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Five Pitfalls That Can Derail Your Big Data Project

  • Five Pitfalls That Can Derail Your Big Data Project-

    Big Data is large – and small. It’s extremely diverse in origin, in style, in consistency and in quality. Some organizations in certain industries are dealing with massive data volumes, while others have much smaller data sets to exploit, but might have a broader variety of sources and formats. Make sure you go after the “right” data: Identify all the sources that are relevant, and don’t be embarrassed if you don’t need to scale your data computing cluster to hundreds of nodes right away!

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Five Pitfalls That Can Derail Your Big Data Project

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  • Five Pitfalls That Can Derail Your Big Data Project-2

    Big Data is large – and small. It’s extremely diverse in origin, in style, in consistency and in quality. Some organizations in certain industries are dealing with massive data volumes, while others have much smaller data sets to exploit, but might have a broader variety of sources and formats. Make sure you go after the “right” data: Identify all the sources that are relevant, and don’t be embarrassed if you don’t need to scale your data computing cluster to hundreds of nodes right away!

Most organizations are still in the early stages of Big Data adoption, and few have thought beyond the technology angle of how Big Data will profoundly impact their processes and their information architecture. Whether Big Data projects are past the pilot stage and being deployed in production, or still on the horizon, they require strategic thinking and adequate planning to avoid some now-typical pitfalls that tend to get in the way of success for big data projects.

Talend recently identified five key areas companies should monitor to avoid pitfalls that can derail big data projects, and ensure those projects generate value as they move past the early pilot stages.