Click here to learn more about author Steve Miller. In last month’s blog, I compared several functions that compute frequencies and crosstabs in R. The ones I’ve worked with primarily, and the foci of Part 1, were table from the base package, xtabs from the stats package, and count from Hadley Wickham’s plyr package. Tests were conducted on a data set […]
The Science of Big Data: The Art of Interpretation
Click here to learn more about Jeff Hirsch. Still think marketing research is more science than art? Allow me to introduce exhibit one, the 2016 presidential election. Lamenting this epic fail in research in The Hollywood Reporter, Michael Wolff went so far to say it was the “day the data died.” That’s not quite right. Big […]
Six Reasons Data Analytics Will Make a Splash in 2017
Click here to learn more about author Jon Pilkington. Looking back over the past year, it is clear that self-service solutions have become widely adopted by organizations across industries, as users want to access and analyze information immediately without having to wait for IT to run a report or provide a database. This trend will continue […]
How We Will Harvest Cognition in 2017
Click here to learn more about author James Kobielus. As we bid farewell to 2016, the entire data industry is focused on cognitive computing as the path forward. We’re all making predictions for how Cognitive Computing’s footprint in our lives will deepen in coming years. One key assumption in everybody’s predictions is that somehow this […]
Social Media Analytics Outperformed the Pollsters
Click here to learn more about author Mark Green. Social Media Analytics Outperformed the Pollsters in the Presidential Election By Mark Green, COO of 4C (www.4Cinsights.com) The polls have been proven wrong twice in 2016 – first in the Brexit vote, and more recently in the U.S. Presidential Election, the two most closely watched and […]
Frequencies in R — Part 1
Click here to learn more about author Steve Miller. I’m often asked to name the most common statistical procedure used in my company’s Data Science work. My answer, only partly in jest, is frequencies and crosstabs — to help with the mundane tasks of profiling and exploring data. Indeed frequency distributions and the dotplots that showcase […]
Coming to Grips with Artificial Intelligence’s Many Manifestations
Click here to learn more about author James Kobielus. Artificial intelligence (AI) is all the rage these days. However, people often overlook the fact that it’s a truly ancient vogue. I can’t think of another current high-tech mania whose hype curve got going during the days when Ike was in the White House, “I Love […]
A Common File Format for Python Pandas and R Data Frames
Click here to learn more about author Steve Miller. I’ve been doing analysis on a Chicago Crime data set off and on the last few of months, using the now ubiquitous Jupyter Notebook to manage my work. Trouble is, I like to switch between data science language leaders R and Python, using the best of each for data munging, […]
Can Data Science and Big Data Improve Design?
Click here to learn more about author Dr. Rahul Razdan. A question for Designers and Data Scientists alike: Can members of the latter empower representatives of the former? Which is to say, can design – a discipline dependent on the artistic ability and the qualitative skills of a given person – become better and more […]
Data Modeling: Why Not 3D?
Click here to learn more about author Thomas Frisendal. Data Models are meant to communicate structure of information to recipients, who need to understand it. But who are these recipients? In fact, they are human beings. Given that, we should choose our means of communication to be the most effective that we can find. Other […]