Sign up for our newsletter and get the latest big data news and analysis.

Keys to a Successful AI Program Launch

In this special guest feature, Jerry Kurtz, EVP of Insights & Data at Capgemini North America, discusses how laying the right foundation early is essential to scale AI programs in the long-term. He provides some key examples of important areas AI leaders should prioritize when kicking off their AI programs to ensure they are positioned to scale in the future.

The One Thing You Don’t Want to Leave Behind on Your Digital Transformation Journey: Your Data

In this special guest feature, Kevin Campbell, CEO of Syniti, argues that digital transformation is data transformation, and for enterprises to have a successful digital transformation, their data transformation must be a priority. Through trust and assurance of data, organizations will set themselves up for more efficient business outcomes, strategic planning, and positive returns.

A Hitchhiker’s Guide to AI that Actually Works for Business

In this special guest feature, Alex Hoff, Senior VP of Product Management & Marketing at Vendavo, believes that if you want an AI or ML solution that will be of any practical use, it needs to be a white-box model that is explainable, interpretable, and it will be both more usable and effective if it allows for human insights and intelligence to be combined with the artificial intelligence and insights – a centaur, or perhaps a cyborg.

How to Move Fast in the Cloud Without Breaking Security

In this special guest feature, Asher Benbenisty, Director of Product Marketing at Algosec, looks at how organizations can solve the problems of managing and maintaining security in hybrid, multi-cloud environments. Also discussed is the common confusion over cloud ownership, and how organizations can get consistent control and take advantage of agility and scalability without compromising on security.

Yes, Data is Valuable—But Much of the Time, It’s Better to Hit Delete

In this special guest feature, Bill Tolson, VP of Global Compliance & eDiscovery at Archive360, discusses the big question surrounding Big Data: when (and how) can information be legally deleted? What’s needed is the right combination of technology and policy.

5 Misconceptions of ML Observability

In this special guest feature, Aparna Dhinakaran, Chief Product Officer at Arize AI, explains five of the biggest misconceptions surrounding machine learning observability. As tools emerge to facilitate the three stages of the machine learning workflow–data preparation, model building, and production–it’s typical for teams to develop misconceptions as they attempt to make sense of the crowded, confusing, and complex ML Infrastructure space.

Mathematical Optimization: A Powerful Prescriptive Analytics Technology That Belongs In Your Data Science Toolbox

In this special guest feature, Dr. Gregory Glockner, Vice President and Technical Fellow at Gurobi, explains how you can get started using mathematical optimization and provides some examples of how this prescriptive analytics technology can be combined with machine learning to deliver business benefits across various industries.

Why It’s Time to Embrace Data Lakes

In this special guest feature, Craig Kelly, VP of Analytics at Syntax, discusses how data lakes can help companies better analyze and use the mounds of data they already store. Data lake technology is helping cutting-edge organizations take control and generate value from their data.

DevOps vs. DataOps: What’s the Difference?

In this special guest feature, Itamar Ben Hemo, CEO of Rivery, discusses commonalities and differences between DevOps and DataOps. Many assume, understandably, that DataOps is simply “DevOps for data.” Although the two frameworks have similar names, DevOps and DataOps are not the same methodology. However, the two frameworks do share many common principles.

Not All Conversational Platforms Are Created Equal; What Makes Virtual Advisors Unique

In this special guest feature, Michele Pini, SVP of Technology at iGenius – the company powering virtual advisor – crystal, examines how a virtual advisor can basically function like another co-worker. By using technology like conversational AI and natural language processing (NLP), advisors have a conversational flow when employees have a question they need answered.