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
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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
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4. TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE
The Data Model
Data model –
overall map for business data needed to effectively manage the data
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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
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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
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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, …
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Figure Entity-Relationship Diagram
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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
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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
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Figure Enterprise Decomposition
for Data Modeling
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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
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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
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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
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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
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14. Page 137 Figure 5.3 The Data Pyramid
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Figure The Data Pyramid
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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)
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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
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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
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18. 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
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19. 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
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20. 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#
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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
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22. © 2005 Pearson Prentice-Hall Chapter 5 - 22
Figure 5.4
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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
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24. MANAGERIAL ISSUES IN MANAGING DATA
Principles in Managing Data
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Figure Types of Data Standards
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25. MANAGERIAL ISSUES IN MANAGING DATA
The Data Management Process
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Figure Asset Management Functions
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26. Page 146 Figure 5.7 The Data Warehouse
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Figure The Data Warehouse
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27. MANAGERIAL ISSUES IN MANAGING DATA
Data Management Policies
Organizations should have policies regarding:
Data ownership
Data administration
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28. MANAGERIAL ISSUES IN MANAGING DATA
Data Ownership
Corporate information policy –
foundation for managing the ownership of data
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29. Page 149 Figure 5.8 Example Data Access Policy
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Figure Example Data Access Policy
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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
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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.
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