There is no shortage of news about the importance of data or the career opportunities within data. Yet a discussion of modern data tools can help us understand what the current data evolution is all about, and it can also be used as a guide for those considering stepping into the data space or progressing within it.
In our report, 2013 Data Science Salary Survey, we make our own data-driven contribution to the conversation. We collected a survey from attendees of the Strata Conference in New York and Santa Clara, California, about tool usage and salary.
Strata attendees span a wide spectrum within the data world: Hadoop experts and business leaders, software developers and analysts. By no means does everyone use data on a “Big” scale, but almost all attendees have some technical aspect to their role. Strata attendees may not represent a random sample of all professionals working with data, but they do represent a broad slice of the population. If there is a bias, it is likely toward the forefront of the data space, with attendees using the newest tools (or being very interested in learning about them).
What did we find?
In a sentence: those who use data tools make more.
More specifically, the tools that correlate with higher salary are scalable and generally open source; they are often script-based or built for machine learning. Those attendees who tend to use one such tool tend to use others––that is, these tools form a “cluster” in terms of usage among our sample. Perhaps just as interesting is that some of the traditional, popular tools such as Excel and SAS were not used as widely as R and Python. This might be food for thought for those data analysts who have thus far resisted learning how to code or moving beyond query-based data tools.
We invite you to take a look at the report, and we hope the methodology will be as interesting as the results. A new survey is available––we are making the Strata survey annual and look forward to sharing the results next time around.