Management Information Systems: Managing Data and Information

Learning Objectives

• 6.1 Problems in Traditional File Environments

  • Issues such as data redundancy, inconsistency, program-data dependence, lack of flexibility, poor security, and data sharing problems.

• 6.2 Capabilities of Database Management Systems (DBMS)

  • DBMS centralizes data, controlling redundancy, and allows for manageability and security. Relational DBMS employ tables for data relation, providing powerful organizational methods.

• 6.3 Tools and Technologies for Information Access

  • Tools include data warehouses, data marts, Hadoop, and analytical platforms aimed at improving business performance and decision making.

• 6.4 Importance of Data Governance and Quality Assurance

  • Essential for managing data resources, ensuring accuracy, completeness, and establishing controls for data use.

• 6.5 The Role of MIS in Careers

  • Understanding of MIS can improve career prospects in fields involving data analysis and management.

File Organization Terms and Concepts

• Database: Group of related Files

• File: Group of records of the same type

• Record: group of related fields

• Field: group of characters and/or numbers

• Entity: person place or thing on which we store information

• Attribute: each characteristic or quality to describe entity.

Problems with Traditional File Environment

• Issues Identified:

  • Files maintained separately by departments: leads to data silos.

  • Data Redundancy: unnecessary duplication of data.

  • Data Inconsistency: discrepancies across different files.

  • Program-Data Dependence: applications tied to specific data formats and structures.

  • Lack of Flexibility: adjustments in data structure require significant program modifications.

  • Poor Security: data spread across files may lead to vulnerabilities.

  • Lack of Data Sharing: difficulties in accessing consistent information across departments.

Database Management Systems (DBMS) Overview

• Key Benefits of DBMS:

  • Serves multiple applications by centralizing data; manages redundancy.

  • Provides logical and physical separation of data views.

  • Facilitates enhanced organizational control over data and security, addressing traditional file issues.

Relational DBMS Features

• Table Structure:

  • Composed of rows (records) and columns (attributes).

  • Key Fields:

  • Primary Key: Uniquely identifies each record.

  • Foreign Key: Links records across tables.

• Manipulation Operations:

  • SELECT: Filter data based on criteria.

  • JOIN: Merge tables for comprehensive data views.

  • PROJECT: Limit columns in output to specific data.

Data Governance and Quality Assurance

• Data Governance: Policies for managing, sharing, and classifying organizational data.

• Data Quality Assurance:

  • Identifying and rectifying inaccurate data.

  • Regular audits and cleansing routines ensure ongoing data quality.

Data Warehousing and Analytical Tools

• Data Warehouse: Centralizes historical data for analysis, supporting reporting but not allowing data alteration.

• Data Mart: A focused subset of a data warehouse tailored for specific business lines.

• Hadoop: Supports high-capacity storage and processing of big data, utilizing a distributed computing framework.

• In-memory Computing: Speeds up data access by utilizing RAM storage instead of disk, enhancing analytical processes.

Big Data and Business Intelligence

• Big Data Challenges: Handling massive data volumes requires new technologies for processing and analysis.

• Business Intelligence Infrastructure:

  • Involves using various analytical tools and platforms to gain insights from complex data sets, enhancing decision-making capabilities.

Conclusion on Data Utilization

• Utilizing Databases: Companies increasingly leverage databases for effective information management and strategic decision-making, supported by emerging technologies like cloud solutions and blockchain, to remain competitive and innovative in their operations.