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Big data is driving the need for high-performance analytics, and this capability is enabled by key technologies such as Hadoop. What is Hadoop and why is it important?

  • Hadoop is a distributed storage platform leveraging inexpensive hardware with the high-availability data protection inherent in the Hadoop Distributed File System (HDFS). On average, Hadoop storage costs are dramatically less expensive than traditional SAN storage.
  • Hadoop is a massively scalable, distributed processing platform that can divide and conquer large computational tasks. As such, Hadoop is easily able to perform work that would bury a traditional ETL process or system.
  • Hadoop is extremely flexible in that it can store and process a wide variety of data types including photos, videos, and documents – in other words, unstructured data.

These characteristics have positioned Hadoop as the de facto platform upon which to perform higher-level analytics. As a result, enterprise software companies are rapidly releasing Hadoop connectors for their products. These connectors enable the software to move data into and out of Hadoop storage as well as offload large computational tasks.

The following principles have enabled HPT engineers to repeatedly deliver successful Hadoop implementations:

  • Formation of well-developed use cases
  • Continuous interaction with enterprise architecture teams as new standards are created
  • Building in security from the beginning, as opposed to bolting it on at the end
  • Engineering at-scale manageability and maintainability into the design
  • Implementing analytic solutions that enable customers to visualize their Hadoop data and discover strategic insights

Leverage HPT and Hadoop to dramatically lower your storage costs and create a high-performance platform to explore your strategic data. Contact to begin today.