Common Analytical Architectures and Components, Part 2

Contemporary Architecture Patterns

This is the Part 2 of the draft chapter on Common Analytical Architectures and Components. I’ve tried to cover the big architectures and components in use today. That said, I might miss something, especially when it comes to the intersection of AI and analytics. If I missed something, drop a line in the comments.

If you think you’ve found a errors, please add them to this errata form. Having all of the errata in one place will help keep me focused organized on addressing potential errors, versus the high friction hellscape I’ve currently created for myself.

Thanks,

Joe

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The popularity, volumes, and use cases of data have exploded over the last decade. Data is analyzed at a scale and in ways that were never imagined in the early days of data warehousing.

Data Lakehouses

While the heart and soul of the data warehouse is alive and well in all analytical architectures, the variety of data and use cases has grown since the data warehouse was created. We’ve transitioned from a world of tables to one that incorporates semi-structured and unstructured data, ingests data from streams, and more. Let’s look at some closely related cousins of the data warehouse - the data lake and data lakehouse.