dotData is Selected by the Microsoft for Startups Program

dotData, a company focused on delivering full-cycle data science automation and operationalization for the enterprise, has been selected as a qualified partner in Microsoft for Startups.

Microsoft for Startups selects organizations developing innovative enterprise-ready technology solutions that run on Microsoft Azure.

The program will provide dotData access to the full Microsoft ecosystem, including sales, marketing, and technical support, to advance dotData's expansion and drive continued innovation by helping dotData make its platform available on Azure.

dotData was selected for Microsoft for Startups as its innovative full-cycle data science automation solution is unique in the fast-growing market of AutoML.

As a qualified partner, dotData will be able to provide to its customers the power of dotData's data science automation along with the benefits and capabilities of Microsoft's highly available, trusted, and scalable Azure cloud platform.

"We are thrilled that Microsoft has recognized dotData's work and selected us to be among the innovative companies in the Microsoft for Startups program," said Ryohei Fujimaki, Ph.D., CEO and founder of dotData. "By having direct access and insight from Microsoft, we will be able to better support our customers who are on Microsoft Azure. We look forward to working with the Microsoft team to drive the continued rapid growth of our full-cycle data science automation solution on Azure."

dotData combines AI-powered feature engineering and AutoML to automate the full life-cycle of the data science process, from source data through feature engineering to implementation of machine learning in production.

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.

dotData democratizes data science by enabling existing resources to perform data science tasks, making enterprise data science scalable and sustainable. 

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