Sustainable data management: strategies and operational implementation

Module 1: Fundamentals and requirements for professional data management

Strengthening problem awareness: Why data-based decisions are essential.

• • Advantages of data-based decisions.
  • Challenges in the data structure (e.g., silo management, duplicates).
  • Analysis of the status quo in your own company.

Learning to understand data

• • Master data: Definition and meaning.
  • Big data - opportunities and risks at a glance.
  • How to generate meaningful information from raw data.

Establishing the foundations of sustainable processes

• • Create consistent processes - ensure uniformity in the use of data.
  • Introduction of metadata management: How to manage data correctly.
  • Define goals: Which KPIs should be achieved?

Module 2: Strategies and operational implementation for sustainable data management

Creating company-wide standards

• • Ensure quality through regular audits of your data processes.
  • Establishing a golden record: The path to a consolidated data basis in the company.

Optimize operational use

• • Efficient clustering - how to organize large amounts of data
  • Clean up inconsistent or incorrect data records.

Observe the legal framework

• • Ensure lawfulness of processing in accordance with GDPR.
  • Insights into the EU AI Act - What does it mean for your company?

Utilizing future prospects

• • Optimally prepare data sets - the basis for successful AI projects.
  • Introduction of a standardized procedure model for data mining.