eQube-ADA provides advanced analytics capabilities. It incorporates Machine Learning (ML) and Advanced Statistics techniques for automated data discovery: 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. With 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 eQube offerings (MI, BI, and DP).

eQube-ADA works with the rest of eQube offerings to augment data profiling and data quality, harmonization, modeling, manipulation, enrichment/inference, metadata development, and data cataloging.


Example of eQube-ADA usage


eQube app Navy Demo with Predictive Maintenance

This is an example of how eQube-ADA is used to analyze sensor data from an aircraft, and automatically raise a Problem Report behind the scene.

eQube-ADA works to augment data profiling and data quality, harmonization, modeling, manipulation,enrichment/inference, metadata development, and data cataloging