eQube®-ADA provides advanced analytics capabilities that incorporates Machine Learning (ML) and Advanced Statistics techniques for automated data
discovery. It helps to identify patterns, clusters, anomalies, textual insights, forecasting, time series decomposition, and text similarity in data.
It leverages state-of-the-art ML libraries like scikit-learn, Dask, statsmodels and Spark-ML. In addition, it has innovative augmented semantic modelling capabilities to auto discover and create semantic model based
on data. Using ADA, analysis pipelines are defined for specific use cases (tasks) that incorporate multiple ML techniques as steps in the pipeline. The task results, made up
of trained models and datasets, are consumed using REST APIs across our eQube® offerings (MI, BI, and DP).
eQube®-ADA works with the rest of our eQube® offerings to augment data profiling and data quality, harmonization, modelling, manipulation, enrichment / inference, metadata development,
and data cataloging.
eQube® App - Navy demo with predictive maintenance
What you see here is a For Purpose App built using eQube®-DaaS Platform. This App helps to log aircraft activity , track and repair aircrafts on an aircraft
carrier. It interacts with multiple systems behind the scene with the help of eQube®-DaaS Platform. eQube®-ADA plays a crucial part here, where although a human
being might not notice abnormal behaviour of the aircraft, eQube®-ADA can figure out abnormal behaviour of the aircraft based on the machine learning (ML) model and
automatically raise a Problem Report in the system.
Here it has an ML model using 700 runs of 200 to 300 cycles each with different settings of the engine.
Using this ML it can identify remaining useful life of the engine, identify anomalies in sensor readings,
degradation status of various parts as well as causes for engine degradation.
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