Data preparation can be complicated. Get an overview of common data preparation tasks like transforming data, splitting datasets and merging multiple data sources. Image: Artem/Adobe Stock Data ...

Machine learning, or ML, is growing in importance for enterprises that want to use their data to improve their customer experience, develop better products and more. But before an enterprise can make ...

For design engineers, an artificial intelligence (AI) workflow encompasses four steps: data preparation, modeling, simulation and testing, and deployment. While all steps are important, many engineers ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. There's a saying that a messy kitchen is a happy kitchen. However, that concept doesn't ...

Business today depends on data. The ability to efficiently acquire, access, and analyze information is essential to effective decision-making. And better decisions are key to building better ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. AI hype is easy to buy into. But behind the scenes, most enterprise teams are struggling with ...

Big data it is often hyped, but I encourage taking a more realistic stance. I’ve seen many organizations attempt to adopt big data solutions and ultimately fail. I fear these missteps may eventually ...