Database Fundamentals and Information Systems Explained
Fundamental Concepts of Data and Databases
Key Definitions
- Data: Facts about people, objects, events, or other entities. Data can be:
- Quantitative or Qualitative
- Internal or External
- Historical or Predictive
- Information: Consists of data that has been organized and processed to provide meaning.
- Database: A collection of related data that can satisfy the information needs of an organization, facilitating data integration and sharing.
Traditional Data Processing Approach
The traditional approach to data processing was commonly used in developing early information systems. It often involved an aggregation approach where each system was designed to meet the specific needs of a single department, rather than a planned corporate strategy. This represented an evolutionary process where new system functions were connected as needed.
Disadvantages of the Traditional Approach
- Uncontrolled Redundancy: Leads to wasted storage space and increased time lost during data updates.
- Data Inconsistency: Results in errors within applications and inconsistent reports.
- Inflexibility: Slows down the evolution and adaptation of the information system.
- Poor Standardization: Causes inconsistency due to the use of synonyms and homonyms across different systems.
Database Management Systems (DBMS)
Core Principles of the Database Approach
- Data is viewed as a shared resource.
- Each user can have a customized view of the database based on their specific requirements.
- Data is independent of the programs that use it.
What is a DBMS?
A Database Management System (DBMS) is software that controls a database, managing its protection, insertion, modification, deletion, and retrieval of data.
Key Functions of a DBMS
- Data Definition: Specifies the data types, structures, relationships, and constraints that are stored in the database.
- Data Manipulation: Allows users to store, modify, and retrieve data from the database.
- Data Security: Enables access control and provides mechanisms for data integrity and recovery.
Elements of a Database System
- Database (BD): The physical location where the data is stored.
- Repository and Data Dictionary: Stores metadata, including data definitions and system information.
- User-System Interfaces: Allow users to interact with the database.
- Application Software: Used to create, maintain, and interact with the database.
- CASE Tools (Computer-Aided Software Engineering): Support software development and database design.
Risks of Using the Database Approach
- Need for Specialized Staff: Requires personnel skilled in converting existing systems, developing new programming standards, database design, and managing the database team.
- Increased Need for Backups: Having minimal data redundancy necessitates robust backup and recovery procedures to prevent significant data loss.
- Challenges in Data Sharing: Requires careful data synchronization, concurrent access management, and crash detection to prevent interference and ensure data integrity.
Types of Information Systems
Operational and Analytical Systems
- Operational Information Systems (OIS) or Transaction Processing Systems (TPS): Support the daily operations of an organization, providing detailed, timely, and accurate information.
- Decision Support Systems (DSS): Aid decision-makers by providing information and analytical tools to support complex problem-solving.
- Management Information Systems (MIS): Provide information necessary for administrators to plan and control organizational operations.
- Data Warehouse: A repository for critical data used in decision-making, integrating data from various sources to facilitate rapid analysis.
- Data Mining: Techniques and tools used to discover patterns, trends, and insights from large datasets, often sourced from data warehouses.
- Online Analytical Processing (OLAP): Simplifies querying large databases, often using multidimensional structures for analytical purposes.