Information Management Module 1

Study Notes

Data is the raw, unprocessed collection of facts in various forms including text, numbers, and media.
Information is processed and organized data that provides meaningful context and is intended for specific purposes.

IM involves the collection, storage, organization, retrieval, and dissemination of information within an organization.

Information Governance Strategy ensures policies and compliance are upheld and defines roles and responsibilities.
Data Management Strategy focuses on maintaining data quality, integration, and governance to enhance data utility.
Information Security Strategy employs access control, encryption, and incident response protocols to protect data.
Information Architecture Strategy involves designing taxonomy, structuring information, and enhancing user experience.
Information Lifecycle Management encompasses processes from creation, collection, and storage to archiving, disposal, and retention of information.

A database is an organized collection of related data stored electronically, enabling efficient access and management.

DBMS is software for creating, defining, manipulating, and managing databases, offering interfaces for user interaction.

Data Abstraction: Simplifies data presentation by managing physical storage and user interpretation.
Data Independence: Structure changes in data do not impact application programs.
Data Integrity: Ensures data accuracy and consistency through constraints and validation rules to minimize redundancy.
Data Security: Implements user authentication and authorization to protect data access.
Redundancy Control: Minimizes data duplication, preserving consistency via centralized management.
Transaction Management: Safeguards reliable transactions following ACID properties: Atomicity, Consistency, Isolation, Durability.
Concurrency Control: Manages simultaneous access to data by multiple transactions using locking and isolation levels to prevent data conflicts.
Backup and Recovery: Offers mechanisms to backup data and recover it in cases of loss or corruption.
Scalability: Supports vertical and horizontal scaling to accommodate rising data loads.
Data Modeling: Facilitates schema design, supporting various data models based on DBMS type.
Multi-User Support: Allows simultaneous access for multiple users, ensuring proper management.
Administrative Tools: Provides tools for database creation, maintenance, monitoring, and user administration.
Data Distribution: Supports replication and sharding for improved data availability.