Data Integration
You may remember from the previous chapters that we separated data integration from other integration use cases covered under cloud integration. Since data integration differs from the process integration style, the patterns and tools used for these two categories are distinct.
With data integration, we bring together data from different sources so that the combined data has a meaning for a specific purpose. This may be for operational requirements; however, it is mostly for analytics and reporting purposes such as producing business insights or replicating data into a data warehouse. Data integration is also naturally relevant to big data and artificial intelligence (AI)/machine learning (ML) use cases.
As you can remember, we covered master data integration in the previous chapter because its patterns and motivations are more akin to the process integration style.
We will cover the following topics in this chapter:
- Why do we need data integration...
