Tag: opinion

HBR published an opinion post by Andrew Burt, called “The AI Transparency Paradox.” This post talks about the problems that were created by tools that open up the “black box” of a machine learning model.

In my last post on data science career, I heavily promoted the idea that a data scientist needs to find his or her specialization. I back my opinion with my experience and by citing other people opinions. However, keep in mind that I am not a career advisor, I never surveyed the job market, and I might not know what I’m talking about. Moreover, despite the fact that I advocate for specialization, I think that I am more of a generalist.

If you had a chance to talk to me about data visualization, you know that I dislike the use of double Y-axis for anything except for presenting different units of the same measurement (for example inches and meters). Of course, I’m far from being a special case. Double axis ban is a standard stand among all the people in the field of data visualization education. Nevertheless, double-scale axes (mostly Y-axis) are commonly used both in popular and technical publications. One of my data visualization students in the Azrieli College of Engineering of Jerusalem told me that he continually uses double Y scales when he designs dashboards that are displayed on a tiny screen in a piece of sophisticated hardware. He claimed that it was impossible to split the data into separate graphs, due to space constraints, and that the engineers that consume those charts are professional enough to overcome the shortcomings of the double scales. I couldn’t find any counter-argument.

In his blog post Big Data Or Big Hype? , Rick Ciesla is asking a question whether the “Big Data” phenomenon is “a real thing” or just a hype? I must admit that, until recently, I was sure that the term “Data Science” was a hype too – an overbroad term to describe various engineering and scientific activities. As time passes by, I become more and more confident that Data Science matures into a separate profession. I haven’t’ yet decided whether the word “science” is fully appropriate in this case is.

It’s hard to overestimate how I adore StackOverflow. One of the recent blog posts on StackOverflow.blog is “What you need to know to start a career as a data scientist” by Julia Silge. Here are my reservations about that post: