Transforming data on Azure
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:
- Mapping data flows
- Spark notebooks
- SQL scripts
- SSIS
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:
- Azure Stream Analytics
- Azure Databricks
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...
