Data Management
The Managerial Perspective
Importance of data management in organizations.
Data is doubling every 1-2 years; companies manage vast amounts.
Human Information Processing System
Newell-Simon model of human information processing: input, processing, output.
External memory tools (smartphones, apps) augment human memory and processing capabilities.
Organizational Information Processing
Organizations collect data from the environment, process it, and produce outputs (e.g., sales forecasts).
Organizational memory is fragmented across various types and needs external sources for data processing.
Data Management Essentials
Key components of organizational memory: people, processes, and technology.
Effective data management requires understanding both organizational behavior and information technology.
Characteristics of Effective Data
Shareable, transportable, secure, accurate, timely, and relevant.
These attributes facilitate effective decision making and operational efficiency.
Problems in Data Management Systems
Common issues include redundancy, lack of data control, poor interfaces, delays, and lack of integration.
Organizations must address these problems to enhance data management systems.
Types of Information Systems
Transaction Processing Systems (TPS), Management Information Systems (MIS), Decision Support Systems (DSS), etc.
Each system serves unique purposes and contributes to the decision-making process.
Decision Making
High-quality decision making is critical for organizational success.
Managers need timely and relevant data to make informed decisions.
Knowledge Management
Difference between data (raw facts), information (processed data), and knowledge (understanding how to use information).
Knowledge is key for effective decision making and organizational success.
Conclusion
Organizations need to effectively leverage their data management systems for competitive advantage.
Continuous improvement in data management practices is essential for adapting to changing environments.