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发布于 : Oct 22, 2012
不在本期内容中
这一条目不在当前版本的技术雷达中。如果它出现在最近几期中，那么它很有可能仍然具有相关参考价值。如果这一条目出现在更早的雷达中，那么它很有可能已经不再具有相关性，我们的评估将不再适用于当下。很遗憾我们没有足够的带宽来持续评估以往的雷达内容。
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Oct 2012
Adopt
我们强烈建议业界采用这些技术，我们将会在任何合适的项目中使用它们。
Machine learning, semantic analysis, text mining, quantitative analytics, and other advanced analytics techniques have steadily matured over the past 15 years. They offer incredible potential for prediction, forecasting, identifying repeatable patterns, and providing insight into unstructured data. Historically, our ability to store and rapidly analyze large amounts of audio, video and image data has been severely limited. This placed constraints on sample size, as well as the time it would take to validate analytical models and put them into production. Now, using a spectrum of new technologies like NoSQL, data harvesters, MapReduce frameworks, and clusters of shared-nothing commodity servers, we have the power necessary to make truly effective use of these techniques. Combined with the massive increase in global data available from sensors, mobile devices and social media and we see this as a field with tremendous opportunity.
