Big Data Education

I recently read, Big Data Education: 3 Steps Universities must take

Here are the 3 steps listed:

  1. Data Science cannot be an undergraduate degree
  2. A graduate degree should contain math, stats and computer science
  3. Research

Step 2 seems obvious. Math, stats, and computer science are some of the key areas for data science. I would add communication and presentation skills to the list because people with just math, stats, and CS skills are not known to be naturally good communicators. I agree with step 3. More research needs to be done, but most of the research will need to be interdisiplinary. Universities need to put more effort into interdisiplinary research.

Step 1 confused me a bit. The argument was data science has too many necessary skills and an applied focus area. Of course a person cannot learn everything about data science in an undergraduate degree. Earning a computer science degree does not mean you will know everything about computer science. It just means you know the fundamentals about algorithms, architecture, and operating systems. You know enough about computer science to understand the field and learn more as you go. I think 4 years should be enough time to do the same for data science.

What are your thoughts?

Advertisements

About the Human Face of Big Data

To start, here is a nice quote from the video. The quote is from Eric Schmidt of Google.

From the dawn of civilization until 2003, humankind generated 5 exabytes of data.
Now we produce 5 exabytes of data every two days.
…and the pace is accelerating

Rick Smolan provides a good talk. He is behind The Human Face of Big Data project. I don’t have a copy of the book, but it looks really intriguing. The talk briefly explains what the book/project is all about.

Interactive Data Visualization for the Web – Free Online Textbook

Interactive Data Visualization for the Web – OFPS – O'Reilly Media is an open textbook for using D3, a javascript library, to merge the following practices.

  1. Data Visualization
  2. Interactive Design
  3. Web Development

The book is in early release and all the sections are available. You are also welcome to comment on any part of the book to help make it better.

Cleaning out an old project

While working on Data Science 201, I was cleaning out some old projects. I found this one interesting, especially since the Christmas shopping season has started.

I named it 34 and More and put it up on Heroku. All it does is query the Google Shopping API and return the results. It works best on very specific queries. Here is an example result for “samsung galaxy player”.

The code is available on Github with an MIT License so you are free to do whatever you want with the code.

Sorry this post does not have much if anything to do with data science.

3 Key Missions For Data Science

Tim Estes, CEO of Digital Reasoning, provides a challenging talk at Hadoop World Strata 2012. Tim challenges Data Scientists to quit focusing on displaying advertisements and start focusing on the following 3 missions.

  1. Security And Freedom of the World
  2. Financial Risk
  3. Health

Take 15 minutes and watch the video. Then be inspired to go change the world.