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Unstructured Data Analytics Shouldn’t Be Such a Mess

The lesson here is that data governance is the necessary foundation of all successful data analysis. The statistics axiom of “garbage in, garbage out” is used ad nauseam for a reason: because it’s accurate and timelessly relevant.

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By Kon Leong

The problem with searching for a needle in a haystack is that the process, by nature, is inefficient. So why has it become a popular analogy for analytics efforts within the enterprise? Because today’s analytics attempts – particularly for unstructured human data – are typically a mess.

Today’s analytics are often ad hoc and rely on incomplete or skewed sample sets. They commonly focus on only one narrowly-defined data type. So for each glimmering “needle” of insight, it seems that heaps of data are scattered and cast aside, often at the cost of subsequent business efficiency.

When it comes to business content such as files, email, social media, IMs, calendar entries, images, and more, firms are failing to extract meaningful insight despite the potential wealth of information contained within.

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