skip to main content

Introduction

Data lakes require adaptation of the data management practices that are already in place with enterprise data warehousing and data archival. The emphasis is on adaptation because the data lake is a different environment.

Highlights

  • Data lakes must be managed.
  • Data lakes will only succeed if they become shared resources.
  • For the data lake to become a shared resource, business end users must be prepared to take on new self-service responsibilities in curating data.

Features and Benefits

  • Summarizes the key building blocks for data lake governance.
  • Provides a reference architecture for data lake governance.

Key questions answered

  • What are the key building blocks for governing a data lake?
  • Why govern a data lake?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Ovum's definition of "data lake"

  • A lake, not a [choose your metaphor]

Assumptions

  • What's included
  • What's not included

The recipe for the data lake

  • Data inventory
  • Security
  • Operation/integration

Appendix

  • Methodology
  • Further reading
  • Author