![]() Data engineers are often incredibly competent at using different programming languages such as Python and Java. In addition, these extraction scripts also involve considerable maintenance since APIs change relatively often. Because making and automating these API calls gets harder as data sources and data volume grows, this method of extraction often requires strong technical skills. To actually get this data, data engineers may write custom scripts that make Application Programming Interface (API) calls to extract all the relevant data. ![]() Ad platforms (Facebook Ads, Google Ads, etc.).Some examples of these data sources include: Data that is extracted at this stage is likely going to be eventually used by end business users to make decisions. In this first step, data is extracted from different data sources. We’ll go into greater depth for all three steps below. In an ETL process, data is first extracted from a source, transformed, and then loaded into a target data platform. If you don’t talk about the benefits and drawbacks of systems, how can you expect to improve them? How ETL works It’s important to talk about ETL and understand how it works, where it provides value, and how it can hold people back. The same transformations can occur in both ETL and ELT workflows, the primary difference is when (inside or outside the primary ETL workflow) and where the data is transformed (ETL platform/BI tool/data warehouse). In many ways, the ETL workflow could have been renamed the ETLT workflow, because a considerable portion of meaningful data transformations happen outside the data pipeline. In ETL workflows, much of the meaningful data transformation occurs outside this primary pipeline in a downstream business intelligence (BI) platform.ĮTL is contrasted with the newer ELT (Extract, Load, Transform) workflow, where transformation occurs after data has been loaded into the target data warehouse. ETL, or “Extract, Transform, Load”, is the process of first extracting data from a data source, transforming it, and then loading it into a target data warehouse.
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