Unstructured data is an inevitable by-product of the information technology world. Often ignored or underutilized by the companies it belongs to, unstructured data is data that doesn’t fit neatly into actionable paradigms or isn’t represented within a database. Unstructured data may be in the form of help tickets, consumer records, email, Word documents or Excel sheets. For this reason, unstructured data can be very difficult to analyze, yet the data can still yield some results if used properly.
What Exactly is Unstructured Data?
Unstructured data comes in many forms and is easiest to understand by discussing specific examples. A hospital’s patient record database would be considered structured data. The records would have specific data fields and be organized in an understandable fashion that could be sorted and searched through.
Conversely, all the email in a company’s internal network would be considered unstructured data, as would documents used through the course of the company’s dealings. Although the header information of an email is structured, the actual text of the data would not be. Mining through customer emails to discover how often customers requested a specific product and then ordered more of that product would be an example of using unstructured data in a structured way and getting an actionable result.
Culling Useless Information and Mining through Important Data
The first step in utilizing unstructured data is to determine which data is truly relevant. Data needs to be appropriately classified and controlled before its relevancy can be determined. Once the data has been classified, the areas where it can become useful can then be identified. The usefulness of any given set of unstructured data will depend on the company and the industry involved. For this reason, unstructured data may need to be collected and classified before the data has actually become relevant, and there’s no guarantee the data will ever be helpful. Instead, throughout the company’s strategy planning the company may ask itself whether its unstructured data could potentially play a role in meeting current goals.
Archiving Unstructured Data for Future Use
Many companies end up with large volumes of unstructured data that aren’t currently useful but also shouldn’t simply be tossed aside. Rather than allowing this data to take up space in a cloud storage plan, many companies segregate their unstructured data based on usefulness, index it and then archive it. Those that have large amounts of unstructured data need to create protocols that determine whether the data is meaningful or not before archiving. They also need to have a very clear archive structure that allows them to find their archived data when necessary. This archived data also needs to be backed up alongside live data to ensure that nothing is lost.
In some ways, unstructured data is a misnomer. All data has a structure, and discovering this innate structure is often the key to using it. As big data grows even bigger, the need to appropriately mine and analyze all of it becomes vital. Companies will need to be creative and vigilant in their future data use, and the cloud platform may provide some unique opportunities in this area through its increased storage capabilities and processing power.
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