Online Analytics or business intelligence, also referred to as operational business intelligence and sometimes called real-time business intelligence.
It is an approach to data analysis that enables decisions based on the real-time data companies generate and use on a day-to-day basis. Typically, the data is queried from within an organization’s enterprise applications. Operational business intelligence technology is primarily targeted at front-line workers who need timely data to do their jobs. It is also used to feed interactive dashboards, a source of insights and tools for senior management who drive their business through data driven decisions.
With operational BI, analysis can take place in tandem with business processing, so that problems can be spotted and dealt with sooner than with conventional after-the-fact business intelligence (BI) approaches. It enables the creation of a performance and feedback loop in which decision makers can analyze what’s happening in the business, act upon their findings and immediately see the results of those actions.
Data must be extremely current, which isn’t always possible with the traditional bounds of both enterprise reporting and data warehousing. However, most business processes at a typical company don’t require real-time data. With that in mind, a key part of every operational BI project is determining which business users need up-to-the-minute data for BI purposes and how they will handle getting data delivered to them in that fashion.
CR-X is a high functioning data gateway that collects massive volumes of data from across the entire enterprise – then cleanses, transforms, compresses and encrypts the data before distributing to single or multiple destinations, at extreme speed (in excess of 100,000 records per second per single core) CR-X has the capacity to collect, cleanse, transform and distribute terabytes of valuable information every hour.
By doing so CR-X has the capacity to feed dashboards in real-time, send triggers and alerts when thresholds are breached and feed downstream enterprise data warehouses, operational data stores and real-time data analytics engines.