LOS ANGELES, CA--(Marketwired - Mar 6, 2017) - DataScience, Inc., today announced the launch of Playbooks, a comprehensive set of tools designed to give DataScience Cloud clients the information they need to build powerful and predictive data models from the ground up.
Playbooks fall under the umbrella of DataScience Success, the data science software company's full-service client success program that includes benefits like advisory services and access to an online community of data scientists. Clients on the DataScience Cloud, the company's enterprise data science platform that launched last year, receive these services automatically with their DataScience Cloud subscription. The program is part of DataScience's mission to go beyond the role of platform provider and give its clients the tools they need to achieve maximum business value from their data science efforts, starting from their first day on the platform.
"What makes DataScience's offering unique is that you're not just getting a packaged software platform," said Ian Swanson, CEO and founder of DataScience. "The DataScience Cloud comes with a full suite of solutions backed by our internal team of data scientists who have already solved complex problems across a wide array of industries. Playbooks were the logical next step for us -- these repositories include exclusive content and code libraries that will help our customers tackle predictive modeling from A to Z, in a way that is completely attuned to their business."
Each Playbook covers a specific business challenge that can be addressed through a predictive data model, such as calculating customer churn or lifetime value. To help its clients' data science teams shorten their R&D timelines and get the information they need to build data models in house, DataScience has devised comprehensive, in-depth content and curated and reviewed the latest research to create each Playbook. Some of the features of Playbooks include:
- A collection of topic-specific curated knowledge: DataScience's internal team has gathered, vetted, and annotated the best scientific literature associated with each Playbook topic. As new research is published, the Playbook knowledge base will be updated.
- An ecosystem of notebooks and code: DataScience Cloud clients will have access to notebooks that walk them through model diagnostics, feature engineering, and benchmark comparisons between different types of models. They can also take advantage of code libraries to help them start modeling projects.
- A library of models already implemented and available in the DataScience Cloud: As part of Playbooks, DataScience is making the state-of-the-art models built by its internal team available to DataScience Cloud clients, along with information on how to select the right model, train it on new data, and deploy it into production.
- Data scientist-led seminars: To make leveraging Playbooks even easier, members of DataScience's internal team will lead clients through Playbooks material and help them apply techniques to their own data.
"Historically, DataScience has worked with two types of customers: companies that are now scaling their data science teams in an attempt to bring model building in house after years of relying on pre-canned applications, and companies that developed a system for building models internally that is now limited by legacy software and analytics packages," Swanson continued. "Their challenges differ, but their need is the same: They both need the ability to build better models. Playbooks, paired with the capabilities of the DataScience Cloud, can give them that."
To find out more about Playbooks, and to request a demo of the DataScience Cloud, please visit www.datascience.com.
DataScience, Inc. provides the DataScience Cloud, an enterprise data science platform that pairs the tools, libraries, and languages data scientists know with the infrastructure and workflows their organizations need. The DataScience Cloud maximizes the way data scientists like to work, so they can solve the right problems, create better analyses, amplify their results, and put more work into production -- all from one place. To learn more, or to request a demo, visit www.DataScience.com.