CHAPTER 5 THE DATA RESOURCE

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 © 2005 Pearson Prentice-Hall Chapter 5 - 2 Page 135

WHY MANAGE DATA? Data should be: Cataloged Named in standard ways Protected Accessible to those with a need to know Maintained with high quality © 2005 Pearson Prentice-Hall Chapter 5 - 3 Page 135

TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE The Data Model Data model – overall map for business data needed to effectively manage the data © 2005 Pearson Prentice-Hall Chapter 5 - 4 Page 135

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 © 2005 Pearson Prentice-Hall Chapter 5 - 5 Page 135

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 © 2005 Pearson Prentice-Hall Chapter 5 - 6 Page 135

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, … © 2005 Pearson Prentice-Hall Chapter 5 - 7 Figure 5.1 Entity-Relationship Diagram Page 135

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 © 2005 Pearson Prentice-Hall Chapter 5 - 8 Page 136

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 © 2005 Pearson Prentice-Hall Chapter 5 - 9 Figure 5.2 Enterprise Decomposition for Data Modeling Page 136

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 © 2005 Pearson Prentice-Hall Chapter 5 - 10 Page 136

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 © 2005 Pearson Prentice-Hall Chapter 5 - 11 Page 136

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 © 2005 Pearson Prentice-Hall Chapter 5 - 12 Page 136-137

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 © 2005 Pearson Prentice-Hall Chapter 5 - 13 Page 137

Page 137 Figure 5.3 The Data Pyramid © 2005 Pearson Prentice-Hall Chapter 5 - 14 Figure 5.3 The Data Pyramid Page 137

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) © 2005 Pearson Prentice-Hall Chapter 5 - 15 Page 138

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 © 2005 Pearson Prentice-Hall Chapter 5 - 16 Page 138

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 © 2005 Pearson Prentice-Hall Chapter 5 - 17 Page 139

TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE Tools for Managing Data Important Notes: Most popular type of database architecture is relational Not all relational systems are identical. Best effort to date for standardizing relational databases is SQL © 2005 Pearson Prentice-Hall Chapter 5 - 18 Page 139

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 Security restrictions Volume and sizes List of applications that use the data Contains: Definition of each entity, relationship, and data element Display formats Integrity rules © 2005 Pearson Prentice-Hall Chapter 5 - 19 Page 139-140

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 SQL query language example: SELECT ORDER#, CUSTOMER#, CUSTNAME, ORDER-DATE FROM CUSTOMER, ORDER WHERE ORDER-DATE > ’04/12/05’ AND CUSTOMER.CUSTOMER# = ORDER.CUSTOMER# © 2005 Pearson Prentice-Hall Chapter 5 - 20 Page 140

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 © 2005 Pearson Prentice-Hall Chapter 5 - 21 Page 140

© 2005 Pearson Prentice-Hall Chapter 5 - 22 Figure 5.4 Page 142

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 © 2005 Pearson Prentice-Hall Chapter 5 - 23 Page 143

MANAGERIAL ISSUES IN MANAGING DATA Principles in Managing Data © 2005 Pearson Prentice-Hall Chapter 5 - 24 Figure 5.5 Types of Data Standards Page 143

MANAGERIAL ISSUES IN MANAGING DATA The Data Management Process © 2005 Pearson Prentice-Hall Chapter 5 - 25 Figure 5.6 Asset Management Functions Page 144

Page 146 Figure 5.7 The Data Warehouse © 2005 Pearson Prentice-Hall Chapter 5 - 26 Figure 5.7 The Data Warehouse Page 146

MANAGERIAL ISSUES IN MANAGING DATA Data Management Policies Organizations should have policies regarding: Data ownership Data administration © 2005 Pearson Prentice-Hall Chapter 5 - 27 Page 148

MANAGERIAL ISSUES IN MANAGING DATA Data Ownership Corporate information policy – foundation for managing the ownership of data © 2005 Pearson Prentice-Hall Chapter 5 - 28 Page 148

Page 149 Figure 5.8 Example Data Access Policy © 2005 Pearson Prentice-Hall Chapter 5 - 29 Figure 5.8 Example Data Access Policy Page 149

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 © 2005 Pearson Prentice-Hall Chapter 5 - 30 Page 150

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. © 2005 Pearson Prentice-Hall Chapter 5 - 31 Page 150-151