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Azure Data and AI Architect Handbook
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As datasets continue to grow in size and complexity, it is increasingly important to have efficient ways of manipulating and processing this data. We will cover both batch and real-time transformation options.
For batch transformations, we will discuss the use of the following:
These tools can be used for shaping and cleaning large datasets and allow you to define complex data transformations using a visual interface or programming language, making it easy to handle even the most challenging data manipulation tasks.
For real-time transformations, we will look at the following:
Both technologies allow you to process data with remarkably low latency, enabling real-time insights and decision-making. With these tools, you can process data streams from various sources in real time, transforming and analyzing the data as...
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