I had a great time presenting my new webinar yesterday, thanks to everyone who attended “The Rise of Data Science in the Age of Big Data Analytics” and especially those who submitted questions. Sorry I didn’t have time to get to them all, but feel free to ask here in the comments.
I had a great time presenting my new webinar yesterday, thanks to everyone who attended “The Rise of Data Science in the Age of Big Data Analytics” and especially those who submitted questions. Sorry I didn’t have time to get to them all, but feel free to ask here in the comments.
There’s been some discussion recently about whether the data scientist will be replaced by tools. Like the author of that article Gil Press, my take is — emphatically — no. Data Science is much more than simply applying machine-learning algorithms to data. It requires knowledge of the domain, understanding means to most effectively communicate results, and above all, the use of the statistical analysis process to be able to forecast the future without being misled by the past. I also make the case that the R language is the ideal enviroment for data scientists to perform that process. I hope I made the argument effectively; judge for yourself in the replay video below.
You can also download the slides and the video replay from the Revolution Analytics webinar archive linked below.
Revolution Analytics webinars: The Rise of Data Science in the Age of Big Data Analytics
