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Big Data Use-Case: ETL made easy

This Big Data use-case involves a Global Fortune 100. The company is interested in rethinking how they manage the many disparate billing systems and data marts which IT  supports within its multiple divisions. The data from the systems is provided in multiple formats including: flat files, feeds, and SQL extracts.

Question: So what’s the issue? Why not just use IBM’s Datastage and SQL in Teradata?

Answer: Maybe because it’s expensive? And using the Teradata DBMS to perform some of the data manipulation is inefficient. Teradata is meant to be focused on decision support, not ETL.

This is where Hadoop can provide a very cost-effective ETL platform which manages all aspects of data integration while still addressing requirements in scalability and usability.

Think about it.

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Continuing the Discussion

  1. Big Data is Thriving. Is RDBMS Dead? – Jim Kaskade linked to this post on December 3, 2011

    [...] routinely hear that Hadoop / MapReduce is being deployed in “data pipeline” use-cases (aka ETL). This makes sense because the canonical use of MR can be characterized in five [...]

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