creating a log for ETL audit and compliance.data loading from one platform to another via a centralized point.automation of data updates at certain times or triggers.IT teams leverage workload automation tools and job schedulers to automate the triggering and execution of ETL tasks in order to minimize human intervention and errors. Since then, the necessary technologies have evolved tremendously and currently give us levels of insight and intelligence not previously thought possible. With the arrival of data warehouses in the 1980’s and 1990’s, the popularity of ETL tools exploded, leading many businesses to have multiple, disparate ETL solutions. This process is integral to business intelligence because it means that data from multiple sources can be brought together in a manner that provides important insights regardless of the original format or location. To be successful in this endeavor, it is key to begin with data mapping where the relationship between the source establishes instructions for how data is to be transformed prior to arriving in the designated location.ĮTL has been around for many years, but gained prominence in the 1970’s because of a growing need to store different varieties of business information. Load: When the data is written into the target database or data warehouse.Creating surrogate keys that are new values applied to similar data from different source systems.Transposing, usually via denormalizing and reorganizing into a dimensional model to optimize reporting.Cleansing through validity checks to remove or modify problematic data.Standardization to a consistent set of lookup values.Transform: Converting recently extracted data into the correct form so that it can be placed into another database.This process is crucial to ensuring data from one database or application can be utilized by other applications and databases.At this point, the data is often from multiple and different types of sources Extract: Collecting data from a database.In addition to migrating data from one database to another, it also converts (transforms) databases into a single format that can be utilized in the final destination. What Exactly is ETL?ĮTL stands for Extract, Transform, and Load, and refers to the process of transferring data from one location to another. For industries that manage large amounts of data, often from disparate sources, ETL can be impactful. Data can then be used for a wide range of analysis, intelligence, and reporting functions. ETL is one key processes needed to extract value out of data.
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