The definition of ‘big data’ can be stated as “datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze”, and ‘big data’ is “high in velocity, volume, and variety”. Big data comes in many forms and includes electronic health records (EHRs), data collected by wearable patient devices, patient provided information, public health information, data collected through studies, demographic and geonomics information. Technology has been growing exponentially and it is important now more than ever to find innovative ways to keep up with the categorization of the masses of information we have available to use. The most important aspect of analyzing ‘big data’ is the capability to omit extraneous information while only analyzing what is pertinent to you intended or meaningful use of the data. Meaningful use refers to the ability to analyze the data effectively for the use in which it is intended. Advanced data analytics can be used to prevent and predict disease by analyzing algorithms to aid physicians in treatment planning and effective medication protocols. The veracity of data is more qualitative and more difficult to discern and includes the ability to measure accuracy, quality, and trustworthiness of data. With the explosion of information technology in health care, the filtering of ‘big data’ is necessary by selecting the correct analysis’ processes to extract the information needed to support data-based clinical decision making. I am overwhelmed personally by the abundance of information circulating, but I do know that as a healthcare provider currently and a future health care facilitator it will be highly important to understand the quality of data and how to properly analyze it.
