Practical data management

Description

The course enables participants to search for relevant, publicly available datasets in order to analyze, manage, and integrate them into a consolidated dataset with a focus on consistency, quality, and efficient storage. Participants also gain practical experience with challenges related to data discovery, analysis, and decision making.

Participants will gain knowledge and hands-on experience in:
- Data Management: Key concepts, importance, and applications across domains
- Data Lifecycle and Flow: How data moves across multiple sources, systems, and applications with varying access rights
- Data Governance: Policies, standards, and best practices
- Data Sources: Accessing and collecting data from databases, APIs, log files, and external datasets (e.g., Statistics Denmark, the National Archives, forskningsportal.dk)
- Data Preparation: Cleaning and transforming data to ensure consistency and accuracy for analysis
- Storage Solutions and Data Formats: Selecting appropriate storage methods and formats for efficiency and cost-effectiveness (during processing and for long-term archiving)
- Data Quality Tools: Monitoring and maintaining data quality to ensure reliability

Participants are expected to have basic knowledge of programming for data handling e.g. in Python. No advanced programming experience is required.

Syddansk Universitet