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101 Ways to Sabotage Your Predictive Analytics Project  

And there is the first five here. Interesting Read, I liked it.

The strategic approach and project design for predictive analytics is substantially different than the other areas of business intelligence. Unlike a data warehouse design, which is similar to an engineering project, predictive analytics and data mining are a discovery process. And while several consortiums have standardized formal processes to accommodate discovery and iterative process, the practice remains riddled with common pitfalls.

Those who make the effort to educate themselves on the industry-standard approach to predictive analytics are nearly assured to reap residual returns – long before their counterparts who typically rush to acquire a tool and dive headlong into the data.

The article has

9 responses

Written by Guru Kirthigavasan

May 18th, 2010 at 6:22 pm

9 Responses to '101 Ways to Sabotage Your Predictive Analytics Project'

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  1. I liked it. good read


    8 Jun 10 at 5:28 am

  2. As I see it, most “ordinary” business intelligence projects would also benefit from a more experimental development approach.

    However, the reason is slightly different.

    In many organizations there is a lack of experience and skills withing business intelligence. Thus, making some small prototypes fast will increase the learning curve drastically and ensure a better design and architecture in the end.

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    7 Jul 10 at 7:37 pm

  4. very nice & knowledgeable article…must read to two time…


    8 Jul 10 at 3:37 am

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    12 Jul 10 at 2:23 am

  6. The Secret to Predictive Analytics is the star schema turned inside out. Leave the data in the transactional systems. Turn the fact table into an RDF triple store that contains an integrated set of RDF patterns linking the KEY predictive TAGS from each of the transactional systems. You need a harmonized vocabulary, thus the role of Master Data Management. You should only need about 14 – 21 concepts and six levels of weights and ranks to get the computational facets you need to discover historical patterns, map those to current state patterns, and extend the results to future probabilities using SPARQL patterns with known constraints. Predicting the future is quite easy when you understand the semantics of human cognitive models.

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    29 Aug 10 at 6:24 am

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  9. I have found it’s not the paralysis of misjudging the strategic implementation, but the rush of miscalculating the tactical approach that kills most data mining implementations before they begin. And it’s an costly mistake because it leaves the practitioners speculating why their models don’t make sense after having completed the procedure.

    I would love to run this article on my blog at

    I know a few business intelligence professionals who would love to comment a great deal on this topic.

    Robert Thomas

    30 Dec 10 at 8:01 am

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