With all the hype about big data changing the way the healthcare industry tracks and treats patients, it’s easy to assume that the need for human interpretation will diminish over time. After all, big data paves the way for artificial intelligence and machine learning to cut costs and predict behavior through a multitude of complicated algorithms and models that use its massive storage of data sets without human input, right? Not quite. What many don’t realize is that data – especially big data – is only useful if it has meaning. And to have meaning, it has to be standardized and applied to a specific situation. In much the same way that professors explain course material or immigration lawyers make clear the nuances of f1 vs j1 visas, data analysts interpret the facts that big data presents, and while human manipulation might indeed decrease along certain points of the data collection cycle, it will never be completely removed. On the contrary, data analysis will inevitably become more critical as more and more data becomes available.
The Difference Between Big Data and Databases
Traditional relational databases use tables with rows and columns to organize and record single data points. They can be expensive to create, but they allow easy access to information because everything is filed in a specific, recognizable system.
Big data, on the other hand, is not organized nor is it compressed into one data node. Instead, it is “raw” and characterized by the 3 V’s: volume, velocity and variety. The amount and type of data sources, along with the speed with which they accumulate, make the interpretation of big data a lot more difficult than that of the data stored in a typical database.
The Role of a Data Analyst
Because federal guidelines now govern the way big data is collected and stored, it is ever more vital that healthcare providers and other industry professionals be meticulous in the ways they solicit, record and use data. Otherwise, they risk massive penalties that can reach into the millions of dollars. It’s a tall order for healthcare industry workers already pulled in multiple directions. Nevertheless, the American healthcare sector is moving toward big data solutions with collaboration and information sharing not only among physicians, but laboratories, pharmacies, patients and multiple types of payers, as well. And because of this, data analysis will be critical for meeting cost-saving and patient care goals.
Data analysts label and measure the relevant aspects of a population, condensing big data into significant points of information and predicting action from them. They know how to search for and transform nuggets of material into actionable insights. Theirs is a skill set that the average healthcare professional doesn’t have the time to learn and the number one reason that the healthcare industry will always need their help.