DSU - From Raw to Refined: Exploring the Differences Between Data Warehouses and Data Lakes

Опубликовано 20 мая 2024, 18:26

00:00 - 01:13 - Introduction
01:13 - 03:09 - What is a data warehouse?
03:09 - 05:10 - What is a data lake and how does it different from a data warehouse?
05:10 - 08:30 - Difference between Data Lakes, Data Warehouse, and Lakehouse.
08:30 - 09:34 - What are open table formats and how can they be used?
09:34 - 11:53 - When to chose one solution versus another.
11:53 - 12:41 – Closing

In this episode Khendr’a Reid, Principal Data Strategy Tech Specialist at AWS, interviews Tony Stricker, Principal Data Strategy Tech Specialist at AWS. They take viewers on a deep dive into the world of data management, exploring the key differences between data warehouses and data lakes. Starting with an introduction to these concepts, the video delves into the unique characteristics and applications of each solution.

Viewers will learn what defines a data warehouse and how it differs from a data lake in terms of data structure, processing, and use cases. The video then expands on the "data lakehouse" approach, which combines the benefits of both warehouses and lakes. An important section covers open table formats and how they can be leveraged to maximize the value of data.

The video culminates in a discussion of when to choose one data solution over another, providing guidance for data professionals navigating the evolving data management landscape.

Whether you're new to data infrastructure or seeking to deepen your understanding, this video offers a comprehensive and insightful exploration of the data warehouse vs. data lake debate, giving viewers a clear grasp of the strengths, limitations, and appropriate applications of these powerful data architectures.

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