Summary

This chapter looked at a growing capability in the cloud, especially in Azure—data integration and analytics.

Azure provides a range of tools for creating end-to-end data pipelines for storing, ingesting, transforming, aggregating, and analyzing data. So, we started the chapter with a high-level view of what a typical pipeline might look like.

We looked at how to configure Azure Storage to use ADLS Gen2, what extra capabilities this gives you, and how Azure Data Factory can create automated and secure pipelines for data loading and transformation.

Finally, we looked at the two primary tools for exploring and analyzing data with Azure: Azure Databricks and Azure Synapse Analytics.

After reading this chapter, you should have a better understanding of the different components that comprise a data analytics solution, including the strengths of each service and where one might be a better choice over another.

In the next chapter, we conclude Part 4, Applications...