Architecting Data Lakes

February 28, 2018

Author Ben Sharma explains the steps necessary to deploy data lakes with robust, metadata-driven data management platforms

Revised for 2018. Data lakes have proven to be highly useful data management architectures for advanced business use cases that require big data inputs. In this eBook, we will discuss best practices associated with building, maintaining and deriving value from a data lake in production environments. Included is a detailed checklist to help you construct a data lake in a controlled yet flexible way.

If you are concerned with building a data architecture that will serve you now and scale for the future, this is a must-read book. You’ll examine: 

  • A reference data lake architecture
  • Key data lake attributes, including ingestion, storage, processing, and access
  • Why implementing data management and governance is crucial for the success of your data lake
  • How to curate the data lake through data governance, acquisition, organization, preparation, and provisioning
  • Methods for providing secure self-service access for users across the enterprise
  • How to build a future-proof data lake tech stack that includes storage, processing, and data management
  • Emerging trends that will shape the future of data lakes

About the Author

Ben Sharma, CEO and cofounder of Zaloni, is a passionate technologist with experience in solutions architecture and service delivery of big data, analytics, and enterprise infrastructure solutions. Previously with NetApp, Fujitsu, and others, Ben’s expertise ranges from business development to production deployment in a wide array of technologies, including Hadoop, HBase, databases, virtualization, and storage. Ben is the coauthor of Java in Telecommunications and holds two patents.

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