Building a data lake house with reference architecture framework

Integrating data lakes and lake house architectures has become essential to an organization's data platform. However, this sophisticated structure has unique challenges, particularly in developing a lake house platform and integrating various source systems.

In this piece, we will systematically outline these obstacles and present our expertly crafted framework, a solution that has been thoughtfully engineered to confront and alleviate these complexities. Our reference architecture framework has been designed to address and mitigate these concerns, offering a robust solution for industry professionals. Let’s get into it.

Data lake house architecture using AWS

For this purpose, we will examine the data lake architecture utilizing Amazon Web Services (AWS). Within this framework, we outline the reference architecture framework, a model that can satisfy the needs for cohesive and all-encompassing data services. The graph and all subsequent steps are designed to showcase the reference architecture framework’s capabilities. Also, it highlights the untapped potential associated with building a data lake house architecture using AWS. Let’s break down each step to articulate the entire solution:

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