Summary
To recap, data pipelines in Azure are a set of tools and services that allows for the efficient movement and transformation of data. One of the concepts covered in the chapter is the difference between ETL and ELT pipelines. In this book, we will focus mostly on ETL. The chapter also covered the differences between data pipelines in ADF and data pipelines in Azure Synapse Analytics.
We described various tools and technologies available for data transformation in Azure, including mapping data flows, Spark notebooks, SQL scripts, and SSIS packages for batch processing, and Azure Stream Analytics and Azure Databricks for real-time processing.
Next, we looked at an example architecture for both batch and stream processing, providing a high-level overview of the components and technologies involved. Later parts of the architecture remain abstract for now. We introduced a holistic flowchart to map the decision-making process when choosing one of the transformation tools discussed...