The success of next-generation data science initiatives depends heavily on teamwork from the right mix of application developers, business analysts, data engineers, statistical modelers and other specialists. Discover more about the composition of high-quality data science collaboration through the
Many organizations can capitalize on big data solutions and technologies to make use of expanded volumes of data for enhancing the critical decisions that drive successful business outcomes. And yet, a number of these enterprises can be inhibited from moving big data initiatives forward for a
Joe Caserta is founder and president of Caserta Concepts, a New York–based innovation technology and consulting firm that specializes in big data analytics, data warehousing, ETL and business intelligence. Don’t miss this enlightening discussion between Joe Caserta and IBM data science evangelist
Chris Maddern is cofounder of Button, the leading marketplace for app connections. Before starting Button, Chris led mobile engineering for popular social payments network Venmo and founded several mobile products startups. Learn more in this interview as Chris talks with IBM data science
Join IBM data science evangelist James Kobielus and Dave Saranchak, a data scientist with Elder Research, to discover how Dave develops and applies statistical data modeling techniques for national security clients.
Join IBM data science evangelist James Kobielus as he interviews Jennifer Shin, the founder of data science, analytics and technology company 8 Path Solutions. A recognized thought leader, Jennifer is a data science contributor for the IBM Big Data & Analytics Hub.
A day in the life of data science professionals likely involves navigating the challenges and complexities of sourcing, preparing, modeling, developing and governing data, analytics tools and other assets in collaborative environments. Get a glimpse of the roles that compose data science teams and
Now introducing the “Insight Ops” model. This new model will embrace and enable an agile environment for discovery and exploration and manage the transition necessary to deploy the insight to make it actionable.
To ensure data science success, you need to provide data scientists with an environment that is open, engaging, and fosters collaboration. To explore how your data scientists can access all the open functionality and expertise they’ll need for critical projects, join the new Data Science Experience.
To ensure data science success, you need to provide data scientists with an environment that is open, engaging, and fosters collaboration. To explore how your data scientists can access all the open functionality and expertise they’ll need for critical projects, join the new Data Science Experience
What is the key to staying ahead of the competition? Quite simply, data science. See why innovative companies have embraced the power behind data and analytics to move themselves way out in front of competitors.
In this video, listen as IBM data science evangelist James Kobielus talks with Dean Wampler, a fast data product architect with the office of the CTO at Lightbend, about how data scientists can access the open functionality and expertise that are central to their work.