M Q Hasan Lecturer/ Statistician UN Statistical Institute for Asia and the Pacific Chiba, Japan Email : hasan@unsiap.or.

1. Data Management (2)“Application of Information and Communication Technology to Production and Dissemination of Official statistics”10 May – 11 July 2007 M Q Hasan Lecturer/ Statistician UN Statistical Institute for Asia and the Pacific Chiba, Japan Email : hasan@unsiap.or.jp

2. Overview • Data management • Data management planning • Data management procedures • Data management software • Hands on experience

3. Recap….. • Managing files during generation • Directory structure • Documentation • Managing files afterwards

4. Data management and the NSO • Data management • All case – long term

5. Data management • Management “files” afterwards. • Different types of files. • Data. • Report. • Computer programs. • Databases. • Etc.

6. Data management • Management “files” afterwards. • Different types of files created with different software packages. • Statistical packages (SPSS, STATA). • Spreadsheet (excel). • Compiler (C++, java ). • Document (MsWord). • Etc.

7. Data management • Management “files” afterwards. • Different types of files created with different application software. • Database (oracle). • DevInfo • Others

8. Data management • Management “files” afterwards. • Different files created are in different media. • Hard disk. • CD. • Floppy. • Juke-box. • Tape. • Flash memory. • others

9. Data management • Management “files” afterwards. • Different files created are at different location. • Different people. • Different section. • Different building but same site. • Different sites

10. Data management • Management “files” afterwards. • Different types of files created in different computing environment. • Unix operating system of different flavors (sun, HP etc). • PC with different operating systems (windows, NT, XP etc.). • Macintosh. • Etc.

11. Data management System analysis

12. Data management : SA • Locate as many “data” as possible and prepare inventory list. • Location. • Creation date. • Person responsible. • Type of contents. • Access conditions. • Size. • Media. • Type and format. • Etc.

13. Data management : SA • Develop naming conventions • Dataset • Files

14. Data management : SA • Check data randomly • Read • Complete • Error free

15. Data management : SA • Completeness check • Identify missing files • Create missing files • Correct files that have errors

16. Data management : SA • Classification • Trial and Error method • Consult all

17. Data management : SA Develop Data files Organization Structure Clarify Fall Back Situations

18. Data management : System Migration (Integration)

19. Data management : SM • Prepare H/W • Identify and procure application software • Develop automation routines for file transfer

20. Data management : SM • Cautious about “moving target.” • Execute transfer when system is less likely to be accessed. • Cross check to make sure files are moved properly. • Date. • Size in bytes. • Owner. • Access rights

21. Data management : • Maintain System • User services

22. Data management : • Backupduring system migration • Data processors responsibility • Temporary back up

23. Data management : • Backup after system migration • System administrator’s responsibility • At least 3 copies • One offsite copy

24. Knowledge management

25. Knowledge management (1) • Is a very generic term. • Often implies management of information in electronic format. • In a broader term, it is the organization of scattered information in such a way that people looking for specific information be able to find it and access it easily.

26. Knowledge management (1) • This scattered information may be located in an organization in the same building at a single point or different sites across national and international boundaries at various points. • Each piece of information may also vary in format, size, content, and etc. • Information can be accessed as a single piece or as a combination of many pieces.

27. Knowledge management (2) • Ideally, KM is a processing model that includes the collection and management of quality information. • Quality checking is part of KM. • Information harmonisation. • For better performance and usability of the KM system.

28. Knowledge management (3) • KM deals with the physical organisation of the information. • Puts an invisible interface between the information (knowledge) and its users. • KM requires a dissemination policy as to “who can access which information and how” of the managed knowledge.

29. Knowledge management ….. • Integration of KM system into working places and beyond. • Culture, change of attitude towards the use of such systems. • Promotion of knowledge contribution. • Continuous maintenance of KM systems.

30. Information System (IS) • Processing System (PS , TPS) • Management Information system (MIS) • Decision Support System (DSS) • Executive Information System (EIS) • Expert System (ES)

31. IS & Management • Processing System • Lowest building block of an Information System • Records and process data • Executed by lower management level • Involvement of single section/department

32. IS & Management • Management Information system • Executed by middle management level • Uses data recorded by processing level • Supports decision making activities through production of statistics, analytical reports etc. • Involvement of multiple sections/departments

33. IS & Management • Decision Support System • Executed by middle / top management level • To backup strategic decisions

34. IS & Management • Executive Information System • Executed by top management level • Deals with what if situations

35. IS & Management • Expert System • Analyzes what if situations automatically • Process of analyzing data to identify patterns or relationship • Extraction of pattern or information from stored information

36. End