CHAPTER 5 T HE D ATA R ESOURCE

1. CHAPTER 5 THE DATA RESOURCE

2. WHY MANAGE DATA? • Organizations could not function long without critical business data • Cost to replace data would be very high • Time to reconcile inconsistent data may be too long • Data often needs to be accessed quickly Page 135

3. WHY MANAGE DATA? • Data should be: • Cataloged • Named in standard ways • Protected • Accessible to those with a need to know • Maintained with high quality Page 135

4. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE The Data Model Data model – overall map for business data needed to effectively manage the data Page 135

5. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE The Data Model • Data modeling involves: • Methodology, or steps followed to identify and describe data entities • Notation, or a way to illustrate data entities graphically Page 135

6. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE The Data Model • Entity-relationship diagram (ERD) • Most common method for representing a data model and organizational data needs • Captures entities and their relationships • Entities – things about which data are collected • Attributes – actual elements of data that are to be collected Page 135

7. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE The Data Model • NOTE: • Entities are Customer, Order, and Product. • Attributes of the Customer entity could be • customer last name, first name, street, city, … Page 135 Figure 5.1 Entity-Relationship Diagram

8. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Data Modeling • Enterprise modeling • Top-down approach • Describes organization and data requirements at high level, independent of reports, screens, or detailed specifications • Not biased by how business operates today Page 136

9. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Data Modeling Enterprise Modeling Steps: • Divide work into major functions • Divide each function into processes • Divide processes into activities • List data entities assigned to each activity • Identify relationships between entities Figure 5.2 Enterprise Decomposition for Data Modeling Page 136

10. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Data Modeling • View integration • Bottom-up approach • Each report, screen, form, document produced from databases first … each called a user view Page 136

11. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Data Modeling View Integration Steps: • Create user views • Identify data elements in each user view and put into a structure called a normal form • Normalize user views • Integrate set of entities from normalization into one description Normalization – process of creating simple data structures from more complex ones Page 136

12. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Data Modeling • Data modeling guidelines: • Objective – effort must be justified by need • Scope – broader scope, more chance of failure • Outcome – uncertainty leads to failure • Timing – consider an evolutionary approach Page 136-137

13. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Database Architecture Database – shared collection of logically related data, organized to meet needs of an organization Database Architecture – way in which the data are structured and stored in the database Page 137

14. Page 137 Figure 5.3 The Data Pyramid

15. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Database Architecture • Six basic database architectures: • Hierarchical(top-down organization) • Network (high-volume transaction processing) • Relational(data arranged in simple tables) • Object-oriented(data and methods encapsulated in object classes) • Object-relational (hybrid of relational and object-oriented) • Multidimensional(used by data warehouses) Page 138

16. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Tools for Managing Data Database Management System (DBMS) – support software used to create, manage, and protect organizational data Page 138

17. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Tools for Managing Data • A DBMS helps manage data by providing seven functions: • Data storage, retrieval, update • Backup • Recovery • Integrity control • Security control • Concurrency control • Transaction control Page 139

18. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Tools for Managing Data • Most popular type of database architecture is relational • Not all relational systems are identical. • Best effort to date for standardizing relational databases is SQL Important Notes: Page 139

19. Contains: Definition of each entity, relationship, and data element Display formats Integrity rules Security restrictions Volume and sizes List of applications that use the data TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Tools for Managing Data Data Dictionary/Directory (DD/D) – central encyclopedia of data definitions and usage information … a database about data Page 139-140

20. SQL query language example: SELECT ORDER#, CUSTOMER#, CUSTNAME, ORDER-DATE FROM CUSTOMER, ORDER WHERE ORDER-DATE > ’04/12/05’ AND CUSTOMER.CUSTOMER# = ORDER.CUSTOMER# TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Database Programming Query language– a 4 GL, nonprocedural programming language to obtain data from a database, often provided by the DBMS Page 140

21. MANAGERIAL ISSUES IN MANAGING DATA Principles in Managing Data • The need to manage data is permanent • Data can exist at several levels • Application software should be separate from the database • Application software can be classified by how they treat data • Data capture • Data transfer • Data analysis and presentation Page 140

22. Page 142 Figure 5.4

23. MANAGERIAL ISSUES IN MANAGING DATA Principles in Managing Data • Application software should be considered disposable • Data should be captured once • There should be strict data standards Page 143

24. MANAGERIAL ISSUES IN MANAGING DATA Principles in Managing Data Page 143 Figure 5.5 Types of Data Standards

25. MANAGERIAL ISSUES IN MANAGING DATA The Data Management Process Page 144 Figure 5.6 Asset Management Functions

26. Page 146 Figure 5.7 The Data Warehouse

27. MANAGERIAL ISSUES IN MANAGING DATA Data Management Policies • Organizations should have policies regarding: • Data ownership • Data administration Page 148

28. MANAGERIAL ISSUES IN MANAGING DATA Data Ownership Corporate information policy– foundation for managing the ownership of data Page 148

29. Page 149 Figure 5.8 Example Data Access Policy

30. MANAGERIAL ISSUES IN MANAGING DATA Data Administration Key functions of the data administration group: • Promote and control data sharing • Analyze the impact of changes to application systems when data definitions change • Maintain the data dictionary • Reduce redundant data and processing • Reduce system maintenance costs and improve system development productivity • Improve quality and security of data • Insure data integrity Page 150

31. MANAGERIAL ISSUES IN MANAGING DATA Data Administration Key functions of the database administrator (DBA): • Tuning database management systems. • Selection and evaluation of and training on database technology. • Physical database design. • Design of methods to recover from damage to databases. • Physical placement of databases on specific computers and storage devices. • The interface of databases with telecommunications and other technologies. Page 150-151