In the first post of a two-part series, Phil Simon plays point-counterpoint with himself.
Tag: ETL
Guest blogger Khari Villela says data lakes are not a cure-all – they're just one part of a comprehensive, strategic architecture.
Joyce Norris-Montanari discusses data engineers in the second of her two-part series.
In the extended enterprise, data integration challenges abound. David Loshin explains.
Clark Bradley explains how SAS can make Hadoop approachable and accessible.
Why they will still play a valuable role in organizational data-management and -integration efforts.
.@philsimon asks some fundamental questions about taking the next step with #bigdata.
The other day I was chatting with an ETL developer and he said he always pushes queries into the database instead of dragging data across the network. I thought “Hmm, I remember talking about those topics when I was a DBA.” I'd like to share those thoughts with you now.
There are many ways to do data integration. Those include: Extract, transform and load (ETL) – which moves and transforms data (with some redundancy) from a source to a target. While ETL can be implemented (somewhat) in real time, it is usually executed at intervals (15 minutes, 30 minutes, 1