Summary
TL;DR check out the dashboarrd I crerated here.
The report is based on the Stack Overflow Developer Survey 2019 and a small dataset from the GitHub Jobs API. The conclusions and study of this report is done after an extensive cleaning, exploration and evaluation of the data using Python and Jupyter notebooks.
It covers what languages, databases and frameworks developers opts for now and in the future. The primary target group for this report is HR departments employing engineers and developers. The secondary target group is potential clients buying consultants that could challenge the technical choices the consultants make.
The report provides the reader with good insights and trends on popular languages, databases and platforms, as well as some suggestions on what could be explored further in order to get a richer and more accurate picture of the question at hand.
Key take-aways are that fullstack tech seems to be what developers in the survey loves. The also are deeply into open source languages, databases and platforms. However, the demographics in the survey shows a tilt towards a younger crowd, which might imply that they work for start-ups/smaller companies, rather than for older more established companies with a more evenly distribution of aged on developers and engineers.
When checking if the demand for developers and engineers against what they prefer to do there are som gaps. Although the dataset is small, there are room for further analysis.
On a final note the gender in-equality is striking with a mere 7 % of the respondents being women. For companies finding the way of attracting more women and to get them to stay within the business there might be good gains branding wise and not to say the least by adding new perspective with a more diverse workplace.
Introduction
This report is based on the Stack Overflow Developer Survey 2019 dataset and a subset of information from the GitHub Jobs API. It covers what languages, databases and frameworks developers opts for now and in the future. The primary target group for this report is HR departments employing engineers and developers. The secondary target group is potential clients buying consultants that could challenge the technical choices the consultants make. The report provides the reader with good insights and trends on popular languages, databases and platforms.
Methodology
The report is based on two datasets:
- Stack Overflow Developer Survey 2019
- GitHub Jobs API
The data was collected by downloading a database with the survey and accessing the API to extract information from GitHub Jobs API.
The data has been cleaned, explored and evaluated using Python and Jupiter notebooks.
Programming language trends
Findings
- Typical full-stack languages are trending, such as JavaScript, HTML/CSS, SQL and Python.
- This correlates with well with the most popular web frameworks used.
- Trending languages are often used in start-ups and for new web based applications.
Implications
- The competition for good talent within the preferred languages might be tough.
- The in-demand languages fits well with classic tech stacks for start-ups and scale-ups.
- The competition for talent will still be fierce which might drive salary increases even more.
Database trends
Findings
- MongoDB has a rapid growth in popularity.
- PostgreSQL is advancing. Could be due to the fact that it is open source.
- MySQL seems to be loosing ground. I would be interesting to dive deeper into why.
Implications
- Having products and/or clients that are open to follow the interest and the latest trends when it comes to databases could be crucial in order to keep and attract talent.
- The two databases advancing the most are PostgreSQL and MongoDB.
- It is interesting to see the classic database providers response to an increased use of thes databases.
Discussion
When looking at the data in the dashboard it is obvious that full-stack tech is booming. The most in demand languages, databases and platforms are all well known choices when it comes to building start-ups and scale-ups.
Diving into the demographics tab it is clear that the crowd that participated in the survey is fairly young. Or at least the data is skewed towards a younger crowd. Therefore I think that the picture might be more nuanced if the dataset was different or if it had been complimented with older developers.
The hypothesis is that adding a more diverse crowd and re-do the analysis would give a different result.
Overall Findings and Implications
Findings
- Full-stack languages, databases and platforms are booming.
- The survey demographic is skewed towards a younger crowd of developers.
- There are very few women represented in the survey.
- Skills indicating ML, AI, Mobility and Apps is rewarded with high salaries.
Implications
- Web techniques are crucial and there will still be fair portion of hunting to get the right talent.
- The survey would be good off with more and older respondents.
- The gender tilt is an issue that is present within the business.
- The future is already here and well pai
Conclusion
- Open Source languages are souring. Drivers might be:
- ML and AI applications
- The ever increase need for more web applications
- The population of the survey is skewed. Would be good to complement it with older respondents.
- There is a gap between what developers like and what the market are asking for. Might be du to the skewed population in the survey.