Real-time analytics is a term used to refer to analytics that can be accessed as they come into a system. In general, the term analytics is used to define data patterns that provide meaning to a business or other entity, where analysts collect valuable information by sorting through and analyzing that data. The adjective real-time refers to a level of computer responsiveness that a user senses as immediate or nearly immediate. It is the analysis of data as soon as that data becomes available, helping businesses react without delay.
Most companies use analytics. Many can act on data from months, weeks, or even days ago. But few can respond to changes minute by minute, or second by second. Because: They're stuck in a mosaic of ETL processes and Excel.- Real-time analytics enable faster, more precise and more effective decisions than conventional decisions made with stale data or no data. Real-time analytics require a structured decision process with predefined logic, but the data must be immediately available, and acquiring this data is often the limiting factor.
Healthcare data from different equipment can be treated as a single data point, adding to the vast data accumulated from a single patient. These data points are crucial for recommending the right medication within a short window. If a real-time analytical engine is in place at the hospital, it can quickly give suggestions to the doctor in picking the right medication and providing the best care immediately and definitely better care tomorrow.