Unleashing Data Power with Lake House Architecture on AWS
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In our data-centric world, organizations are embracing contemporary data architectures to manage, process, and analyze vast volumes of information. The Lake House Architecture, a merger of data lake and data warehouse, is one such model. This article delves into the advantages of AWS-based Lake House Architecture and how it empowers businesses to fully harness their data…
Data Lake architectures vertigo — do you get it?
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In the previous post, I explained what a data lake is and its main business benefits. This time around we will have a brief look at related and most commonly adopted data architectures…
Understanding the elements of a well-built data lake that translates into business value
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In this article, we will overview the different layers of a well-built data lake, as well as highlight common pitfalls and challenges to consider when implementing a data lake architecture…
How well do you know a data lake and its main business benefits?
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When I tackled my first data lake project it was difficult for me to understand what it actually is. However, I finally grasped the concept with the help of understanding that there are three types of data — structured, semi-structured, and unstructured. In layman’s term, it is a data management solution that stores and process raw data at scale…
The Definitive Guide to Data Lakes on AWS
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This guide aims to empower you with the fundamental knowledge needed to understand what a standard data lake is, it’s main architecture elements and how you can utilise AWS services for managing your data securely and effectively. With base-level understanding, you can build your expertise in data lakes and implement them across various business functions.
DataPhoenix goes live!
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If you’ve been working with me for a while, you’ll probably know some of the great work I’ve been involved in in the realms of data solutions like data lakes, data mesh, AWS and DevOps…