Data is the new oil — pretty sure you have heard that like a million times by now. But it’s true — the information is, indeed, among the most precious commodities in the world. This truth, in turn, has put the focus on technologies, tools, and resources that enable entities across the globe to make the most efficient use of what can practically be described as gold mines of data. It is why ETL has gained so much favor with stakeholders across the entire ecosystem. If you are wondering, well what is ETL? Allow us to explain.
Short for Extract, Transform, Load, ETL is a strategy comprised of a three-step process that enables one to, first, Extract data from a variety of sources, such as JSON, XML, RDBMS, and more with the use of minimal resources. During this phase, it is imperative that the source system’s performance and response time. Then comes the Transformation of this data into a uniform format to facilitate analysis. To ‘transform’ this data, companies make use of a variety of business rules. And, finally, loading said it into a data warehouse. There are two ways to go about it, by the way: Full Load and Incremental Load.
But don’t rush to implement ETL for your organization just yet. We have compiled a list of some factors that are vital to the successful implementation of ETL. Be sure to keep these in mind.
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Get an idea of the data volume: One of the most crucial aspects of implementing an ETL tool is the volume of data that it will handle. And to help you make the right choice, it is essential you have a clear idea too; so, analyze if you will need data to be extracted from a single source or several of them. Understanding this will allow you to make an informed decision about which tool will best suit your business’ requirements.
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What do you expect from the ETL tool?: We are not referring to the process of ETL; we are relating to the company’s expectations from the instrument. In addition to the source systems, you must also know and understand the type of data the ETL tool will need to work with, as well as the ultimate goal of implementing ETL. It, again, will go a long way in helping you choose the right tool.
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Incremental data is critical: Since data warehouses are comprised of massive tables, it becomes impossible to refresh them through each ETL run. However, when you use incremental data, you can easily ensure that the most recent updates are included in the process. It is of considerable importance in ETL because the problem arising out of even one missed update can prove to be very expensive to fix.
Admittedly, ETL and its implementation can seem a bit overwhelming at first. But an expert service provider can not only skillfully walk you through the intricacies of the process but also lend quality assistance with migrating your data and everything else that your business may need in this regard.
