2. Data Integration

Data Integration is a data preprocessing technique that combines data from multiple sources such as databases (relational and non-relational), data cubes, files, etc., and provides users a unified view of these data. It gives a complete picture of key performance indicators (KPIs), customer journeys, market opportunities, etc.

Data Integration [1]

The data sources can be homogeneous or heterogeneous. The data obtained from the sources can be structured, unstructured, or semi-structured in format.

In data integration, we talk about combining data from multiple sources, and you might be wondering what data we mean. Well, modern companies – even those that are smaller in size – have adopted numerous digital tools to assist them in their day-to-day operations. These can range from marketing and sales tools to logistics and transactional processing tools, even a small team with basic operational needs uses multiple tools; all of these tools create data that without integration processes will result in detrimental data silos

There are mainly 2 major approaches for data integration :

1. Tight Coupling:

  • Here, a data warehouse is treated as an information retrieval component.
  • In this coupling, data is combined from different sources into a single physical location through the process of ETL – Extraction, Transformation, and Loading.

2. Loose Coupling:  

  • Here, an interface is provided that takes the query from the user, transforms it in a way the source database can understand, and then sends the query directly to the source database to obtain the result.
  • And the data only remains in the actual source databases.


1] https://www.alibabacloud.com/blog/what-is-data-integration-in-analytics_596500

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