dotData Partners With Teradata, a Leading Cloud Data & Analytics Company
By making Teradata Vantage available, dotData offers enhanced seamless integration between enterprise data management and AutoML 2.0
dotData, a leader in full-cycle data science automation and operationalization for the enterprise, announced that it has partnered with Teradata, a leading cloud data & analytics company. The integration leverages the robust enterprise data management and analytic capabilities of Teradata’s Vantage platform and dotData’s autoML 2.0 platform to create a powerful end-to-end data science solution, from data collection and preparation through feature engineering to machine learning operationalization. The collaboration will streamline and simplify the movement of data between Teradata and dotData to help the companies’ joint customers derive more value from their AI and machine learning initiatives.
Vantage is Teradata’s flagship platform that was designed to simplify analytic ecosystems by unifying analytics, data lakes and data warehouses. This single platform ensures that insights are based on 100 percent of the data. Regardless of the required scale or the location of the data, organizations receive a unified, integrated view of the business.
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dotData provides AutoML 2.0 solutions that help accelerate the process of developing AI and Machine Learning models for use in advanced predictive analytics BI dashboards and applications. dotData makes it easy for BI developers and data engineers to develop AI/ML models in just days 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. 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 that are fundamental to developing predictive analytics solutions.
Mitsui Sumitomo Insurance Co., Ltd., a member of MS&AD Insurance Group Holdings, Inc. (‘MS&AD Insurance Group’) leverages the combination of Teradata and dotData in its data science program to optimize customer value and utilization of its products and services.
“We aim to build trust and loyalty among our customers, and using advanced digital technology to better meet our customers’ needs is one way in which we excel above our competition,” said Mr. Shinichiro Funabiki, Senior Executive Officer, CDO of MS&AD Insurance Group. “Deploying the combined solution of Teradata and dotData gives us a powerful and streamlined data science platform that enables our data science team to maximize the value of our data science investments, and bring better value to our customers.”
“The integration of the Teradata and dotData platforms enables our joint customers to leverage the benefits of Teradata’s proven, enterprise-class data solutions with dotData’s autoML 2.0 platform to derive even greater value from their AI and ML models,” said Ryohei Fujimaki, Ph.D., CEO and founder of dotData. “We are proud to collaborate with Teradata to help MS&AD transform the insurance business with our data science automation.”
dotData democratizes data science by enabling BI developers and data engineers to make enterprise data science scalable and sustainable. dotData automates up to 100 percent of the AI/ML development 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 AI/ML models by producing both feature and ML scoring pipelines in production, which IT teams can then immediately integrate with business workflows. 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, AI/ML development becomes a five-minute operation, requiring neither significant data science experience nor SQL/Python/R coding.
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