TDWI Emerging Best Practices for Data Lakes

Type: Analyst Research

Product: Data Integration

The need for fact-based decision-making means that businesses are more dependent on data than ever before. This often means leveraging a data lake (frequently using Hadoop) - but it’s not always easy to ensure that a data lake truly serves the needs of the business. From the great size and diversity of data within a data lake, to the need to support a wide range of interfaces, platforms, data structures, and processing methods, too often data lakes turn into a messy data swamp, and fail to deliver promised analytic value.

How can you ensure a successful data lake? 

This TDWI Checklist will discuss many of the emerging best practices for data lakes, including technical data management issues and practical business use cases.  Read the checklist and learn more about how to:

  1. Design a data lake for both business and technology goals
  2. Simplify your data lake with a scalable onboarding process
  3. Rely on data integration infrastructure to make the data lake work
  4. Integrate your data lake with enterprise data architectures
  5. Embrace new data management best practices for the data lake
  6. Empower new best practices for business analytics via a data lake