Everybody is Sherlock Holmes in the era of Watson-powered team data science
Sherlock Holmes was the ultimate data scientist. He deftly sought out relevant data, made astute inferences, and iteratively tested hypotheses on his hunt for actionable insights. But he couldn’t have been quite so effective if he hadn’t had a versatile, reliable partner, Dr. John H. Watson, to help him acquire the necessary data and keep him focused on the problem at hand.
Data science is a team sport that involves specialists with complementary skills and aptitudes. Successful data science initiatives leverage high-performance team collaboration. Like the fictional sleuth and his partner, IBM’s customers in the data science community must have the right mix of Holmeses and Watsons in their teams working closely together.
Recognizing this imperative, IBM has designed IBM Watson Data Platform (WDP) as an integrated platform for team data science. WDP is a single cloud-based development platform for team data science that integrates data for cognitively-powered decision-making. WDP provides a self-service task-oriented environment for teams of data scientists, data engineers, and other professionals to collaboratively develop, iterate, and deploy sophisticated artificial intelligence and advanced analytics.
As an integral component of WDP, IBM Data Science Experience (DSX) is central to the productivity-boosting benefits of this cloud-based development platform. Already widely adopted in the data science community, DSX provides:
- Integrated workbench: DSX is interactive, cloud-based, scalable and security rich user interface for consolidating open-source tools, languages and libraries and for team collaboration to rapidly put high-quality data science applications into production. It provides built-in connectivity to diverse data sources as well as simplified data ingestion, refinement, curation and analysis capabilities
- Extensible architecture: DSX provides an extensible architecture for accessing open-source tools and libraries—including Spark, R, Python and Scala—as well as solutions from IBM and IBM collaborators such as RStudio and Continuum Analytics, and others.
- Collaboration environment: DSX is a unified environment for data scientists and other analytics developers that allows them to connect with one another while accessing project dashboards and learning resources, forking and sharing projects, exchanging development assets (datasets, models, projects, tutorials and Jupyter notebooks) and sharing results.
With WDP and DSX as core offerings, IBM is a leader in collaborative, self-service environment for secure data-science exploration, visualization, and modeling. As such, IBM is pleased to welcome other solution providers into this fast-growing solution segment. Given the central role that Apache Spark plays in these environments, IBM would like to point out the depth of our ongoing commitment to this and closely related open-source initiatives serving the data science community.
You can learn more about Apache Spark and how to use it within your enterprise by following these Spark Technology Center resources. You can also learn more about data science engagements by visiting the online resources for DSX and WDP.