![]() ![]() If we want to perform high-speed, sophisticated analytics and intelligence on all of our data, the cloud is the only place to do it. However, the introduction of Cloud Computing revolutionized the way we looked at data storage and processing forever. Data was stored and transformed primarily in on-premises data warehouses until the end of the 20th century. #Extract transform load softwareAs the amount of data grew, data warehouses grew, and ETL software tools proliferated and became more sophisticated. Granted, the amount of data they handled was modest by today’s standards. The first ETL tools were primitive, but they got the job done. Early adopters needed a way to “extract” data from siloed systems, “transform” it into the destination format, and “load” it. LOAD - the data into the target system or databaseĪs the databases grew in popularity in the 1970s, ETL was introduced as a process for integrating and loading data for computation and analysis, eventually becoming the primary method to process data for data warehousing projects.TRANSFORM - data by cleaning it up, combining it, removing redundancy, and getting it ready for the next step i.e.EXTRACT - the data from its source, could be an application or another database.It comes into the picture when you have basically data coming from a number of sources into a centralized database or system. ETL stands for Extract, Transform and Load. ![]()
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