Data Governance & Management
Data management and governance encompass a range of practices aimed at organizing and managing information to ensure its accessibility, security, and usability. This includes operational activities such as data storage, backup strategies, platform transitions, and full-stack web application development, as well as strategic frameworks for organizing data to support trustworthy Artificial Intelligence.
Key Concepts
- Storage Solutions: Options for storing and retrieving your data efficiently.
- cloud-storage
- local-storage
- Backup Strategies: Methods to ensure that your information is protected against loss or corruption.
- backup-strategies
- Data Migration: Processes involved in transferring your data from one system to another, such as moving from Evernote to other platforms.
- data-migration
- Full-Stack Web Application Development: Building functional web applications
Emerging Governance Models
Recent research examines four models of data governance emerging in the current platform society, shifting focus from purely technical management to broader data politics and data policy:
- See Micheli - Emerging models of data governance for analysis of corporate platform dominance and alternative governance structures.
- Key themes include big data, data infrastructure, and the political implications of datafication.
- Data Governance for AI: Structuring data to enable trustworthy algorithmic decision-making and information sharing.
- Establishes frameworks for Big Data and Open and Linked Data to support Artificial Intelligence reliability.
- Focuses on algorithmic governance and trusted frameworks for data utilization.
- See: Janseen - Data governance Organizing data for trustworthy Artificial Intelligence