Content Analytics

What is Content Analytics?

Content analytics is a language-based approach to methodically narrow down extremely large volumes of unstructured (text-based) data and identify potentially relevant information. With a series of interrelated processes and technologies, organizations are able to quickly and cost-effectively analyze a document collection, understand what each document is about, and make important decisions based on this understanding.

Content analytics is unlike traditional approaches to identify relevant data because:

  • It begins with a formalized first step: Content analytics engagements generally begin with establishing a logical framework – identifying what concepts you are looking for. This provides structure for analysis and allows for a methodical, repeatable approach to identify relevant data.
  • It leverages human understanding of language: Unlike alternative approaches that rely solely on artificial intelligence, content analytics takes advantage of a human's innate ability to understand context and meaning to determine what each document is about.
  • It is not wedded to a certain product or methodology: A variety of tools and methodologies are leveraged to accomplish the task, including (but not limited to) keyword analysis, predictive coding, bulk tagging, and visualization, because different objectives require different processes.
  • It takes the shortest path to finding all relevant data: Instead of looking for what may be relevant, content analytics provides clear insight on what data can't possibly be relevant, thus enabling the user to narrow the results with great speed and the highest degree of defensibility.

Content analytics has broad applications, particularly in eDiscovery and investigations, where data volumes are large, budgets are constrained, and the risk associated with missing potentially relevant documents is severe.

In the hands of a trained professional, it can deliver significant benefits. It prevents organizations from spending far too much on review and analysis, enables consistency of document interpretation, provides greater transparency into how results were achieved, and delivers a measurable level of certainty (if necessary) that all data has been uncovered.

Click here to learn more about RDC Analytics »