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. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Data model – overall map for business data needed to effectively manage the data • Data modeling involves: • Methodology, or steps followed to identify and describe data entities • Notation, or a way to illustrate data entities graphically Page 135

4. 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

5. 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

6. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Data Modeling • Enterprise modeling (a process focus) • 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

7. 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

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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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

16. Page 142 Figure 5.4

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

18. 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

19. 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