Latency in real time systems
All real time business intelligence systems have some latency, but the goal is to
minimize the time from the business event happening to a corrective action or notification
being initiated. Analyst Richard Hackathorn describes three 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
Action latency; the time taken to react to the information and take action
Real time business intelligence technologies are designed to reduce all three latencies
to as close to zero as possible. Traditional business intelligence and business
activity monitoring by comparison only seek to reduce data latency and do not address
analysis latency or action latency since both are governed by manual processes.
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data latency typically is in the rage from minutes to hours out of date.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.
* Real time Server-less Technology
The latest alternative innovation to "real time" event driven and/or "real time"
data warehouse architectures is MSSO Technology (Multiple Source Simple Output)
which does away with the need for the data warehouse and intermediary servers altogether
since it is able to access live data directly from the source (even from multiple,
disparate sources). Because live data is accessed directly by server-less means,
it provides the potential for zero-latency, real time data in the truest sense.
* Process-aware Real time Business Intelligence
Also known as Operational intelligence, this allows entire processes (transactions,
steps) to be monitored, metrics (latency, completion/failed ratios, etc.) to be
viewed, compared with warehoused historic data, and trended - in real time. Advanced
implementations allow threshold detection, alerting and providing feedback to the
process execution systems themselves, thereby 'closing the loop'.
Application performance monitoring
Customer Relationship Management
Dynamic pricing and yield management
Operational intelligence and risk management
Payments & cash monitoring
Data security monitoring
Supply chain optimization
RFID/sensor network data analysis
Call center optimization