We asked to see your papers, and 2,898 people from 66 countries answered.
Download the raw data in Excel, and you can slice and dice by country, years of experience, whether you manage staff or not, education, and more.
Community bloggers have already started to analyze the results:
- Analyzing Salary with Power BI by Cláudio Silva – He talks about possible issues with the data, and how he filters for salaries under $500k, 25-70 hours per week worked to get to more realistic answers.
- Data Mining the Salary Survey by Lori Edwards – Lori used SQL Server Analysis Services to figure out which dimensions were the biggest influence on your salary. The first one is years of experience, but the rest surprised me as I went down the SSAS decision tree.
- Analyzing DBA Salaries with R by Kevin Feasel – He analyzes cost of living versus DBA salaries and discovers that South Africans make killer money, but Russians aren’t doing so well.
- What Different Databases Make by Kellyn Pot’Vin-Gorman – Kellyn shows how she imported the data into Oracle, and then analyzed the secondary databases people work on, too. (I wondered if anybody was going to do that!) Looks like RDS users make the big bucks.
- Live Power BI Dashboard by Vishal Pawar – Vishal’s blog post shows all kinds of visualizations, gives you a Power BI PBIX to play with, and even lets you work with his Power BI solution online. (Use the left-page links at the bottom of the page.)
- What Should My Salary Be? by Mohammad Darab – In which Mohammad asks, “Who’s exactly making $1.45mm as an analyst?”
- When Does It Pay for a DBA to Have an Associate Degree by Melissa Connors – Holy smokes, 85% of US responders have a degree! Melissa finds some interesting correlations, like the pay gap for T-SQL developers who are looking for a job (vs not looking) is pretty wide, and people working for the State aren’t looking for another job.
- You can be here too! If you write about the survey results, leave a comment with a link, and we’ll edit this post to include yours.
Keep in mind that the data’s only as good as the people who entered it. This was free for anyone to enter, and we didn’t validate their experience, their actual pay stub, or whether they have naked pictures of the boss that they’re using for blackmail. You have to take the data with a grain of salt, and use medians (the middle numbers) rather than averages. (We’ve also taken the liberty of hand-editing and removing specific rows – for example, somebody filled it in $10,000,000,000,000 per year, and that row got removed.)
We’ll definitely do this again next year, and there’s one thing we’ll need your help to figure out: how do we get more granular location data around the world? The problem with open text entry location fields is that people can’t be trusted to put in consistent data. I’d love to have a dropdown box for country, which then populates a dropdown box for state/province, which then lets people pick metro areas. The challenge there is finding a free or open source provider for that data that integrates well into a survey. If you’ve got ideas, I’d love to hear ’em – but remember, they need to be global (not just US), and they need to be free or open source.