Every data integration pipeline consists of 3 stages: Data Extraction (E), Data Transformation (T) and Data Load (L) During the Data Extraction stage, the source data is read from its origins: transactional databases, CRM or ERP systems or through data scraping from web pages. During the Data Transformation stage, the necessary modifications are applied to the source data. This includes data filtering, enrichment or merging with existing or other source datasets, data obfuscation, dataset structure alignment or validation, fields renaming and data structuring, according to the canonical data warehouse model. During the Data Loading stage, the data is stored in the pipeline destination, which could be a staging area, data lake or data warehouse. There are two principal methods for the data integration process: transferring it from where it originated to the destination, where the data will be used for analysis, ETL and ELT. The difference between ETL and ELT pipelines...
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