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Dark Data

Posted by Marcus Zillman

Dark Data

Data that’s regularly collected and stored, but rarely organized for further analysis. Dark data refers to data that has been collected and stored, but not organized in a usable format for further data analysis. As a result, you cannot use it for decision-making. It is called dark because it is unexplored. According to Gartner, dark data is “the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes.” Customer call records are an example of dark data. These types of records are regularly recorded and stored, but rarely organized or analyzed. Other examples of dark data include social network feeds, financial statements, raw survey data, emails, log files, geo-location data and notes, among others. Dark data is complex and difficult to categorize. Often, it requires large amounts of resources to be processed and analyzed. However, it offers significant value to organizations for extracting critical insights that can drive tremendous business value. For example, customer call records can indicate customer sentiment. Web server logs can reveal visitor behavior. Organizations can use these insights to improve their products or services. This will be added to Business Intelligence Resources Subject Tracer™. This will be added to Entrepreneurial Resources Subject Tracer™. This will be added to the tools section of Research Resources Subject Tracer™.

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