Five Pitfalls to Avoid with Hadoop

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Tips to avoid this pitfall:

Without the right connectivity, Hadoop risks becoming another data silo within the enterprise. Tools to get the needed data in and out of Hadoop at the right time are critical to maximize the value of Big Data.

  • Select tools with a wide range of native connectors, particularly for popular relational databases, appliances, files and systems.
  • Don’t forget to include mainframe data in your Hadoop and Big Data strategies.
  • Make sure connectivity is provided not only from a stand-alone data integration server to Hadoop, but also directly from the Hadoop cluster itself to a variety of sources and targets.
  • Look for connectors that don’t require writing additional code.
  • Ensure high-performance connectivity in both loading and extracting data from various sources and targets.

The emergence of Hadoop as the de facto Big Data operating system has brought on a flurry of beliefs and expectations that are sometimes simply untrue. Organizations embarking on their Hadoop journey face multiple pitfalls that, if not proactively addressed, will lead to wasted time, runaway expenditures and performance bottlenecks. By proactively anticipating these issues and utilizing smarter tools, the full potential of Hadoop may be realized. Syncsort has identified five pitfalls that should be avoided with Hadoop.


Related Topics : Vulnerabilities and Patches, Resellers, Broadcom, Broadband Services, Supercomputing

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