‘Data Governance in Multi-Tenant Data Lakes – A Tech Perspective’

What You’ll Learn:

1. Understanding Data Governance:
   • Grasp the foundational principles of data governance and its importance in managing valuable business data.
   • Learn about the key aspects such as data quality measures, metadata capturing, and access controls.
2. Multi-Tenancy Challenges:
   • Discover the expanding context of multi-tenancy and how it adds layers of complexity to data governance.
3. Tech Building Blocks for Governance:
   • Explore the essential technological components for a robust governance system, including asset inventory, lineage, security mechanisms, and quality metrics.
4. Policy Management:
   • Dive into creating dynamic, self-serve policies for data access and management that align with governance goals.
5. Lifecycle and Ownership:
   • Understand the evolving lifecycle of data and the significance of ownership and permissions throughout the data’s journey.
6. Quality Measurement:
   • Learn the importance of continuous quality measurement and the tools that can aid in maintaining high data standards.
7. Solving the Lineage Problem:
   • Tackle the lineage problem in multi-tenancy architectures and the methodologies to attribute data sources accurately.
8. Leveraging Graph Databases:
   • See the advantages of using graph databases for managing complex, multi-relational data governance challenges.
9. Evaluating Tools for Governance:
   • Get insights into the criteria for evaluating governance tools and the leading solutions in the market.
10. Security and Infrastructure:
    • Gain knowledge on implementing zero trust and positive security models in your data infrastructure.
11. Towards Self-Serve Automation:
    • Embrace the path to self-serve and minimal operational support with declarative data workflows and automated provisioning systems.