As the data in the company’s database increases, the need to consolidate the data is imperative to manage it effectively and use it for business operations. Data consolidation is about getting data from multiple locations and sources and integrating it into a single database for use across the business. Consolidation is an important component in the data integration modules that includes data propagation and federation.
Data propagation deals with the duplication of information from different sources and locations, while data federation deals with virtually unifying source information. When data is integrated into a single database, it allows faster access and better control. Data management is now more effective and efficient. Data consolidation is done with the use of two different technologies and these are ELT and ETL.
ELT stands for Extract, Load and Transform. This is where systems transform a volume of data after loading it into a database. Once the upload process is done, it is transformed and then delivered to different tables that can be accessed by authorized users. This technology is also called pull systems because any individual performs it on demand. This also allows users to transform and publish data after uploading it to the database.
On the other hand, ETL stands for Extract, Transform, and Load. This is another data consolidation technique where you pull information from multiple sources, transform it into standard rules, and then load it into target systems in specific formats. It is quite different from ELT, because the data is first transformed before the upload process takes place. The transformation takes place in the form of reformatting, standardization and simplification to other data manipulation rules established by the company.
The extraction process is the first stage in any data consolidation technique. The extraction can take place from a large volume to multiple data sources or perhaps from relational databases to databases of objects and other documents. This can also deliver structured and unstructured data. The next technique is the transformation process which varies from the available data consolidation technique. This can also range from simple operations to complex operations. This also makes it possible to deliver timely and relevant information that is used by the management team in its decision-making process. The data is personalized and adapted to what the company really needs. And the last process is upload, where you transfer and deliver data from one location to any destination application. The loading process differs in both techniques because in ELT the loaded data is not processed, while in ETL the data is loaded after it is processed.
Data consolidation is performed with two different techniques. However, both techniques aim to integrate all the necessary data and information from different sources into a single database for effective data management.