Introduction to Data Management Chapter 1 Pratt Adamski

Introduction to Data Management Chapter 1, Pratt & Adamski

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.

Knowledge Generation DATA INFORMATION

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

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

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

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

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

Database DATA METADATA ACCESS ENGINE UTILITIES

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

Database Access USER INTERFACE DATABASE PROGRAM

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

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.

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

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.

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.

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

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

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

Relational Terminology z. Entity y. Person, place, thing or event about which we wish to keep data z. Attribute yproperty of an entity z. Relationship yan association among entities (entity records)

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

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.