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eQ Technologic enhances eQube®-ADA 3.2 with Automated Data Discovery

eQ Technologic enhances eQube<sup>®</sup>-ADA 3.2 with Automated Data Discovery

In today's data-driven world, the ability to uncover hidden patterns, make predictions, and derive insights from data is paramount. That is where eQube®-ADA comes into play. With its latest release, eQube®-ADA 3.2, a Machine Learning (ML) based automated data discovery and modeling platform, it's easier than ever to harness the power of data for predictive analysis, textual narratives, and identifying patterns, clusters, and anomalies. In this blog post, we will explore the exciting features and capabilities that eQube®-ADA 3.2 brings to the table. 

Dinesh Khaladkar, our President & CEO, stated, “Data is one of the most valuable assets for any organization.  Having an unprecedented ability for data discovery and data analysis using ML techniques can be a game changer for organizations. Excited to announce the release of eQube®-ADA 3.2 with its inherent capabilities in automated data discovery and ML modeling. With eQube®-ADA integrations with eQube®-BI and with eQube®-MI, our customers will be able to productionize compelling solutions that deliver intended business outcomes.” 

Unlocking the Potential of Data in Motion 

Augmented ML Modeling 

One of the standout features of eQube®-ADA 3.2 is its automated ML modeling capabilities. With wider support for eQube® connectors, eQube-ADA now opens doors to a broader range of data sources beyond text files and databases. Gone are the limitations of having very few connectors to use. Now, you can seamlessly access and analyze from multiple data sources supported by eQube®-DaaS platform. Additionally, eQube®-ADA 3.2 introduces support for creating multi-system, multi-object complex datasets using the Easy Mapper. This empowers users to build comprehensive datasets that drive more accurate and insightful ML models. 

Another significant enhancement is the caching of datasets. This not only optimizes trial execution but also supports results on rerun. To enhance security, eQube®-ADA 3.2 offers support for cached dataset encryption, ensuring that sensitive data remains protected. 

Model Delivery, Management, and Monitoring 

In the world of ML, deploying models from development to production can be a complex process. eQube®-ADA 3.2 streamlines this journey with faster deployment capabilities. It enables the swift transition of ML models from development to the production environment, seamlessly integrated with the eQube®-DaaS Platform. 

This release also introduces support for what-if analysis on deployed ML models, allowing users to explore different scenarios and fine-tune their models for optimal performance. Additionally, users can now review data drifts as part of deployed ML model monitoring, ensuring that models remain accurate and reliable over time. 

Enhanced Usability 

Usability is a key focus of the eQube®-ADA 3.2 release. To cater to diverse user roles and responsibilities, this release adds operations and roles for Data Engineers, Data Scientists, and MLOps Engineers, each with their own access controls. It also offers the ability to download ML engine logs, providing easy ways to troubleshoot issues in trial runs and ML model deployment. Users can now update ML engine properties directly from the application, enhancing the overall user experience. Additionally, the ability to maximize Custom Script Input further improves flexibility in extending solutions with scripts. 

Augmented Data Preparation and Discovery 

Data discovery is a crucial step in the data analysis process. eQube®-ADA 3.2 introduces support for Automated Insights based on associations, trends, trend comparison across different measures and categories in collaboration with the eQube®-BI platform. 

Streamlined Deployment 

For organizations managing multi-tenant environments, eQube®-ADA 3.2 offers support for multi-tenant deployments for eQube®-ADA. It also introduces the ability to set processor affinity for the ML engine, allowing organizations to manage CPU allocations to ML Engine deployment easily. Moreover, this release aligns with industry standards by upgrading the minimum supported Java version to 11 (11.0.17 onwards). 

In conclusion, eQube®-ADA 3.2 release represents a significant leap forward in the world of automated data discovery and ML modeling. Its enhanced capabilities in ML modeling, model delivery and management, usability, data preparation, and deployment make it a compelling choice for organizations seeking to derive valuable insights from their data. With its certified compatibility with eQube®-BI 8.4 and eQube®-MI 6.1, eQube®-ADA 3.2 is ready to empower you to explore, analyze, and leverage your data like never before.  


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