Webcast Recap: Top Strategies for Successful Big Data Projects

25% of IT projects are canceled before completion. More than double that, 62% of IT projects are considered “failed” because although they weren’t canceled, they faced severe budget overruns, failure to deliver business value, and many other issues.

In a recent survey that Infochimps and SSWUG performed, we discovered that 44% of Big Data projects are canceled before completion. How many more are failing to meet project goals and objectives? 80%? 90%?

We uncovered the most common reasons Big Data projects fail:

Business Challenges:

  • Inaccurate scope
  • Non-cooperation between departments
  • Lack of talent / lack of expertise

Technical Challenges:

  • Technical or roll-out roadblocks
  • Gathering data from different sources
  • Understanding the tools, platforms, technologies, and vendors

Big Data projects can have such a transformative effect on business, from deeper business insights leading to new profit channels or products, to unifying and streamlining a fragmented, siloed enterprise data environment.

With all this in mind, based on our research and experience, we’re sharing our 7 Strategies for Successful Big Data Projects. These strategies have worked for Infochimps customers, and can work for any organization looking to successfully tackle their own Big Data project.

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For more details on the 7 Strategies for Successful Big Data Projects, watch our webcast recording here. >>

Have a story about a Big Data project of your own? Share it with us, and help us continue developing and advancing this framework!

Source: CNET





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