Data integration vs ETL: What are the differences?

If you’re considering using a data integration platform to build your ETL process, you may be confused by the terms data integration vs. ETL. Here’s what you need to know about these two processes.

Businesses have a wealth of data at their disposal, but it is often spread out among different systems. This scenario makes it challenging to get a clear picture of what’s happening in the business.

That’s where data integration and ETL — or Extract, Transform and Load — come in to support greater data visibility and usability. Although these two concepts are closely related, data integration and ETL serve distinct purposes in the data management lifecycle.

Data integration is the process of providing users with a unified view of data that comes from multiple disparate sources. It follows different processes depending on the application. For example:

For data integration to be successful, it is crucial to understand what data is needed and where it is stored. Once this information has been gathered, the next step is determining how the various data sets can be brought together. This may involve using ETL tools or manual processes such as manual data entry or CSV file importation.

ETL is one of the simpler forms of data integration. It is a three-step process that is used to collect data from multiple sources, such as ERP systems, e-commerce platforms, legacy systems, CRM systems and other data sources. From these sources, ETL converts data into a format that a central system can use and then loads it into a data warehouse.

Data integration and ETL are closely related concepts. In fact, ETL can be thought of as a subset of data integration. This is because both processes involve combining data from multiple sources into a single repository.

However, it’s important to note that not all data integration solutions use ETL tools or concepts. In some cases, it’s possible to use alternative methods such as data replication, data virtualization, application programming interfaces or web services to combine data from multiple sources. It all depends on the specific needs of the organization if ETL will be the most useful form of data integration or not.

The main difference between data integration and ETL is that data integration is a broader process. It can be used for more than just moving data from one system to another.