The National Basketball Association is hosting an Analytics Hackathon.
Application are accepted until August 6, 2017 and the actual competition occurs on September 23-24, 2017. The competition has 2 focus areas:
- Basketball Analytics
- Business Analytics
The prizes for winning consist of:
- Lunch with NBA Commissioner
- A trip to the All-Star Game
- Tickets to a game of your choosing
To be eligible, you must be:
- At least 18 years old
- An undergraduate or graduate student
Georgia Tech University just announced a new online master’s degree in Analytics.
Georgia Tech Creates First Online Master of Science in Analytics Degree for Less Than $10,000
The degree will begin in August 2017 and will be fully online. It will offer 3 tracks:
- Big Data
- Analytical Tools
- Business Analytics (coming at a later date)
The 2016 Midwest Undergraduate Data Analytics Competition (MUDAC) will be held at Winona State University in Winona, Minnesota on April 2 and 3.
- What is MUDAC?
MUDAC is an intense 2-day analytics competition aimed at undergraduate students. Teams compete to solve a problem posed by an external organization.
- Who can compete?
Teams of 3 to 4 undergraduate students attending a school in Minnesota, Wisconsin, Iowa, Illinois, North Dakota, or South Dakota
- Why attend MUDAC?
- A fun learning experience
- Friendly competition
- Meet others with similar inteests
- Learn about data science/analytic careers
- Practice preparing and giving a presentation
- Cash prizes for winning
- Door prizes
The competition also includes a panel discussion with some local data professionals. I am honored to be one of those panelists.
If you attend or teach at a university in the upper Midwest and you are interested in data science, you should strongly consider bringing a team to MUDAC. I hope to see you there.
Tomorrow, January 28, 2016, David Smith will present a webinar titled Introduction to Microsoft R Open. David is the R Community Lead at Microsoft. The webinar will discuss:
- Introduction to R
- History of R
- Enhancements of Microsoft R Open (Microsoft’s enhanced distribution of open-source R)
- CRAN Time Machine
- Reproducible Data Analysis
If you are looking to get started with R or get more from R, this webinar will be worth your time.
Plus, the webinar is the first in a series of Microsoft webinars focused on R.
Full Disclosure: I work for Microsoft, and I will be helping (in a very minimal capacity) with the webinar.
The lines between analytics and data science can definitely be very blurry. Different companies might call the same position by two different names, but at their core, they do have some differences.
Below is an infographic from the faculty of the Online MS in Analytics at American University. I think the infographic is accurate.
In my opinion, a true data scientist should spend more time creating and programming new algorithms while a business analyst should spend more time applying existing algorithms.
A couple of notes
- Years of Education are not much different, but the academic disciplines are very different. Data Scientists tend to have degrees with more rigorous mathematical training. For me, this is the biggest differentiator.
- It appears financial institutions prefer business analysts while the government and colleges prefers data scientists
- Surprisingly, Business analyst jobs are projected to grow faster than data scientists (27% to 15%), not sure I totally agree with that!
Know Of Other Differences?
Please, Leave a Comment.
Brought to you by American University’s Analytics@American, a masters in business analytics
A great read for people without an extensive math, statistics or computer science background. And still an interesting read for those people.
The book includes tons of non-technical descriptions for data science terms.
You can download a copy of the book on SlideShare, or you can purchase a paperback copy via Lulu.
Organizations everywhere are racing to build analytics/data science teams. Big Data is everywhere and companies don’t want to fall behind. Unfortunately, many organizations are struggling to get started because of questions similar to the following:
- How will Analytics help us?
- What does an analytics team look like in our organization?
- How do we start?
Luckily, the analytics team at 500px, a photography community site, was kind enough to provide a detailed overview, Building Analytics at 500px, of what really happens when building an analytics team. The overview provides:
- And more
If your organization is considering adding an analytics or data science team, this article is definitely worth reading.
My previous list of Colleges with Data Science Degrees has grown very large, and numerous people have requested the ability to sort and/or filter. Thus, I built a new list. It is available at: Data Science Colleges. As far as I know, this is the most comprehensive list of data science programs available. Here are some of the features it offers:
- Over 200 Programs
- Certificate, Bachelors, Masters, and Doctorate programs included
- Sort and Filter Programs
- US and International
- Program Name
- Online Programs
- Ability to download the raw data as CSV or JSON
Yes, you read that last one correctly. All the data is freely available for you. If you do use the data for something, I would love to know and potentially blog about it.
The list will continue to evolve. If you find any broken links or missing programs, please leave a comment. Also, please leave a comment if you can think of ways to improve the list.
This infographic explains the Three V’s of big data, contains a nice list of analytical techniques, related trends and some other information.
I recently saw the article, The Best Data Mining Tools You Can Use for Free in Your Company. It contains a very brief description of each of the following tools.
- Apache Mahout
See The Best Data Mining Tools You Can Use for Free in Your Company for more details, links, and pictures.