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
The future of cognitive computing is bright and Chief Data Officers have the chance to lead the way for their organizations. Not just a science-fiction dream, machines that are experts, expressive, educated, and evolving have the potential to create a stunning reality by driving meaningful market
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
Inderpal Bhandari, chief global data officer at IBM, talks about the many nuances of data, value of analytics and importance of the partnership between the CIO office and CDO office. He also discusses why building a comprehensive data strategy is important for organizations. Check out this CIO
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.
Developers and data engineers’ horizons are broadening with the advent of technologies designed to help them build and deploy analytics applications quickly and easily. Take part in the open beta of the Basic Plan for IBM BigInsights on Cloud to find out what lies in your future as you build
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
Maybe classifying data as structured or unstructured isn’t so simple. What is structured to some may not be structured to others and vice versa. When it comes to the business value of data, consider another way to look at data—whether it is repetitive data or non-repetitive data.
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.
When I spoke with Derek Schoettle, General Manager, Analytics Platform Services, the subject of open source capabilities came up a few times. Data is going to change the culture of business, and in fact it becomes the culture when you truly embrace it.