Data Consolidation Techniques

As data increases in the company’s database, the need for data to be consolidated is a must in order to manage it effectively and utilize it for business operations. Data consolidation is getting data from multiple locations and sources and integrating them into a single database to be used in the company. Consolidation is an important component in data integration modules that comprise data propagation and federation.

Data propagation deals with duplicating information from different sources and locations while data federation deals with unifying the source information virtually. When data is integrated into a single database it allows for quicker access and better control. Managing data is now more effective and efficient. Data consolidation is done with the use of two different technologies and these are the ELT and ETL.

ELT stands for Extract, Load, and Transform. This is where the systems transform a volume of data after it is loaded in a database. After the loading process is done, it is then transformed and then delivered to different tables that can be access by authorized users. This technology is also called pull systems because it is performed on-demand by any individual. This allows also the users to transform and publish data after it is loaded in the database.

On the other hand, ETL stands for Extract, Transform, and Load. This is another data consolidation technique where it extracts information from multiple resources, transforms it into the standard rules and then loads it afterwards in the target systems with specified formats. It is quite different from ELT, because data is being transformed first before loading process takes place. Transformation takes place in the form of reformatting, standardizing and streamlining it to other data manipulation rules set by the company.

The extraction process is the first stage in any data consolidation techniques. Extraction may take place from high volume to multiple data sources or maybe from relational to object databases and other documents. This may also delivers both unstructured and structured data. The next technique is the transformation process that varies from data consolidation technique that is available. This may also ranges from single to complex operations. This allows also to deliver timely and relevant information that are used by the management team in their decision making process. Data is customized and tailored to what the company really needs. And the last process is the loading where it transfers and delivers data from one location to any target application. The loading process differs in both techniques because in ELT data loaded is unprocessed while in ETL data is loaded after it is processed.

Data consolidation is done with two different techniques. However, both of these techniques aim to integrate all the necessary data and information from different sources to a single database for effective management of data.

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