The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture

by Rukmani Gopalan

More organizations than ever understand the importance of data lake architectures for deriving value from their data. Building a robust, scalable, and performant data lake remains a complex proposition, however, with a buffet of tools and options that need to work together to provide a seamless end-to-end pipeline from data to insights. This book provides a concise yet comprehensive overview on the setup, management, and governance of a cloud data lake. Author Rukmani Gopalan, a product management leader and data enthusiast, guides data architects and engineers through the major aspects of working with a cloud data lake, from design considerations and best practices to data format optimizations, performance optimization, cost management, and governance.

Genres: Technology

244 pages, Paperback

Published January 17, 2023

Reviews

[Thang]

A short but informative book for data engineers:
- Cover basic concept of Data Warehouse, Datalake, Data Lakehouse, Datamesh, and Modern Data architecture (Datalake + Data warehouse)
- Go to basic open data formats such as Apache Iceberg, Apache Hudi, Delta Lake

[Kin]

I read few chapters only it’s a good book.

Some learning on datalake:
Big companies moved existing data to cloud i.e aws Amazon stores days in S3 buckets then you can add permission/rules and then data can be used by ai/machine learning

Datalake costs less than data warehouse, supports modern tools, framework ai/ml and let your future proof your design to scale to your growing needs

Datalake ability to store and process unstructured data.