As you can imagine, the concept of interpreting results is a fairly broad one. Simply put, no matter what you are interested in, there is a ton of data out there for it. At the same time, there are a number of ways in which you can interpret these results.

While it is naturally important for a variety of reasons to interpret these results, it’s also important to understand the dangers inherent in doing so. Most concepts are divided into good and bad points. With data interpretation, it’s impossible to fully appreciate the benefits, without also considering the challenges and very-real dangers.

Problematic Elements To Interpreting Results

One of the main dangers of interpreting results involves shifting to an impersonal approach to analyzing data. Many would argue that a humanistic approach is essential to getting useful information from deep data results. However, with so much material to sift through, maintaining that humanistic approach can be a challenge. After a certain point, maintaining efficiency becomes impossible. A speedier process can allow interpreters to move through the information quickly. However, in doing so, they may lose the crucial notion that involves keeping in mind that we’re dealing with people. We are dealing in personals. Taking an impersonal touch to interpreting data that involves real people can become highly dangerous in short order.

Improved decision making is another danger to interpreting results. Creativity is sometimes an essential element to using data results to improve the decision making process. Trying to make sense of so much data can sometimes suffocate that creativity, with the end result being to simply make the data easy to understand. The range of possibilities for improving decision making can suddenly become much, much smaller. Data interpretation can suddenly become a shallow, ultimately useless endeavor.

There is also the potential of data interpretation being used for sinister purposes. It seems like news articles about the NSA and privacy concerns are cropping up all the time. They are. As the range of tools for data acquisition and interpretation becomes increasingly elaborate and comprehensive, concerns over personal privacy and security become complex. This is perhaps one of the most significant dangers associated with data interpretation. As you can note from all of the information above, privacy and security are not the only dangers to keep in mind.

As time goes on, it will be interesting to see how governments, companies, and even individuals utilize data interpretation. How will they consider the various dangers?


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