Data integration is the process of merging data from multiple sources into a single, coherent whole. In the context of data analytics, data integration is often used to bring together data from different systems and technologies to provide a unified view of the available data. This can mean, for example, extracting, transforming and/or converting data from different sources, and then storing it in a central storage point, such as a
datalake.
Not all data needed for a specific business process is generated in the system that primarily supports that process. This requires links between different databases and the determination of which data is the correct and thus leading. Also, the same type of data occurs in different databases. Data integration focuses on linking between data sources and unambiguity of data.
The purpose of data integration in the context of data analytics is to make it easier for data analysts to access and work with data from multiple sources, and to enable them to gain a more complete understanding of the data.
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