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
And they said resilience—continuous data access in the face of outages, failures and downtime—across distributed data sources is impossible. Yet the recent IBM BigInsights release offers this capability in its IBM Big Replicate technology. Get an inside look at resilience in an interview with Jim
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.
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
IBM Big Replicate is a replication technology that delivers continuous availability, streaming backup, uninterrupted migration, hybrid cloud and burst-to-cloud, helping meet the most demanding enterprise SLAs across any combination of Hadoop distributions and cloud storage.
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
Spark’s built-in machine-learning library (MLlib) provides a key differentiator from predecessor open source technologies and leverages Spark’s distributed, in-memory execution model. Take a look at some practical applications for specific Spark machine-learning algorithms in three advanced
A world that grows increasingly complex calls for disruptive innovation in an open, collaborative environment. See how open data science provides an ecosystem of expertise, skill sets and advanced open source data science tools that fuels collaborative creativity in the development and deployment