Some feel asking attorneys to add predictive coding tools to their technology tool belt is like asking them to fly jet airplanes instead of drive cars.

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Not surprisingly, early generation predictive coding tools are far more complex and difficult to use than traditional legal technology tools such as keyword search, concept search, email threading, and data clustering to name a few.

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The process is messy and time consuming with its different program coding platforms and various developmental tools, when with Android or the Apple OS there is just a simple developers kit.

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However, the industry should demand that predictive coding providers include enough transparency into their tools so both parties can evaluate the soundness of the underlying statistical approach being applied.

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Yet, power users almost always want to get to the lowest level their tools will allow, which usually involves some form of coding.

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Their options range from using online app-building tools, to taking crash courses in computer programming and coding languages, hiring a costly professional on contract, or recruiting a full-time developer.

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Data science can create value by getting tools such as R and Hadoop into common parlance, making coding something that subject matter experts desire to learn in order to communicate effectively with data scientist colleagues.

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If the coding masses see this as the future, it could be as big a deal for BEA as better development tools were for Microsoft (nasdaq: MSFT - news - people )--the kind of thing that establishes industry wide dominance.

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