Introduction to Data Management

1. Introduction to Data
Management
Chapter 1, Pratt & Adamski

2. Data and Information
DATA: Facts concerning people, objects, vents or
other entities. Databases store data.
INFORMATION: Data presented in a form
suitable for interpretation.
Data is converted into information by programs
and queries. Data may be stored in files or in
databases. Neither one stores information.
KNOWLEDGE: Insights into appropriate actions
based on interpreted data.

3. Knowledge Generation
DATA
INFORMATION

4. Basic Principles
DATABASE: A shared collection of interrelated
data designed to meet the varied information
needs of an organization.
DATABASE MANAGEMENT SYSTEM: A
collection of programs to create and maintain a
database.
Define
Construct
Manipulate

5. Advantages of Database
Processing
More information
from same data
Shared data
Balancing conflicts
among users
Controlled
redundancy
Consistency
Integrity
Security
Increased
productivity
Data independence

6. Disadvantages of
Database Processing
Increased size
Increased complexity
More expensive personnel
Increased impact of failure
Difficulty of recovery
Cost
Especially server and mainframe systems

7. Objectives of the DBMS
Approach
SELF-DESCRIBING
DATA INDEPENDENCE
MULTIPLE VIEWS
MULTIPLE USERS

8. What is a Database
Management System?
Data Files
Directory
Access Engine
Utility Programs

9. UTILITIES
ACCESS ENGINE
METADATA
Database
DATA

10. Files and Databases
Metadata
“Data about data”
Description of fields
Display and format instructions
Structure of files and tables
Security and access rules
Triggers and operational rules

11. Database Access
DATABASE
PROGRAM
USER
INTERFACE

12. History of Database
Management
File Management Systems
Hierarchical Model
IBM “Information Management System (IMS)” 1966
Network Model
Charles Bachman’s “Integraded Data Store (IDS)” 1965
Conference on Data Systems Languages /DataBase Task
Group CODASYL/DBTG (1971)
Relational Model
E.F. Codd, 1970

13. File Management Systems
Provided facilities to extract data and
share files, but did not implement any
way to connect records in one file to
those in another. Relationships had to be
implemented in application code.

14. Database vs File Systems
Program 1
Program 2
Program 3
Meta-Data
Meta-Data
Meta-Data
Data
Program 1
Program 2
Program 3
Meta-
Data
Data
FILE SYSTEM
DATABASE

15. Structured Databases
Relationships were implemented by
physical pointers (called “sets”) which
allowed records to be connected in
different files. Hierarchical databases
allow only one parent set; networks allow
several. These permit efficient processing
but the sets must be constructed on data
entry and cannot be rearranged later.

16. Relational Models
Relational models implement relationships
with matched data values in related files
(called primary and foreign keys). Any
attributes can be matched. The
connection is established at retrieval so
interconnections can be developed as
needed.

17. STUDENT
SECTION
INSTRUCTOR
Hierarchy
COLLEGE
COLLEGE
Each file can have only one parent. To implement a second
“parent” (COLLEGE) we have to implement a shadow copy.

18. STUDENT
SECTION
INSTRUCTOR
Network
COLLEGE
Each file can have several parents. Both SECTION and
COLLEGE are “parent” files..

19. SECTION
Relational
COLLEGE
Each file can have several parents. Both SECTION and
COLLEGE are “parent” files..
STUDENT
COLLEGE-KEY
INSTRUCTOR
COLLEGE-KEY
SECTION-STUDENT
SECTION-KEY
STUDENT-KEY
SECTION-INSTRUCTOR
SECTION-KEY
INSTRUCTOR-KEY

20. Relational Terminology
Entity
Person, place, thing or event about which we
wish to keep data
Attribute
property of an entity
Relationship
an association among entities (entity
records)

22. KERR MCGEE’S LIFE CYCLE
STAGE PROCESS MODEL DATA MODEL
Initialization Report Report
Feasibility Report
High Level DFD
Process Analysis
(Business Chart)
High Level E/R Diagram
Requirements
General
DFD
High Level Dictionary
Top Down E/R
File Specifications
Requirements
Logical
DFD
Data Dictionary
File Specifications
Process Logic
Bottom Up E/R
Action Diagrams
System Design Structure Charts
Module IPO Specification
Screen/Report Layouts
Cleanup
Volume/Usage Analysis
Physical Schema
Index/Record Specs
Coding/Testing Test Plan
Logs and Documentation
Code
Implementation Installation Plan Population Plan

23. Data Management
Designing and managing information in a
data base environment requires:
Understanding the principles of data
modeling in system design.
Using SQL for data manipulation.
Understanding the concepts of managing
data in a database environment.

24. Information System
Modeling Approaches
PROCESS MODELING: The traditional method of
designing systems by following the changes to data
flows.
DATA MODELING: An approach to system development
that specifies the file structure that conforms to the
things important to the organization.
PROTOTYPING: An iterative approach that focuses on
building small operating
OBJECT MODELING (Event driven design):
Defines objects that contain data and associated
processing rules encapsulated together.