Real time business intelligence
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Real time business intelligence the process of delivering information about business operations without any latency. In this context, Real time means delivering information in a range from milliseconds to a few seconds after the business event. While traditional Business Intelligence presents historical information to users for analysis, Real Time business intelligence compares current business events with historical patterns to detect problems or opportunities automatically. This automated analysis capability enables corrective actions to be initiated and or business rules to be adjusted to optimize business processes.
Latency in real time systems
All real time Business Intelligence systems have some latency, but the goal is to make reduce the time taken from the business event happening to a corrective action or notification being initiated as sort a period as possible. Analyst Richard Hackathorn describes thee types of latency:
- Data latency; the time taken to collect and store the data
- Analysis latency; the time taken to analyse the data and turn it into actionable information
- Action latency; the time taken to react to the information and take action
Some commentators have introduced the concept of Right Time Business Intelligence which proposes that information should be delivered just before it is required, and not necessarily in real time.
Real Time Business Intelligence Architectures
* Event based Real time Business Intelligence
Real time Business Intelligence systems are event driven, and use Event Stream Processing techniques to enable events to be analysed without being first transformed and stored in a database. These in- memory techniques have the advantage that high rates of events can be monitored, and since data does not have to be written into databases data latency can be reduced to milliseconds.
* Real time Data warehouse
An alternative approach to event driven architectures is to increase the refresh cycle of an existing data warehouse to update the data more frequently. These real time data warehouse systems can achieve near real time update of data, where the data latency typically is in the rage from minutes to hours out of date. The analysis of the data is still usually manual, so the total latency is significantly different from event driven architectural approaches.
Application areas
- Algorithmic trading
- Fraud detection
- Systems monitoring
- Application performance monitoring
- Business Activity Monitoring
- Customer Relationship Management
- Demand sensing
- Dynamic pricing and yield management
- Data validation
- Operational risk management
- Payments & cash monitoring
- Data security monitoring
- Supply chain optimization
- RFID/sensor network data analysis
- Call center optimization
References
[Gartner Group - The Real Truth About Real-Time Business Intelligence and Data Warehousing]
[Real time Business Intelligence congress]
[Seven Successful Rules for real time data warehousing]
[Different approaches to real time Business intelligence]
[The difficulty with real time Business Intelligence in a data warehouse environment]
[Colin White - Now is the Right Time for Real-Time BI]
[Colin White - Building the Smart Business:In-Line Real-Time BI]
Real time Business Intelligence tools
Event based
Real time data warehouse
- [IBM]
- [Terradata]
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