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
Analytics enables banks to comply with regulations and reduce the risk of fraudulent practices in four major areas. These innovation-driving areas include identifying suspicious transactions, staying within the law to uncover predatory lending practices, defending against online threats and
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
Consumers want their banks to know them well, and they are more than willing to partner with their financial institutions to help that happen. But many banks are finding that businesses such as Amazon, Google, Uber and AirBNB are meeting consumers’ desires better than they are, even though
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.
Technologies are much better than they were previously. In the past, we'd know when an event had happened. Now, problems related to events can be anticipated. For an interactive demo and purchasing information: http://ibm.co/insight-for-banking
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.
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.
Scientists are using predictive weather data capabilities to analyze and forecast storm paths with increasing accuracy. They’re tapping into data from a variety of sources for information, and these developments and applications of data analytics help keep communities in the paths of oncoming
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
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.
Data scientists and others often encapsulate big data by its dimensions known as the four Vs: volume, variety, velocity and veracity. But when considering big data as a source for insight to enhance decision making, it may be best characterized by its three Cs—confidence, context and choice—with