제 5 장

1. 제 5 장 업무 요구사항 규정 DEFINING THE BUSINESS REQUIREMENTS Data Warehousing

2. 장의 목표 • Defining requirements is different for a data warehouse • 업무 차원의 역할 이해 • Information packages와 그 용도 • 요구 사항 수집 방버 • Formal requirements definition document Data Warehousing

3. DW system 정보 전달 시스템 의사결정 지원 시스템 요구사항들을 수집할 때 정보가 무엇인지에 집중 OLTP system 데이터 획득 시스템 요구사항들 수집 일일 업무 운용 시스템 DW system and OLTP system Data Warehousing

4. 5.1 차원 분석DIMENSIONAL ANALYSIS • DW 구축 시 운용 시스템 구축과 다르다 • Usage of Information Unpredictable • Dimensional Nature of Business Data • Examples of Business Dimensions Data Warehousing

5. Usage of Information Unpredictable • Requirements for an operational system • Give precise details of required functions, information content, and usage patterns • Requirements for a data warehousing system • Generally unable to define their requirements clearly • Cannot define precisely what information from DW • Nor can express how they would like to use the information or process it Data Warehousing

6. 업무 데이터의 차원 성질 • Users can provide very important insights into how they think about the business • What measurement units are important • How they measure success in the particular department • How they combine the various pieces of information for strategic decision making • Figures 5-1 and 5-2 Data Warehousing

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9. 업무 차원의 예제 • Figure 5-3 • Supermarket Chain • Sales units • Insurance Business • Claims • Manufacturing Company • Shipments • Airlines Company • Frequent flyer flights Data Warehousing

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11. 5.2 정보 패키지INFORMATION PACKAGES– A NEW CONCEPT • A novel idea for determining and recording information requirements for a data warehouse • Requirements Not Fully Determinate • Business Dimensions • Dimension Hierarchies/Categories • Key Business Metrics or Facts Data Warehousing

12. 요구사항은 충분히 결정적이지 않다 • When requirements cannot be fully determined, we need a new and innovative concept to gather and record the requirements • The new methodology is based on business dimensions • The basic measurements and the business dimensions • Information package for the specific subject • Figure 5-4 Data Warehousing

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14. 정보 패키지는 당신에게 다음을 가능하게 할 수 있다: • Define the common subject areas • Design key business metrics • Decide how data must be presented • Determine how users will aggregate or roll up • Decide the data quantity for user analysis or query • Decide how data will be accessed • Establish data granularity • Estimate data warehouse size • Determine the frequency for data refreshing • Ascertain how information must be packaged Data Warehousing

15. 업무 차원Business Dimensions • Data must be stored to provide for the business dimensions • To identify business dimensions and their hierarchical levels • Business dimensions for the subject of sales for an automaker • Product, dealer, customer demographic, method of payment, and time • Hotel occupancy information package • Hotel, room type, and time Data Warehousing

16. 차원 계층/범주Dimension Hierarchies/Categories • Hierarchy of the time dimension • Levels of year, quarter and month • Dimension hierarchies are the paths for drilling down or rolling up in our analysis • Categories of data elements • Holiday flag in the time dimension • Package type in the product dimension • Hierarchies and categories are included in the information packages for each dimension Data Warehousing

17. 주요 업무 측정 규준 또는 사실 • Using these business dimensions, what exactly are the users analyzing? • Numbers • Measurements or metrics • Facts • Figures 5-5 and 5-6 Data Warehousing

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20. 5.3 요구사항을 수집하는 방법 • Who are the users that can make use of the information in the data warehouse? • Where do you go for getting the requirements? Data Warehousing

21. 데이터 웨어하우스의 사용자 • Senior executives (including the sponsors) • Key departmental managers • Business analysts • Operational system DBAs • Others nominated by the above Data Warehousing

22. 어떤 요구사항을 수집해야 되는가? • Data elements: fact classes, dimensions • Recording of data in terms of time • Data extracts from sources systems • Business rules: attributes, ranges, domains, operational records Data Warehousing

23. Meeting with groups of people • Two basic techniques • Interviews • Joint application development(JAD) sessions Data Warehousing

24. A Few Thoughts about Interviews • Two or three persons at a time • Easy to schedule • Good approach when details are intricate • Some users are comfortable only with one-on-one interviews • Need good preparation to be effective • Always conduct preinterview research • Also encourage users to prepare for the intervie Data Warehousing

25. A Few Thoughts about Group Sessions • Groups of twenty or less persons at a time • Use only after getting a baseline understanding of the requirements • Not good for initial data gathering • Useful for confirming requirements • Need to be very well organized Data Warehousing

26. Interview Techniques • A list of major tasks on page 100 • Figure 5-7 • A list of some key research topics on pages 100 and 101 Data Warehousing

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28. Some Tips on the Types of Questions to be Asked • Current Information Sources • Subject Areas • Key Performance Metrics • Information Frequency Data Warehousing

29. Interview Write-ups • User profile • Background and objectives • Information requirements • Analytical requirements • Current tools used • Success criteria • Useful business metrics • Relevant business dimensions Data Warehousing

30. Adapting the JAD Methodology • Joint process • Methodology for developing computer applications jointly by the users and the IT professionals • Discussion workshop lasting a certain number of days Data Warehousing

31. Five-Phased Approach of JAD • Project Definition • Research • Preparation • JAD Session • Final Document Data Warehousing

32. Review of Existing Documentation • Be able to gather useful information from the review of existing documentation • Documentation from User Departments • Everything about the functions of the business units • Documentation on the processes and procedures in those units • Documentation from IT • Data for the metrics and business dimensions • Operational system DBAs and application experts from IT Data Warehousing

33. 5.4 요구사항 정의: 범위와 내용 • Formal documentation • Detailed documentation of the requirements definition • Basis for the next phases • 팀원이 떠나면, 뒤의 사람이 어려움이 없다 • Also validate your findings when reviewed with the users Data Warehousing

34. 공식적인 요구사항 정의문서를 위한 정보의 유형 • Data Sources • Data Transformation • Data Storage • Information Delivery • Information Package Diagram Data Warehousing

35. 데이터 소스 Data Sources • All the details you have gathered about the source systems • Available data sources • Data structures within the data sources • Location of the data sources • Operating systems, networks, protocols, and client architectures • Data extraction procedures • Availability of historical data Data Warehousing

36. 데이터 변환 Data Transformation • Involve mapping of source data to the data in the data warehouse • Indicate where the data about your metrics and business dimensions will come from • Describe the merging, conversion, and splitting Data Warehousing

37. 데이터 저장장치 Data Storage • Sufficient details about storage requirements • Preliminary estimates on the amount of storage needed for detailed and summary data • Estimate the size of historical and archived data Data Warehousing

38. 정보 전달 Information Delivery • Drill-down analysis • Roll-up analysis • Drill-through analysis • Slicing and dicing analysis • Ad hoc reports Data Warehousing

39. 정보 패키지 다이어그램 • Major and significant difference between operational systems and DW systems • The best approach for determining requirements for a DW • Crystallize the information requirements • The accuracy and adequacy of the information package diagrams Data Warehousing

40. 요구사항 정의 문서 개요Requirements Definition Document Outline • Introduction • General requirements descriptions • Specific requirements • Information packages • Other requirements • User expectations • User participation and sign-off • General implementation plan Data Warehousing