ETL By Any Other Name Is Still A Challenge, And Machine Learning Can Identify And Manage The Metadata

Extraction, transformation and load (ETL) became a familiar concept in the 1990s, when data warehousing became a well known business intelligence (BI) concept. The advent of the web, and the vast volume of data took many organizations' focus away from ETL to data lakes. Too many people disparaged ETL as a tool of the past. However, as IT has always been aware, data lakes aren't a solution all to themselves and rebranding to ELT doesn't change the fact that there are now far more sources and targets than there ever were. Data movement is still a complex problem and metadata management (MDM), and it's a problem becoming even more challenging as regulatory requirements for privacy mean data must be better tracked and controlled.