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Wikibon offers 12-point evaluation framework for big data
Companies are abandoning big data projects because of the complexity of the technology, even when outcomes are well-chosen, writes Wikibon Chief Research Officer Peter Burris. Vendors are rushing to fill holes in toolkits, but often they seem more focused on improving the productivity of individual tools rather than aligning them with a holistic vision of how the toolkits should work.
- Typical errors include:
- Misplaced faith in ease-of-procurement as a harbinger of success;
- A tendency to evaluate piece parts rather than integrated wholes; and
- Widespread discounting of the value of packaging, which can provide real returns in simplification.
Burris discusses these errors in depth and provides 12 criteria for evaluation ranging from price to longer-term operational costs. The methodology is based upon Wikibon research and is designed to help big data teams make more strategic decisions about the technologies they choose.
Wikibon Premium users can read the full analysis here. To learn about subscribing, look here.
Image courtesy FirstMark Capital
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