DataScience, Inc., announced the DataScience Cloud, a platform that enables data scientists to explore varied data sources, build models and algorithms, and seamlessly deploy work throughout their entire organization, regardless of their tech stack and level of engineering support.
The DataScience Cloud is the culmination of the best practices DataScience has established over two years of working with clients to perform high-volume data engineering, data analysis, and predictive modeling work. The platform launches as a direct competitor to SAS for enterprise data science teams that seek a more modern, full-service platform designed to support their particular needs.
Leading companies see data science as an integral part of every business function, but many enterprise data science teams lack the tooling, infrastructure, and engineering support for their diverse workflows and needs,” said Ian Swanson, CEO, DataScience Inc. “The result is a broken and inefficient process which inhibits the ability of data science teams to experiment efficiently, collaborate with each other, and deliver value at scale. Working closely with our customers, we designed the DataScience Cloud as a platform for enterprise data science teams to work seamlessly from data integration to model deployment, backed by secure big data infrastructure and industry expertise. What Salesforce has done for maximizing the value of sales teams, DataScience is doing for maximizing the value of data science teams.”
The launch of the DataScience Cloud coincides with the rise of insights-driven businesses, which are poised to take $1.2 trillion away from their peers by 2020. That’s according to Forrester Research’s July 2016 report, “The Insights-Driven Business,” which defines insights driven companies as those who apply data and analytics at every opportunity to optimize their products and customer experiences. And while hiring for data scientists continues to skyrocket, many companies are not realizing the value of those investments, and are beginning to fall behind more agile, insights-driven companies.
The ability to turn insight to action is no longer a ‘nice to have,’” Swanson said. “It must become a core competency that will make or break companies in the next five years. Enterprise data science teams face a number of unique challenges related to their workflows, many of which are compounded by reliance on inflexible tooling and infrastructure from legacy companies such as SAS. That’s why we’re excited to offer the DataScience Cloud as the platform for enterprise data science teams to deploy models and insights across their organization and to win in the marketplace.”
The DataScience Cloud helps data science teams complete virtually every task in their workflow, from merging disparate data sources to deploying predictive models. Each tool in the platform addresses a key function of the data science process:
- DataScience Connect: a gateway for securely connecting any type of data source, with support for over one hundred integrations, like SQL databases, distributed filesystems, streaming data endpoints, SaaS platforms (e.g. Salesforce), and a variety of data enrichment sources.
- DataScience Explore: a data source browser, query editor, and visualization tool for quickly understanding and shaping data across every source.
- DataScience Notebook: a powerful, cloud-hosted notebook to seamlessly create and share analyses, visualizations, and reports. With access to pre-built playbooks and tutorials, data teams can get their analyses up and running quickly.
- DataScience Deploy: turns models and algorithms into scalable apps automatically. Code sent to the platform is deployed behind an API, making it accessible to any service with a web connection.
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