BHC3 AI Suite
Continuous Analytics Processing
Continuous analytics processing is an important feature of the BHC3 AI Suite that allows for the efficient analysis of big data. With the broad-scale deployment of sensors and the availability of data from multiple enterprise and external data sources, companies generate and ingest very large volumes of data every second. Recent reports have shown that data volumes are now exceeding 10TB of data per day for a single oil well. While machine learning models generally get better with more data, ingesting large volumes of high-velocity data and analyzing it using machine learning models can be an expensive task. This can prove particularly wasteful when the data does not change significantly enough to impact the analytical model predictions.
Continuous analytics processing helps to automatically and efficiently update analytics and machine learning predictions as soon as new data arrives and ensures that end users are always using the latest analytics results. The BHC3 AI Suite enables developers to quickly and easily configure analytics that will trigger only when relevant new data arrives.
Automate Machine Learning
- Retrain algorithms when needed.
- Manage retraining pipelines based on incoming data.
- Detect anomalies as they occur when using unsupervised algorithms.
- Update the predictions for business users when it is required, using latest data.
Data Flow Events
- Leverage distributed stream processing to capture new data and calculate updated results.
- Configure specific analytics and frequency to update on arrival of new data.
- Optimize computation needs by updating only when sufficient new data has arrived.