Predictive information governance: the time has come
By Barry Murphy
Big data has become big business. The ever-rising volumes of digital data in the global corporate world create opportunities for companies to leverage information in ways never before possible. Leveraging information requires the ability to quickly and efficiently analyse it and understand what it means and how it can affect business decisions.
Examples abound of innovative uses of analytics to mine big data: a financial services company reducing the amount of time necessary to run market surveillance algorithms so that compliance officers can quickly spot questionable stock trading trends; a telecommunications provider quickly being able to combine data from a variety of sources — social media sites, call records, cell tower logs, etc — to see which customers are experiencing issues such as dropped calls at any point in time and to proactively contact the customer and deal with the problem; or a consumer products company creating granularly targeted marketing plans by forecasting how customers are going to respond in the future based on their past behaviours and their segmented demographics, as tracked and stored in a CRM system.
While these examples showcase the value of leveraging information to gain revenue and cuts, they only hit the tip of the iceberg. That is because big data to date has been focused almost solely on structured data — that which fits into the rows and columns of a database and is relatively simple to manipulate for the purposes of analysis. But even conservative estimates are that structured data makes up no more than 15–20 per cent of overall corporate information. In other words, companies fail to leverage 80–90 per cent of the information stored in various repositories. This other information — unstructured content — does not fit easily into a traditional database; rather, content is typically stored in some kind of a file system or repository and the metadata about the file is stored in a relational database…
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