Five Pitfalls to Avoid with Hadoop

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Tips to avoid this pitfall:

ETL is emerging as the key use case for Hadoop implementations. However, Hadoop alone lacks many attributes needed for successful ETL deployments. Therefore, it’s important to choose a data integration tool that can fill the ETL gaps.

  • Choose a user-friendly graphical interface to easily build ETL jobs without writing MapReduce code.
  • Ensure that the solution has a large library of pre-built data integration functions that can be easily reused.
  • Include a metadata repository to enable re-use of developments, as well as data lineage tracking.
  • Select a tool with a wide variety of connectors to source and target systems.

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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