December 2025
Beginner
336 pages
9h 53m
English
Content preview from Azure Data Fundamentals
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Chapter 3. Understanding Data Workloads
The shift to cloud computing has both changed where we store data and transformed how we process it. As organizations migrate their data operations to Azure, traditional approaches to handling transactions and analytics have developed dramatically. Understanding the difference between transactional and analytical workloads—and knowing how to design systems that support each effectively—is crucial for anyone working with Azure’s data platform and is essential for the DP-900 exam.
The distinction between transactional and analytical workloads is more than just academic. It drives real-world decisions about database selection, infrastructure design, application architecture, and operational procedures. For instance, Azure SQL Database excels at transactional processing, while Azure Synapse Analytics is optimized for analytical workloads. A system optimized for processing individual customer orders operates differently from one designed to analyze sales trends across millions of transactions. Getting this distinction wrong can cause poor performance, excessive costs, frustrated users, and missed business opportunities.
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