Real time analytics, is about making faster decisions to influence the events, based upon data from events which are happening now and data stored from past. Some organizations have been using real time analytics for many years. However, building real time analytics solutions was complex, costly and time consuming. Real time analytics so far was leveraged by large organizations with deep pockets and resources. Even existing solutions needs to go through change with availability of new unstructured data sources to improve the decision algorithms.
However, now many technologies are available to build scalable and cost effective solutions for real time analytics. Innovyt has recommended architecture which used Hadoop and related technologies including Kafka, Spark to build real time analytics solutions. We see two main use cases for real time analytics solutions.
- Identify risk as soon as possible e.g. fraud analytics.
- Respond to current events e.g. factory maintenance.
THERE ARE TWO PARTS OF THIS SOLUTION
- First part is about creating model from historical data.
- Second part is about using the model to predict based upon live events.
APPLICATIONS OF THE REAL-TIME ANALYTICS:
- Marketing
- Security
- Fraud Prevention
- Customer Support
Our recommended solution approach keeps scalability, cost, data latency and effectiveness in mind.
