- December 9, 2012
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:
- Inaccurate scope
- Non-cooperation between departments
- Lack of talent / lack of expertise
- 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.