ETL Process: How You Can Design And Implement It Effectively

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ETL Process: How You Can Design And Implement It Effectively

Implement and design ETL fast and effectively.

· Big Data Zone ·
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 Extract, Transform, and Load, commonly referred to as ETL, alludes to a process wherein data is transferred between two locations. However, that’s a rather simplistic view of what is admittedly a rather elaborate and equally complicated process. ETL is much more than the migration of data from one database to another — it also includes transforming databases into a uniform format to ensure that they can be adequately leveraged wherever required. What purpose does this serve, you ask. The answer is that it helps a business perform so many activities.

You may also like: Things to Understand Before Implementing ETL Tools.

Nonetheless, the primary goal of the ETL process is to glean value from data. The amount thus gained from data takes various forms — insights, analytics, reports, which, in turn, drive several functions across a business’ operations, though the primary focus is smart business decisions. However, as mentioned above, ETL is a rather complicated process, which means, it must be not only designed also but adequately implemented suitably. So, here’s a collection of some handy tips to help you ensure that you design and implement ETL in the right way.

  1. Know and understand your sources of data: This is the first thing that anyone who is working to implement ETL must ensure — the proper understanding of both the variety of references as well as types of data. It will help you better gauge your business’ needs and also determine the data volume the solution will have to contend with.

  2. Don’t forget to streamline the solution: Just because the system is a go and the business is now able to use basic functionalities offered by the ETL solution doesn’t mean the job is done. After setting up basic features, the company must then focus on further enhancing the process in the context of memory consumption and performance. You can undertake additional testing of various environments as well as data sizes to identify any opportunities for improvement in the process and solution.

  3. Logging errors is crucial: While mistakes are regrettable, the fact remains that they are a natural and unavoidable part of the process. Moreover, instead of freezing over the fact that they occurred, it would be wiser to use them to your advantage. So, make sure that you have a robust logging and alert system in place to ensure that any interruptions can be avoided in the future. Also remember, the error logs must include error descriptions, execution time, and more.

  4. There’s a unit testing tool: The process of unit testing is critical in the overall scheme of things since it isn’t suitable for standard UI validation. One must not forget that unit testing’s substantially technical validation necessitates access to backend data sources along with aptitude in the query as well as data analysis tooling.

However, before you embark on the path of adapting ETL, it is highly recommended that you thoroughly research and understand the process and its many aspects, including using Talend for data integration. It will help accelerate the process when you finally do get started with it.

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big data ,data integration ,etl ,etl tool ,unit testing

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