Whitepaper: Five best practices for maximising big data ROI

Organisations of all kinds have begun to capitalise on the tremendous opportunities presented by big data. Consider these examples:

  • eHarmony’s big data infrastructure investment processes 30GB of data every day to help 20 million registered users find the relationship they seek.
  • FleetRisk Advisors gleans predictive insights from 4,500 operational parameters to help customers reduce minor accidents by 20 percent and major accidents by 80 percent.
  • Visa International performs analytics on 20,000 transactions per second to avoid $1.5 billion in fraud losses.
  • SUNY Buffalo examines more than 2,000 genetic and environmental factors in just minutes to develop breakthrough therapies and prevention strategies for multiple sclerosis (MS).

How can other organisations achieve these kinds of results? And how can they ensure the maximum return on their investment in big data capabilities? The answer to this question is complex — and will vary considerably among organisations, given differences in their strategic objectives and existing IT resources. The experiences of successful early adopters, however, reveal best practices that can significantly contribute to higher big data ROI.

1. Be Smart About Infrastructure Decisions

Organisations starting out on their big data journey often focus first on the data science issues associated with analytics and reporting. Ultimately, those analytics and reports will deliver value to the organisation through actionable insights, so it may seem logical to begin by figuring out which data sets should be included in the big data initiative and what kind of insight might be gained from them. But experienced big data adopters know that it’s as important to make the right infrastructure investments as it is to ask the right data science questions.

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