Big Thinkers on Big Data
Big Data: What, Why, and How
Is big data the game changer for business it’s claimed to be? Or is it just this week’s hot topic, one more tech meme, nothing to get excited about?
Find out what it is, why it matters, and what you need to do about it from Big Thinkers on Big Data, hosted by TWiT Network’s Sarah Lane. When Sarah talks with influential big data thought leaders, the answers are strategic, practical, and far from predictable.
Sponsored by Intel, Big Thinkers on Big Data is a new series with a fresh perspective and big ideas. Check back for updates, live Q&A sessions, and new episodes. Join the conversation on Twitter by using #bigthinkers.
Forrester Principal Analyst Mike Gualtieri on how to get ready for big data
Big data is driving disruptive change and forcing IT to respond. Mike Gualtieri says when it comes to big data and IT, “run, don’t walk.” Covering data scientists, cloud computing, computing power, data silos, and IT solutions—this episode continuation was built with IT in mind. Big data has specific needs, and business and IT must work together to architect solutions.
LiveRamp CEO Auren Hoffman on the big data revolution driving business competition
Big data isn’t just for big companies anymore, it’s for everyone, says Auren Hoffman, Live Ramp CEO and RapLeaf Chairman. Use the tools that let you know which data informs predictive analysis and which data doesn’t. Customer service is where businesses now need to compete, and big data’s potential for increased personalization makes that possible.
Forrester Principal Analyst Mike Gualtieri on what’s next in
Big data is no buzzword—it’s real, says Mike Gualtieri, Principal Analyst with Forrester Research. It’s driving disruptive change across the economy in businesses such as healthcare, retail, communications, and entertainment. The potential is huge and the time to get on board is now.
Cogito CEO Joshua Feast on big data, human behavior, and business outcomes
Josh Feast, CEO of Cogito, describes how real-time behavioral data from human interactions can help business deliver better customer service and reach operational goals more efficiently. Accurate predictive analysis depends on contextual understanding and strategies that avoid restrictive, proprietary data siloing.