Real-time business intelligence is an approach to data analytics that enables business users to get up-to-the-minute data by directly accessing operational systems or feeding business transactions into a real-time data warehouse and business intelligence (BI) system.
The technologies that can be used to enable real-time BI include data virtualization, data federation, enterprise information integration (EII), enterprise application integration (EAI) and service-oriented architectures (SOA). Complex event processing tools can be used to analyze data streams in real time and either trigger automated actions or alert workers to patterns and trends.
Real-time BI can help support instant decision-making, which is necessary, for example, if a company sells clothing online. The company's website and representatives at the company's call center need to have the same up-to-the-minute data regarding inventory levels so if a customer places an order and a particular size or color is sold out, the customer can be notified and redirected to another, similar item. A real-time approach isn’t required for every part of a company's business, however. Most BI users can meet their business goals by looking at weekly or monthly business performance numbers and long-term trends such as year-over-year comparisons. Similarly, finance groups aren’t likely to require real-time data to analyze financial metrics or compare actual budgets to forecasts.
Because real-time BI implementations can increase the overall cost of a BI system, the best practice for organizations is to deploy real-time BI technology only when it’s absolutely required.