Welcome back to the round-up, an overview of the most interesting data science, statistics, and analytics articles of the past week. This week, we have 4 fascinating articles ranging in topics from data scientists types to data collecting music apps.
In this week’s round-up:
- What Kind Of Data Scientist Are You?
- Evernote’s Three Laws of Data Protection
- Big Data Analysis Drives Revolution In Travel
- Samsung and Jay-Z Accused of Using New Album to Mine Customer Data
Our first article this week is a Fast Company piece about the new ebook our very own Harlan Harris, Marck Vaisman, and Sean Murphy authored. The ebook is about how there are actually multiple types of data scientists and the different combinations of skills and experience each type tends to have. The article provides some overview, some excerpts and graphics, and a link to the ebook as well.
This is a Smart Data Collective article about Evernote’s stance on data protection and how it differs from other companies. Evernote is one of the most popular note-taking apps on the market, essentially letting you keep a copy of your brain out in the cloud where you can access it from anywhere and remember things your real brain may have forgotten. That being the case, the privacy of their users’ data is of great importance to them.
Our third piece this week is an InformationWeek article about how data is revolutionizing the travel industry. We’ve all had to endure the frustrations that often come along with getting from point A to point B. This article highlights several companies and explains how they are using data to operate more efficiently and improve customer experiences.
Our final piece this week is a Time article about how Samsung and rapper Jay-Z offered early access to Jay’s new album Magna Carta Holy Grail through an app on select Samsung mobile devices. The intent seemed to be for them to be able to collect some data about the types of customers that would want access to the album before the official release date. This article describes some of the data the app requested and talks about how this has raised some eyebrows about why they would need to collect the type of data they are collecting.
That’s it for this week. Make sure to come back next week when we’ll have some more interesting articles! If there’s something we missed, feel free to let us know in the comments below.
Read Our Other Round-Ups
- Data Scientists, Startups, Big Data Leaders, and Einstein
- Industrial Internet, Business Culture, Visualization, and Beer Recommendations
- Computer Vision, Machine Learning, Benchmarking, and R Packages
Latest posts by Tony Ojeda (see all)
- Natural Language Analysis with NLTK on October 25th - September 8, 2014
- Building Data Apps with Python on August 23rd - July 24, 2014
- High-Performance Computing in R Workshop - May 27, 2014