Migrated from eDJGroupInc.com. Author: Barry Murphy. Published: 2013-06-25 07:30:56Format, images and links may no longer function correctly. 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 analyze 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 a issues such as dropped calls at any point in time and proactively contact the customer and deal with the problem.

  • A consumer products company creating granularly targeted marketing plans by forecasting how customers are going to respond in the future based on their past behaviors 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% of overall corporate information.  In other words, companies fail to leverage 80%-90% 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.

As a result, running analytics on unstructured content can be more complex than doing so on structured data.  That is why Big Data has a lopsided focus on structured data.  But, organizations are beginning to focus more on unstructured content and gaining valuable insight to what is in it in order to manage risk, cut costs, and increase revenue.  The huge volumes of unstructured content, though, will force organizations to leverage advanced tools to sift through the info, determine what is valuable or not, and help take action.  Just like Predictive Coding impacts the Legal Review process, so too can Predictive Information Governance give companies the ability to more effectively and efficiently find, access, secure, preserve, delete, or use information assets as needed.

eDJ’s new report, “Predictive Information Governance: The Time Has Come,” looks at how Predictive IG works and how it can positively impact multiple use-cases.  The report is available for ad hoc purchase or to eDJ research subscribers here, or you can download a complimentary copy of the report (thanks to Recommind) here.

Barry Murphy can be reached at barry@eDJGroupInc.com for offline comments or questions. His active research topics include information governance, Predictive Coding, and the impact of social media on eDiscovery.  Barry’s latest research report is Predictive Coding: What You Need To Know Now​.

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