Back to all glossary articles

Extract, Transform, Load (ETL)

Extract, Transform, Load (ETL) is a crucial data integration process that enables organizations to consolidate data from multiple sources into a unified data repository and derive actionable insights from them.

In the ETL process, data is extracted from various source systems, transformed to meet business requirements, and then loaded into a data warehouse for analysis and reporting. This flow is from operational systems to a centralized data repository. The primary goal of ETL is to consolidate and prepare data for analysis by transforming it into a structured format suitable for reporting and business intelligence.

Another process is Reverse ETL, which involves extracting data from a data warehouse and loading it back into operational systems or applications. This process pushes data downstream to where businesses can leverage analytical insights in real time.

Learn more:

  • 4 ways to make your analytics HIPAA-compliant: Implementation guide

    Healthcare organizations have four main approaches to achieving HIPAA-compliant analytics. Each has different trade-offs in cost, technical complexity, and analytics capabilities. This guide compares all four implementation methods – from using Google Analytics with workarounds to deploying fully HIPAA-compliant analytics platforms – so you can choose the right approach for your organization’s needs and resources.

  • Is Google Analytics HIPAA-compliant?

    If you use Google Analytics or similar software, you’re likely already optimizing your website to serve your customers better. But what about Google Analytics and HIPAA compliance? In short – if you’re a HIPAA-covered entity, using GA4 puts you at serious risk of a HIPAA breach. Google states that Google Analytics doesn’t satisfy HIPAA requirements. And…

Other definitions

Recent posts from Piwik PRO blog