Summary
In this chapter, we’ve reviewed a number of common transformations that can be applied to raw datasets, covering both generic transformations used to optimize data for analytics and business transforms to enrich and denormalize datasets.
This chapter built on previous chapters in this book. We started by looking at how to architect a data pipeline, then reviewed ways to ingest different data types into a data lake, and in this chapter, we reviewed common data transformations.
In the next chapter, we will look at common types of data consumers and learn more about how different data consumers want to access data in different ways, and with different tools.
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