Real-time business intelligence architectures are designed to enable organizations to access and analyze data in near real-time, allowing them to make informed, data-driven decisions quickly and efficiently.
With RTBI, organizations can better understand their customers, optimize their operations, and improve their overall decision-making process.
Real-time Business Intelligence systems are event-driven and may employ Complex Event Processing, Event Stream Processing, and Mashup (web application hybrid) techniques to analyze events without first transforming and storing them in a database. These in-memory database techniques have the advantage of monitoring high rates of events and reducing data latency to milliseconds because data does not have to be written into databases.
To update data more often, one alternate option to event-driven systems is to increase the refresh cycle of an existing data warehouse. These real-time data warehouse systems can update data in near real-time, with data latency typically ranging from minutes to hours. Because data analysis is still typically done manually, total latency differs dramatically from event-driven architecture approaches.
MSSO Technology (Multiple Source Simple Output), the most recent alternative innovation to “real-time” event driven and/or “real-time” data warehouse systems, eliminates the requirement for the data warehouse and intermediary servers entirely because it can get live data straight from the source (even from multiple, disparate sources). Because live data is retrieved directly by server-less means, it has the possibility for true zero-latency, real-time data.
This is also known as Business Activity Monitoring and is sometimes considered a component of operational intelligence. It enables the monitoring of complete processes (transactions, steps), as well as the viewing of metrics (latency, completion/failed ratios, etc.) that can be compared to warehoused past data and trended in real-time. Advanced solutions enable threshold detection, alerting, and feedback to process execution systems, effectively ‘closing the loop’.
Technologies that support real-time analytics
Data visualization, data federation, corporate information integration, enterprise application integration, and service oriented architecture are all technologies that can be supported to provide real-time business intelligence. Complex event processing technologies can be used in real time to evaluate data streams and either trigger automated actions or alert workers to patterns and trends.
Data warehouse appliance
A data warehouse appliance is a hardware and software solution designed for analytical processing. DBAs perform duties such as tuning, adding or updating structure to data, and optimizing the database for large groups of users.
Mobile business intelligence is provided by a small number of providers; MBI is connected with current BI architecture. MBI is a package that combines existing BI tools to allow consumers to make informed decisions on their mobile phone in real time.