A Case Study: Unifying Data Sources with Azure Data Lake and Serverless SQL

The Dashboard Effect

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Brick and Caleb discuss Blue Margin's use of Azure Data Lake for unified data management. Using a recent client project as an example, Caleb explains how he integrated multiple data sources using serverless SQL to create a single data repository with a semantic model to enhance consistency across projects and reports. They also discuss the current performance benefits of using a serverless SQL and the Microsoft Fabric OneLake updates they're waiting on before transitioning from Azure Data Lake.

In this episode:

Introduction to Azure Data Lake: Caleb kicks off the discussion with an overview of Azure Data Lake, emphasizing its role in creating a unified data repository. The conversation highlights the significance of maintaining "one copy of your data" to eliminate redundancy and ensure consistency across various data analysis projects.
Client Case Study: Caleb walks through a recent project of creating an Azure Data Lake for a client. Learn about the challenges of integrating multiple data sources and how serverless SQL views simplify data modeling and reporting.
Serverless SQL Explained: Caleb outlines the benefits of serverless SQL, including its flexibility, cost-effectiveness, and how it caters to users familiar with SQL Server without the need for a traditional database setup.
Semantic Modeling for Unified Reporting: Understand the process of creating a semantic layer that merges data from disparate systems, enabling consolidated reporting across different business units without compromising data integrity.
Performance Insights: Caleb shares his experience with the performance of serverless SQL on Azure Data Lake, busting myths about query execution times and handling large datasets efficiently.
Looking Ahead: Brick and Caleb discuss the features they're waiting on within Microsoft's Fabric OneLake before transitioning from Azure Data Lake.

Click here to watch this episode on our YouTube channel.

Blue Margin increases enterprise value for PE-backed, mid-market companies by serving as their fractional data team. We advise on, build, and manage data platforms. Our strategy, proven with over 300 companies to-date, expands multiples through data transformation, as presented in our book, The Dashboard Effect.

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