Happy New Year! 2010 was an amazing year for data science, and we believe that 2011 will truly be the year that data science grows up.
We have a lot to look forward to this year, so without further blather I present to you our top
hopes and dreams for data science in 2011:
New tools will make data analysis accessible to everyone.
You currently have to be able to swing some fly command line fu to really get your hands dirty. We’re already starting to see more libraries that make it easier for programmers to analyze data and more visual and non-programming oriented toolkits .
There will be more public data to play with.
More companies and government organizations will see the value in sharing data, perhaps through contests like Yahoo!’s Learn to Rank Challenge .Individuals will also have more access to data as tools for scraping web data become more accessible and sensors and other hardware become more affordable and easy to use.
There will be progress in tools and techniques for cleaning data.
As tools become easier to use and more data becomes available, there will be more attention paid to developing focused tools and techniques for the tedious process of cleaning data for analysis.
Educational resources will improve.
Data science books, courses and online resources will encourage a wider participation in all things data. Hopefully more open source examples of the practice of data science will make such analysis more approachable to first-time data hackers.
As the tools become more sophisticated, the focus will shift from technology toward discovery.
Much of what was written about data science in 2010 focused on the marvels of modern technology that allow for the analysis of massive stores of data. As these technologies become ubiquitous, more concern will be on the methods of analysis and presentation of findings.
There will be massive growth in data science jobs.
We’ve already seen a huge demand for people with data analysis skills in the last part of 2010, and we expect this to continue into 2011.