phase Definition Analysis Design Build Strategy Strategy Production Definition Definition Analysis Analysis Design Design Build Build Production Production

5. Benefits of an Incremental Approach • Delivers a strategic data warehouse solution through incremental development efforts • Provides extensible, scalable architecture • Supports the information needs of the enterprise organization • Quickly provides business benefits and ensures a much earlier return of investment • Allows a data warehouse to be built based on a subject or application area at a time • Allows the construction of integrated data mart environment

6. Top-Down Approach Data warehouse Data marts Users Sales Legacy data Marketing Operational data External data source

7. Top-Down Approach:Advantages and Disadvantages • Advantages: - Provides a relatively quick implementation and payback - Offers significantly lower risk - Emphasizes high-level business needs - Achieves synergy among subject areas • Disadvantages: - Requires an increase in up-front costs - Difficult to define the boundaries - May not be suitable unless the client needs cross-functional reporting

8. Bottom-Up Approach Data marts Data warehouse Sales Legacy data Operational data Marketing External data source

9. Bottom-Up Approach:Advantages and Disadvantages • Advantages: - Appealing to IT - Easier to get buy-in from IT • Disadvantages: - Requires source systems to encapsulate the current business processes - Design may be out-of-date before delivery - Requires reengineering for each increment - Solutions may be rejected by the next line of business to be involved - Overall benefit to the business may be minimized

10. Oracle Method • Consists of: - Online guidelines and manuals - Workplan templates - Deliverable templates • Created by experienced and field-based practitioner for estimated, managing, developing, and delivering business solutions.

11. Oracle Data Warehouse Method • Guides through development: - Business functions - Processes - Tasks • Modeled on the Custom Development Method

12. Method Materials • Workplan templates* • Deliverable templates* • Online handbooks • Estimating software Software Tools Handbooks • Method handbook • Process and task reference* • Deliverable reference*

13. Oracle Data Warehouse Method • Focuses on scoping • Manages risk • Relies on user involvement throughout • Delivers an extensible, scalable solution • Uses a variety of technologies • Identifies tasks with clear objectives and deliverables • Employs common techniques, skills, and dependencies • Assigns tasks to processes and processes to phases

14. Benefits Consistency Experience and best practices Flexibility Productivity Risk avoidance

15. DWM Fundamental Elements • Approaches • Phases • Processes • Tasks and deliverables • Roles Phase 1 Phase 2 Phase 3 Process 1 Process 2 Phase 1 Task1 Phase 1 Task2 Phase 1 Task3 Phase 2 Task1 Phase 2 Task2 Phase 2 Task3 Phase 3 Task1 Phase 3 Task2 Phase 3 Task3

16. Approaches Packaged data mart Increment I Proof of Concept Warehouse Business infrastructure application implementation implementation Data mart Data mart Warehouse Increment II Increment II Data mart Through N Through N

17. Incremental Approach Requirements Capture Business Strategy Warehouse Strategy Phase Scoping Services IT Strategy Technical Architecture Services Warehouse Infrastructure Services Warehouse Business Solution Services Increment 1 Increment A Proof of Concept Increment 2 Increment B Increment 3 Increment C Increment n Increment z

18. Incremental Development Strategy • Focus on business functionality • Deliver business benefit • Suited to warehouse evolution • Once an increment is complete the selection and scope of the next increment is defined • Each increment follows the same phase sequence Incremental Development PGMPJM Project and Program Management Definition ETA Enterprise Technical Architecture Analysis Design Build Transition to Prod. Discovery

19. The Strategy Phase Strategy Strategy Definition Business requirements Analysis Data acquisition Design Architecture Build Data quality Transition Administration Discovery

20. The Strategy Phase Strategy Strategy Definition Metadata Analysis Data access Design Documentation Build Testing Transition Training Discovery

21. The Definition Phase Strategy Definition Definition Business requirements Analysis Data acquisition Design Architecture Build Data quality Transition Discovery

22. The Definition Phase Strategy Definition Definition Administration Analysis Metadata management Design Data access Build Documentation Transition Training Discovery

23. The Analysis Phase Strategy Analysis Definition Business requirements Analysis Data acquisition Design Architecture Build Data quality Transition Administration Discovery

24. The Analysis Phase Strategy Analysis Definition Metadata Analysis Data access Design Documentation Build Testing Transition Training Discovery

25. The Design Phase Strategy Design Definition Data acquisition Analysis Architecture Design Data quality Build Administration Transition Metadata management Discovery

26. The Design Phase Strategy Design Data access Definition Database design & build Analysis Documentation Design Testing Build Training Transition Transition Discovery

27. The Build Phase Strategy Build Definition Data acquisition Analysis Architecture Design Data quality Build Administration Transition Metadata management Discovery

28. The Build Phase Strategy Build Data access Definition Database design & build Analysis Documentation Design Testing Build Training Transition Transition Discovery

29. Transition to Production Phase Strategy Transition to production Definition Data acquisition Analysis Testing Design Training Build Transition Transition Post-implementation support Discovery

30. Discovery Phase Strategy Definition Analysis Design Discovery Build Post-implementation support Transition Discovery

31. Processes • Cohesive set of tasks that meet objectives • Common skill set • Project deliverables Most overlap and interrelate; others are strict predecessors

32. Processes Business Requirements Definition Data Acquisition Architecture Data Quality Warehouse Administration Metadata Management Data Access Database Design and Build Documentation Testing Training Transition Post-Implementation Support

33. Business Requirements Definition • Defines requirements • Clarifies scope • Establishes implementation road map • Provides initial focus on enterprise implementation • Identifies information needs • Models the requirements

34. Data Acquisition • Identify, extract, transform, and transport source data • Consider internal and external data • Move data between sources and target • Perform gap analysis between source data and target database objects • Define first-time load and refresh strategy • Define tool requirements • Build, test, and execute data acquisition modules

35. Architecture • Specify technical foundation • Create warehouse architectural design • Integrate products of architecture components for scalability and flexibility • Determine database environment--distributed or centralized • Define development, testing, training, and production environments • Configure the platform • Perform database sizing • Consider disk striping

36. Data Quality • Ensure data consistency, reliability, accuracy • Develop a strategy for: - Cleansing - Integrity functions - Quality management procedures • Identify business rules for: - Cleansing - Error handling - Audit and control • Define data quality tool requirements • Build, test, and execute data quality modules

37. Warehouse Administration • Specify maintenance strategy for: - Configuration management - Warehouse management - Data governing • Define warehouse management workflow and tool requirements • Build, test, and execute modules • Prove data access management and monitoring • Automate warehouse management tasks

38. Metadata Management • Define metadata strategy • Define metadata types • Specify requirements for the metadata repository, integration, and access • Establish technical and business views of metadata • Develop modules for capturing, bridging, and accessing metadata

39. Data Access • Identify, select, and design user access tools • Define user profiles • Determine requirements for interface style, queries, reports, and the end user layer • Evaluate, acquire, and install access objects - Queries and reports - Catalogs - Hierarchies and dimensions

40. Database Design and Build • Support data requirements • Provide efficient access • Create and validate logical and physical models • Create relational and multidimensional database objects • Evaluate partitioning, segmentation, and placement • Identifying indexes and keys • Generate DDL • Build and implement database objects

41. Documentation Produce textual deliverables: • Glossary • User and technical documentation • Online help • Metadata reference guide • Warehouse management reference • New features guide

42. Testing • Develop a test strategy • Create test plans, scripts, and scenarios • Test all components: - Data acquisition - Data Access - Ad hoc access - Regression - Volume - Backup - Recovery • Support acceptance testing

43. Training • Define requirements: - Technical - End user - Business • Identify staff to be trained • Establish time frames • Design and develop materials • Focus on tool training and use of the warehouse

44. Transition • Define tasks for transitioning to the production warehouse • Migrate modules and procedures • Develop the installation plan • Prepare the maintenance environment • Prepare the production environment

45. Post-Implementation Support • Evaluate and review warehouse use • Monitor warehouse use • Refresh the warehouse • Monitor and respond to problems • Conduct performance testing and tuning • Transfer responsibility • Evaluate and review the implemented solution

46. Tasks and Deliverables • Outlined in Work Breakdown Structure • Organized by process and phase Task ID Task Name A Strategy A. RD.EXEC Business Requirements Definition A.RD.001 Obtain Existing Reference Material A.RD.002 Obtain Reference Data Models A.RD.003 Define Strategic Goals, Vision of the Enterprise A.RD.004 Establish Business initiatives A.RD.005 Define Objectives and Purpose of Enterprise Data Warehouse A.RD.015 Collect Enterprise Business Information Requirements

47. Roles • The project team: roles and responsibilities • Common roles Analyst, database administrator, programmer, tester • Warehouse specific roles DW architect, metadata architect, data quality administrator, DW administrator

48. Warehouse Technology Initiative • Customer driven - Warehouse products only - Quality, not quantity - High-value partnerships • Requires - Oracle certified solution partner level - Product certification - Reference

49. WTI Partners by Categories • Design and administration • Source • Manage • Access • Data content provider

50. Summary This lesson discussed the following topics: • Explaining the different approaches to warehouse development and the benefits of an incremental approach • Identifying the purpose of the Oracle Method • Discussing the purpose and fundamental elements of Data Warehouse Method • Discussing the objectives of the Oracle Warehouse Technology Initiative