(This article was first published on R-exercises , and kindly contributed toR-bloggers)
To stay on top of R in the news, we’re sharing some stories related to R published last week. Why Data Science ‘Rock Stars’ Earn Big Salaries (Dennis McCafferty)
Recent post and slide deck related to the 2016 Data Science Salary Survey (O’Reilly Media), with R mentioned as one of the high-demand programming languages (next to SQL and python). “Today’s data scientists in the United States are typically members of the six-figure salary club”. Are you a member as well?
Prediction in the Age of Big Data: The Science Behind Recommendation Systems (Devavrat Shah)
Interesting article by MIT professor Devavrat Shah answering the question “How can data scientists extract meaningful insights and accurately predict customers’ preferences in the age of big data?”. Mentions the RecommenderLab R package.
Microsoft and the ubiquity of data intelligence (Andrew Brust)Short overview of improved R integration in Microsoft Power BI and SQL Server 2016. “with SQL Server R Services, Microsoft has been able to get SQL Server to support the generation of 100 million predictions per second.”
Where Will Data Science Be in Five Years (Anthony Goldbloom / Huffington Post / Quora)Some thoughts by Kaggle’s co-founder and CEO Anthony Goldbloom on the recent past and (near) future of Data Science. Interesting estimates (1.5-3 million) on the number of data scientists (by his definition “somebody using R or Python”) in the world. Compared to 20 million software engineers. BUT: he believes “data science will be bigger than software engineering in the next decade.” Do you agree?
How do R and Python complement each other in data science? (CrossValidated)Oh no… Python vs R, not again! But wait: This lively CrossValidated discussion seeks common ground and focuses on the complementarity of both languages. Are you actually using Python as a complement to R?