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Graphic Guide to Offloading the Data Warehouse

Discover a no-coding approach to shift SQL ELT workloads to Hadoop

Several organizations are reaping the benefits of offloading ELT/ETL workloads to Hadoop.
But there’s a catch: Re-writing heavy ELT workloads, like complex data warehouse SQL processes to run in Hadoop usually takes highly-skilled Java, Hive or Pig programmers (if you can find them at all).
Not anymore. Learn a simple, graphical approach to offload ELT processing & data from your data warehouse to Hadoop – without writing a single line of Java, Hive or Pig! Our new how-to guide, complete with screen shots, walks you through:

  • Extracting source data from the data warehouse
  • Joining & sorting the source datasets using a MapReduce ETL job
  • Loading the final dataset into the data warehouse
  • Executing & scheduling your Hadoop ETL jobs
  • Monitoring Your Hadoop ETL Jobs