Introduction

Hadoop helps organizations make decisions based on a comprehensive analysis of various variables and data sets. This data processing is commonly used to support better decision making, provide real-time monitoring for a lot of things like hardware conditions, threat levels, transaction volumes, and a lot more, also enables predictive and proactive activity.

The ability to process large and complex data gives users a more comprehensive view of their clients, operations, opportunities, risks, etc. To develop a similar perspective without big data, organizations would need to conduct multiple, limited data analyses then find a way to synthesize the results, which would likely involve a lot of manual effort and subjective analysis.

Here are some other benefits to using Hadoop

  • 1 Advanced data analysis can be done in-house

  • 2 Run a commodity vs. custom architecture
  • 3 Keeping operations in-house helps organizations be more accessible, while also avoiding the ongoing operational expense of outsourcing.
  • 4 Hadoop makes it practical to work with large data and customize outcomes without having to outsource specialized service providers.
  • 5 It enables organizations to take full advantage of all their data – structured and unstructured, real-time and historical. Leveraging adds more value to the data itself and improves the return on investment (ROI) for the legacy systems used to collect, process, and store the data, including ERP and CRM systems, social media programs, sensors, industrial automation systems, etc.
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