Big data implementations in finance

Before any big data project is kicked off, just like any other project, there are certain prerequisites for it to be successful:

  • Business requirements: Work with business users to understand their requirements—the problems with the current data systems, new sources, and possible opportunities. We need to have the big data problem defined.
  • Gap analysis: Understand the current and future state and list down all gaps—changes to data interfaces, data governance, data architecture, data visualization, and so on.
  • Project plan: Details on the business, big data, and technical architectures, including resource requirements and clear return on investment calculations.

The key challenges

As Hadoop is a new technology, its ...

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