Machine learning is one of those hot technology categories that has lots of business and technology executives scrambling to see how their organizations can get in on the action. Done right, machine learning can help you create more effective sales and marketing campaigns, improve financial models, more easily detect fraud, and enhance predictive maintenance of equipment—to name a few. But machine learning can also go terribly wrong, making you regret that enthusiastic rush to adopt. Learn about five negative outcomes that are possible if the initiatives are not properly vetted and implemented. Read article…

Learn how 10 leading CIOs are successfully tapping data analytics and machine learning to achieve business goals. Read article…

David Linthicum warns of the pitfalls of a cloud data migration that doesn't address underlying issues with the data prior to a migration that will reduce the ROI. Read article…

Data management experts share suggestions on why we are still dealing with data silos and how to break them down. Read article…

Your AI program should have short-term and long-term goals and milestones. Here's how CIOs can reset executive expectations and deliver results with their artificial intelligence programs. Read article…

An execution engine for Arrow-based in-memory processing, Gandiva brings dramatic performance improvements to analytical workloads. Read article…

Organizations are using data to facilitate digital transformation, making data analytics a booming market. InformationWeek highlights vendors that are addressing enterprise challenges with products for advanced analytics, machine learning, and data governance. Read article…

You'll get more value out of your data projects and programs in 2019, according to five predictions from Forrester Research. Read article…