Publishing My First Book — A book on data, architecture, analytics, and cloud

Why did I author this book?

Who is this book for?

What does this book contain?

Part 1: The context setting

  • Chapter 1, Introducing the Evolution of Data Analytics Patterns, provides an overview of the evolution of the data architecture patterns for analytics.
  • Chapter 2, The Data Lakehouse Architecture Overview, provides an overview of the various components that form the Data Lakehouse architecture pattern.

Part 2: The deep dive

  • Chapter 3, Ingesting and Processing Data in a Data Lakehouse, deep dives into the methods of ingesting and processing data in a batch and streaming data in a Data Lakehouse.
  • Chapter 4, Storing and Serving Data in a Data Lakehouse, discusses the types of datastores of a data lake and various methods to serve data from a Data Lakehouse.
  • Chapter 5, Deriving Insights from a Data Lakehouse, discusses how one can perform business intelligence, artificial intelligence, and data exploration.
  • Chapter 6, Applying Data Governance in a Data Lakehouse, discusses the ways data can be governed, how to implement and maintain data quality, and how data needs to be cataloged.
  • Chapter 7, Applying Data Security in a Data Lakehouse, discusses various components used to secure the Data Lakehouse and ways to provide the proper access to the right users.

Part 3: The implementation and scaling

  • Chapter 8, Implementing a Data Lakehouse on Microsoft Azure, focuses on implementing the Data Lakehouse in a cloud computing platform like Microsoft Azure.
  • Chapter 9, Scaling the Data Lakehouse Architecture, discusses how data lakehouses can be scaled to realize macro-architecture patterns of Data Mesh and Hub-Spoke.



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Pradeep Menon

Pradeep Menon


Creating impact through Technology | #CTO at #Microsoft| Data & AI Strategy | Cloud Computing | Design Thinking | Blogger | Public Speaker | Published Author