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

Why did I author this book?

Digital transformation is a reality. All organizations, big or small, must embrace this reality to be relevant in the future. Data is at the core of this transformation and data analytics is the catalyst for this transformation. Therefore, an agile, scalable, and robust architecture is pivotal for shaping data as a strategic asset.

Who is this book for?

I have always strived to make complex topics palatable to everyone. This book follows that trend.

What does this book contain?

This book is a comprehensive framework for developing a modern data analytics architecture. While authoring this book, I have focused on the architectural constructs of a Data Lakehouse. The book covers different layers and components of architecture. It explores how these different layers synthesize together to form a robust, scalable, and modular architecture deployed on any platform.

Part 1: The context setting

The first part of the book focuses on the evolution of Data architecture and provides an overview of Data Lakehouse architecture. This part has two chapters:

  • 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

The second part of the book drills down into details and explains the seven layers of data lakehouse architecture (ingestion, processing, data lake, serving, analytics, governance, and security). This part has three chapters:

  • 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

The third and final part of the book focuses on implementing the architecture in a cloud computing platform (Azure) and scaling the architecture with Data mesh/Hub-Spoke patterns. It has two chapters:

  • 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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