“The majority of companies don’t realize that they can answer many of their business questions with the data that they already have. It’s just a question of being able to access it.” — TSA Enterprise Solutions Architect, Corey Gary
In a previous blog post, we discussed the three basic levels of analytics—descriptive, predictive, and prescriptive—and explained how this technology is architected to break down massive amounts of raw data into more manageable, actionable chunks. With modern business data analytics, researchers and technologists no longer have to “drink from the fire hose” of raw data.
However, it is important to establish that analytics is not simply a “wind-up-and-let-it-go” apparatus; it requires more resources than its current IT buzzword-status may have you believe. As a result, many companies are underutilizing the data at their disposal.