Data Analytics

DEFINITION of 'Data Analytics'

Data analytics is the science of drawing insights from sources of raw information. Many of the techniques and process of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption. Data analytics techniques can reveal trends and metrics that would otherwise be lost in the mass of information. This information can then be used to optimize processes to increase the overall efficiency of a business or system.

BREAKING DOWN 'Data Analytics'

Data analytics is a broad term that encompasses many diverse types of data analysis. Essentially any type of information can be subjected to data analytics techniques to get insight that can be used to improve things. For example, manufacturing companies often record the runtime, downtime, and work queue for various machines and then analyze the data to better plan the workloads so that the machines operate closer to peak capacity.

Of course, data analytics can do much more than point out bottlenecks in production. Gaming companies use data analytics to set rewards schedules for players that keep the majority of players active in the game. Content companies use many of the same data analytics to keep you clicking, watching, or re-organizing content to get another view or another click.

Types of Data Analytics

Data analytics is broken down into four basic types.

  • Descriptive analytics describes what has happened over a given period of time. Have the number of views gone up? Are sales stronger this month than last?
  • Diagnostic analytics focuses more on why something happened. This involves more diverse data inputs and a bit of hypothesizing. Did the weather affect beer sales? Did that latest marketing campaign impact sales?
  • Predictive analytics moves to what is likely going to happen in the near term. What happened to sales last time we had a hot summer? How many weather models predict a hot summer this year?
  • Prescriptive analytics moves into the territory of suggesting a course of action. If the likelihood of a hot summer as measured as an average of these five weather models is above 58%, then we should add an evening shift to the brewery and rent an additional tank to increase output.

Data analytics underpins many quality control systems in the financial world, including the ever-popular Six Sigma program. If you aren’t properly measuring something - whether your weight or the number of defects per million in a production line - it is nearly impossible to optimize it.