1. Data Administration Bad administration, to be sure, can destroy good policy; but good administration can never save bad policy Adlai Stevenson, 1952

2. 2 Data administration Data are the lifeblood of organizations Data need to be managed Data administration is concerned with the management of organizational memories

3. 3 Data are generated by stakeholders Employees Customers Shareholders Investors Suppliers Government

4. 4 Data management problems Redundancy Inconsistent representations Multiple definitions of data items Essential data missing Inaccurate or incomplete data Uncaptured data Data that cannot be located

5. 5 Goals of data management Enable users to access the data they need in the most suitable format Maintain data integrity

6. 6 Management of the database environment

7. 7 Components of the database environment Databases User interface Data dictionary External databases

8. 8 Data administration System Environment wide management issues Planning Data standards and policy Data integrity Resolving data conflicts Managing the DBMS Data dictionary Benchmarking Project Defining user requirements Data modeling Training and consulting Monitoring integrity and usage Change management

9. 9 Data administration functions and roles A function is a set of activities to be performed Individuals are assigned roles to perform certain activities Data administration functions may be performed by a: Data administrator Data administration staff Database development Database consultant Database analyst

10. 10 Data steward Responsible for managing all corporate data for a critical business entity or product Cuts across functional boundaries Aligns data management with organizational goals

11. 11 Database use levels Personal Workgroup Organizational More users means greater complexity

12. 12 Personal databases Notebook computers Personal digital assistants (PDAs) Personal information managers (PIMs) Cell phones Music players (iPod) Information appliances

13. 13 Workgroup and organizational databases Shared by many people Greater complexity Require more planning and co- ordination than personal databases

14. 14 System level data administration Planning Development of data standards and policies Data integrity Data conflict resolution Managing the DBMS Establishing and maintaining the Data Dictionary Selection of hardware and software Benchmarking Managing external databases Internal marketing

15. 15 Konflikthåndtering Eksempel: De som sitter i kassa blir bedt om å spørre etter bydel og registrere bydel, antatt alder og kjønn på den som kjøper, slik at markedsføring kan skreddersys Problem: De som sitter i kassa gjør en dårlig jobb – registrering mangler eller er feil i mange tilfeller Diskusjon: Hvordan kan problemet løses

16. 16 Selection of hardware and software How many users will simultaneously access the database? Will the database need to be geographically distributed? What is the maximum size of the database? How many transactions per second can the DBMS handle? What kind of support for on-line transaction processing is available? What are the initial and ongoing costs of using the product? What is the extent of training required, will it be provided, and what are the associated costs?

17. 17 Benchmarking TPC-C Benchmarking of TPS TPC-H Benchmarking of ad-hoc decision support TPC-R Benchmarking of standard decision support TPC-W Benchmarking of Web sites

18. 18 Project level data administration functions Meeting the needs of individual applications and users Support and development of a specific database system

19. 19 Systems Development Life Cycle Application Development Life Cycle (ADLC) Database Development Life Cycle (DDLC) Project planning Requirements definition Application designDatabase design Application construction Application testingDatabase testing Application implementationDatabase implementation OperationsDatabase usage MaintenanceDatabase evolution

20. 20 Strategies for system development Database and applications developed independently Applications developed for existing databases Database and application development proceed simultaneously

21. 21 Development roles Database Development Phase Database DeveloperData AdministratorUser Project planningDoesConsultsProvides information Requirements definition DoesConsultsProvides requirements Database designDoesConsults Data integrity Validates data models Database testingSystem and user testing Consults Data integrity Does user testing Database implementation System related activities Consults Data integrity Does user activities Database usageConsultsData integrity monitoring Uses Database evolutionDoesChange controlProvides additional requirements

22. Database development cycle

23. 23 Data administration interfaces

24. 24 Data administration interfaces Management Sets the agenda and goals Users Seek satisfaction of goals Development Co-operation Computer operations Establishing and monitoring procedures for operating databases

25. 25 Data administration tools Database development phase Data Dictionary (DD) Database Management System (DBMS) Performance monitoringCase tools 1. Project planning Document Data map Design aid Estimation tools 2. Requirements definition Document Design aid Document Design aid 3. Database design Document Design aid Data map Schema generator Document Design aid Data map 4.Database testing Data map Design aid Schema generator Define, create, test, data integrity Impact analysis Test data generator Design aid 5.Database implementation Document Change control Data integrity Implement Design Monitor Tune 6. Database use Document Data map Schema generator Change control Provide tools for retrieval and update Enforce integrity controls and procedures Monitor Tune 7. Database evolutionDocument Data map Change control RedefineImpact analysis

26. 26 Data dictionary All columns – name, type, format, validation, constraints All relationships All databases All tables All indexes All users and their authorisations All programs that access the database and what they access – SQL queries...

27. 27 Use of the data dictionary Documentation support Data maps Design aid Schema generation Change control

28. 28 Data integration Lack of data integration is a common problem Examples Different identifiers for the same instance of an entity The same data stored in multiple systems Related data stored in different databases Different methods of calculation for the same business indicator in different systems

29. 29 Data integration Red divisionBlue division partnumber (code for green widget) 27 customerid (code for UPS) 53 Definition of salesdateThe date the customer signs the order

30. 30 Lack of data integration Red divisionBlue division partnumber (code for green widget) 2710056 customerid (code for UPS) 53613 Definition of salesdateThe date the customer signs the order The date the customer receives the order

31. 31 Goals of data integration A standard meaning and format for all data elements A standard format for each and every data element A standard coding system A standard measurement system A single corporate data model for each major business entity

32. 32 Data integration strategies Environmental turbulence HighLowModerate Low ModerateHigh LowHigh Unit interdependence

33. 33 Organizing the data administration function Creation of the function Selecting staff and assigning roles Locating the function

34. 34 Data administration reporting to the CIO

35. 35 Data administration reporting to Support Services

36. 36 Matrix structure for data administration

37. 37 Data administration as a staff function

38. 38 Decentralized data administration

39. 39 Conclusion Data administration is Growing in complexity Critical to the success of most organizations Generally underrated in importance