New SnapLogic Data Science Solution Improves Data Engineering and Data Science Results by Accelerating the Development and Deployment of Machine Learning Models
SnapLogic, provider of the intelligent integration platform, announced SnapLogic Data Science, a new self-service solution to accelerate the development and deployment of machine learning with minimal coding. Through SnapLogic’s drag-and-drop interface, data engineers, data scientists, and IT/DevOps teams can use SnapLogic Data Science to manage and control the entire machine learning lifecycle – including data acquisition, data exploration and preparation, model training and validation, and model deployment – all from within the SnapLogic integration platform. SnapLogic Data Science breaks down traditional barriers that can undermine machine learning initiatives by providing a common platform for machine learning visibility and collaboration across teams including data engineering, data science, IT, DevOps, and development.
“With SnapLogic Data Science, we’re enabling our customers to overcome the common barriers associated with putting machine learning into practice by arming them with a full stack of self-service tools to be faster, more agile, more data-driven.”
According to our recent research with Vanson Bourne, 68% of IT decision-makers consider artificial intelligence and machine learning as vital to accelerating their transformation projects. At the same time, McKinsey Global Institute predicts that the U.S. alone will be short 250,000 data scientists by 2024. Machine learning initiatives are hampered by limited access to data science talent as well as a lack of automated data access to fuel model building. By bridging the data science skills gap and automating the machine learning lifecycle, SnapLogic Data Science makes end-to-end machine learning accessible to enterprises of all sizes for the first time.
“Every enterprise in every industry will need to employ AI and machine learning in order to keep pace with today’s most progressive businesses. However, most companies fall flat in actualizing machine learning because they don’t have the talent or financial resources to make the most of their data,” said Greg Benson, Chief Scientist at SnapLogic. “With SnapLogic Data Science, we’re enabling our customers to overcome the common barriers associated with putting machine learning into practice by arming them with a full stack of self-service tools to be faster, more agile, more data-driven. Just as we enabled self-service application and data integration for IT and citizen integrators, we are extending these self-service capabilities to data engineers and data science teams who need to build and deploy machine learning models faster and easier.”
“451 Research believes the operationalization of data science projects involving machine learning and other artificial intelligence technologies is set to be a significant aspect of the next wave of developments in the data management space,” said Matt Aslett, Research Vice President, Data, AI and Analytics, 451 Research. “As adoption of data science expands and matures we expect to see enterprises looking for products and services that simplify and support the complete machine learning lifecycle from development, through training and testing to deployment.”