ETL too slow? Constantly breaking? Find out how to use Hadoop to fix your ETL while avoiding the landmines.
Companies traditionally have approached ETL (Extract, Transform and Load) with a set-it-and-forget-it mentality. Prior to big data this was OK, but as some organizations are discovering, that approach needs to change because the data pipeline itself is becoming more complex both in terms of sources and in terms of destinations for that data. Rapidly growing data volume and variety demand a more fluid ETL process. By transforming the ETL process, organizations can improve data quality, data recency, and data availability.
In this Webinar, we will discuss:
Presenter: Rich Reimer, VP of Product
Management for Splice Machine