Data science for humans and data science for machines

[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Michael Li on the state of data engineering and data science training programs. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud,Continue reading “Data science for humans and data science for machines”

A brief look at data science’s past and future

[A version of this post appears on the O’Reilly Radar blog.] Back in 2008, when we were working on what became one of the first papers on big data technologies, one of our first visits was to LinkedIn’s new “data” team. Many of the members of that team went on to build interesting tools andContinue reading “A brief look at data science’s past and future”

Business analysts want access to advanced analytics

[A version of this post appears on the O’Reilly Data blog and Forbes.] I talk with many new companies who build tools for business analysts and other non-technical users. These new tools streamline and simplify important data tasks including interactive analysis (e.g., pivot tables and cohort analysis), interactive visual analysis (as popularized by Tableau andContinue reading “Business analysts want access to advanced analytics”

Data Wrangling gets a fresh look

[A version of this post appears on the O’Reilly Strata blog.] Data analysts have long lamented the amount of time they spend on data wrangling. Rightfully so, as some estimates suggest they spend a majority of their time on it. The problem is compounded by the fact that these days, data scientists are encouraged toContinue reading “Data Wrangling gets a fresh look”

Data analysis tools target non-experts

[A version of this post appears on the O’Reilly Strata blog.] A new set of tools make it easier to do a variety of data analysis tasks. Some require no programming, while other tools make it easier to combine code, visuals, and text in the same workflow. They enable users who aren’t statisticians or dataContinue reading “Data analysis tools target non-experts”

Data scientists tackle the analytic lifecycle

[A version of this post appears on the O’Reilly Strata blog.] What happens after data scientists build analytic models? Model deployment, monitoring, and maintenance are topics that haven’t received as much attention in the past, but I’ve been hearing more about these subjects from data scientists and software developers. I remember the days when itContinue reading “Data scientists tackle the analytic lifecycle”