dotData Achieves AWS Machine Learning Competency Status

Source:-aithority.com

Company Achieves Milestone Just Eight Months After Joining the AWS Partner Network, Proving Technical Validity and Customer Success of dotData’s AutoML 2.0 Platform

dotData, focused on delivering full-cycle data science automation and operationalization for the enterprise, announced that it has achieved Amazon Web Services (AWS) Machine Learning (ML) Competency status.

dotData achieved AWS ML Competency status only eight months after joining the AWS Partner Network (APN). The certification recognizes dotData as an APN Partner that accelerates the full-cycle ML and data science process and provides validation that dotData has deep expertise in artificial intelligence (AI) and ML on AWS and can deliver their organization’s solutions seamlessly on AWS. dotData achieved AWS ML Competency status through a rigorous qualification process that included a strict validation of their capabilities to demonstrate technical proficiency and proven customer success, as well as a technical audit of its dotData Enterprise solution.

dotData provides solutions designed to improve the productivity of data science projects, which traditionally require extensive manual effort from valuable and skilled resources, by automating the full life-cycle of the data science process, from business raw data through feature engineering to implementation of ML in production utilizing its proprietary AI technologies.

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dotData’s AI-powered feature engineering automatically applies data transformation, cleansing, normalization, aggregation, and combination, and transforms hundreds of tables with complex relationships and billions of rows into a single feature table, automating the most manual data science projects.

“By leveraging the ease of use of dotData Enterprise and the power of AWS, we were able to develop and deploy our first machine learning models in weeks, without the need for data scientists,” said Phillip Byrnes, Director of Business Intelligence, of US Electrical Services Inc. an independent electrical supply distributor headquartered in Middletown CT. “dotData Enterprise is like having a mathematician in a box, it helps us optimize our business by leveraging our existing Business Intelligence teams and resources. The product is that easy to use.”

“From its foundation, dotData’s vision has been to make AI and ML accessible to as many people in the enterprise as possible. We are proud of the successful experience of US Electrical Services’ BI team, which is a testament to our commitment to truly democratize AI in enterprise,” said Ryohei Fujimaki, founder and CEO of dotData. “Achieving AWS ML Competency status in just eight months recognizes our ability to deliver an outstanding product that dramatically accelerates the AI and ML initiatives of AWS users and maximizes their business impacts.”

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AWS ML Competency Partners provide solutions that help organizations solve their data challenges and enable ML and data science workflows. The program is designed to highlight APN Partners who have demonstrated technical proficiency in specialized solution areas and helps customers find the most qualified organizations with deep expertise and proven customer success.

dotData democratizes data science by enabling existing resources to perform data science tasks, making enterprise data science scalable and sustainable. dotData automates up to 100 percent of the data science workflow, enabling users to connect directly to their enterprise data sources to discover and evaluate millions of features from complex table structures and huge data sets with minimal user input. dotData is also designed to operationalize data science by producing both feature and ML scoring pipelines in production, which IT teams can then immediately integrate with business workflow. This can further automate the time-consuming and arduous process of maintaining the deployed pipeline to ensure repeatability as data changes over time. With the dotData GUI, the data science task becomes a five-minute operation, requiring neither significant data science experience nor SQL/Python/R coding.

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