Summary: Some observations about new major trends and directions in data science drawn from the Strata Data conference in San Jose last week.
Summary: There are an increasing number of larger companies that have truly embraced advanced analytics and deploy fairly large numbers of data scientists. Many of these same companies are the one’s beginning to ask about using AI. Here are some observations and tips on the problems and opportunities associated with managing a larger data science function.
Summary: Recently we’ve been profiling Automated Machine Learning (AML) platforms, both of the professional variety, and particularly those proprietary one-click-to-model variety that are being pitched to untrained analysts and line-of-business managers. Since our first article, readers have suggested some additional companies we should look at which are profiled here along with some interesting observations about who is buying and why.
Summary: The largest companies utilizing the most data science resources are moving rapidly toward more integrated advanced analytic platforms. The features they are demanding are evolving to promote speed, simplicity, quality, and manageability. This has some interesting implications for open source R and Python widely taught in schools but significantly less necessary with these more sophisticated platforms.