As data grows in the enterprise database, the need for data to be consolidated is imperative to effectively manage it and use it for business operations. Data consolidation is 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 data integration modules that included data federation and propagation.
Data propagation deals with the duplication of information from different sources and locations, while data federation deals with unifying source information virtually. When data is integrated into a single database, it enables 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 it is loaded into a database. Once the upload process is complete, it is transformed and then delivered to different tables that can be accessed by authorized users. This technology is also called extraction systems because it is performed by any individual on demand. This also allows users to transform and publish data after it is loaded into 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 resources, transform it into standard rules, and then upload it to target systems with specific formats. It is quite different from ELT, because the data is transformed first before the loading process takes place. The transformation takes place in the form of reformatting, standardization and simplification of other data manipulation rules established by the company.
The extraction process is the first stage in any data consolidation technique. Extraction can take place from a large volume to multiple data sources or perhaps from relational databases to object databases and other documents. This can also provide structured and unstructured data. The next technique is the transformation process that varies from the data consolidation technique that is available. This can also range from simple to complex operations. This also allows the delivery of timely and relevant information that is used by the management team in their 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 uploaded data is not processed while in ETL the data is loaded after processing.
Data consolidation is done 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.
