How Text Analytics Can Solve the Unused Data Problem
The world is producing a massive amount of data that companies want to use to their advantage. However, 88% of information that companies collect from every channel goes unused and unanalyzed. This data sits in massive storage servers, waiting to be put to use. The difficulty lies in both the nature of the data and the technology to analyze it. For years, analysts and data scientists on board with various companies have used a variety of strategies to process and gain insight from their data. Some processes have become obsolete, requiring massive amounts of time and energy to gain even the barest understanding. The average analyst spends 80% of their time manually processing data sets in Excel or SQL for structured data. When that data is unstructured, the time investment goes up exponentially.
Much of the information that goes unused is in the form of unstructured textual data. Text data has historically been difficult to analyze due to the sheer man hours it would take to read through and see any value in line upon line of text. Advances in text analytics tools have allowed companies to gain better insight from their mountain of text data, but many companies are slow to adopt these new technologies, leaving much of their gathered information on the shelf.
With data as the new portal to better customer experience, greater employee understanding, deep marketing insight, and product management excellence, 85% of companies are making efforts to be data driven. Yet, only 37% of these companies believe that their efforts will be successful in showing ROI. With 60% of business leadership believing that failure to implement strong data analytics for big data projects will lead to obsolescence, there is a wide gap between expectation and reality.
72% of businesses admit to collecting they never use, calling the process of analysis expensive and time consuming. 52% of this data is known as dark data, or information that has never been given a value or categorized in any way. While it’s understandable that the mountains of information available to companies can go unanalyzed in such huge quantities, it isn’t necessary. Advances in data analytics tools with machine learning and artificial intelligence can automatically process and analyze huge volumes of data in minutes, not months to provide near real time insight on a wide variety of information. By utilizing better data tools, businesses can gain access to their unused information and create better data driven decisions.