Sean Smart joined Rockborne as a data consultant in November 2022. Prior to joining Rockborne, he completed a master’s of Zoology, specialising in macroevolutionary modelling at the University of Lincoln. Like all Rockborne consultants, Sean went through a 13-week intensive data training course where he learned a variety of data skills, including how to clean, analyse, and explore large datasets in order to extract insights from them.
Sean’s recently put his analytics skills to good use―he was one of the three consultants to work on Harnham’s 2023 Data & AI Salary Guide. Sean and the team (Mohammed Dougramaji and Rachel Nunn) analysed data from over 6,500 survey respondents around the world to garner insights on the state of the data market across the US, UK, and select European countries.
We sat down with Sean to find out what he’s learned from this project, and what advice he has for any new grads wanting to get into the data field.
How was your experience working on the project?
Overall, I found the project very enjoyable. This was my first long-term project and first-time liaising with both internal stakeholders at Harnham and an external firm- fortunately, all stakeholders were very reasonable and responsive to our questions and opinions. The data itself was fascinating and gave me an excellent top-down view of the industry.
What did you find the most challenging? The most rewarding?
One of the most challenging aspects of this product was the sheer volume of data that we had to process (the survey is over 100 questions long) so to keep each response in first normal form there were over 300 columns of data to process and extract for analysis. Getting a foundational understanding of, and interpreting the data proved a challenge.
I think the most rewarding aspect was probably watching the CEO of our company and some of the people from Harnham talking about the results of our work for an audience of around 350 people on LinkedIn Live.
What were some key learnings that you gained from the project?
Real-world experience is always invaluable in the industry, but more specifically I think this project tested our ability to convey the technical results and data insights from our analyses in a way that would be clear to non-data professionals.
Additionally, while we checked over our dashboards before submitting, there were some back and forth and edits throughout the process, which was a learning experience for me. In the future, I may consider creating a checklist of specific things to check for each item when making a dashboard.
In terms of tool-based learning, this project certainly levelled up my Power BI skills, especially using DAX to create new variables from the data and using buttons to streamline navigation and apply complex filters.
How will you take what you’ve learned to your next role?
Looking towards the future, I think long-term project management and communication skills are what will be applicable and beneficial to just about any project I undertake.
Did Rockborne’s training set you up well for this project?
The training at Rockborne gave us a strong familiarity with all the tools we used over the course of this project (Python, Excel, and Power BI).
However, I learned a lot by working on a ‘real world’ project. For instance, one key learning was just how messy data can be―even from something more structured such as a survey, data always requires more cleaning and preparation than you anticipate in order to be standardised for analysis.
Funnily enough, in our training with stakeholder management, the fictional stakeholders were often very vague with their requests and changed their minds often. However, the opposite was true in this project―the team at Harnham had a clear understanding of what they wanted from the final product, this massively minimised the guesswork involved and sped up progress significantly. Though I understand that we were being trained to be able to work with any stakeholders, not just those that have a strong vision of the project.
This project was also far longer than any project we completed in training, I was on this project for 10/11 weeks, but our whole training period was only 13 weeks. Each step in the project was built upon what we had completed previously and sometimes we had to go back and redo certain things, such as recovering columns that we had initially dropped so that we could join different tables. Thankfully, we had detailed records of our workflows and notebooks, so this was not a serious issue.
Anything else you’d like to add?
Whilst our task was always to create the dashboards to facilitate an external company to create the handbook when asked, we were able to give several useful insights as to how the survey could be altered to improve the quality, and hopefully, quantity of the data gathered and how it could be better formatted.
This goes to show that even if your project is one aspect of a larger process, your familiarity with that particular aspect will help you make (hopefully) meaningful recommendations, even if they aren’t necessarily implemented.
Any advice for new grads looking to get into the data industry?
On a project like this, people may come and go throughout the duration, or you may join partway through a project. In situations like this, the ability to effectively communicate with your team and adapt to changing personnel is an underappreciated aspect of success in the industry.
Interested in joining our diverse team? Find out more about the Rockborne graduate programme here.