Visualising in pairs – growing data visualisation skills through mentoring

The Data Visualisation Accelerator programme was first launched in June 2021 and is now accepting applications for its second cohort, until 11 February 2022.

The programme meets the increasing demand for data visualisation mentoring and builds on the highly successful Data Science Accelerator model that has supported over 300 participants since 2015.

Participants work on a data visualisation project that will benefit their organisation, with the support of an experienced mentor in the field. This increases the mentee and their organisation’s data visualisation ability, but also the mentor’s technical, mentoring, and coaching skills.

Maria Jacob (Higher Statistical Officer at the Department for Transport) and her mentor George Wood (Data Scientist, Cabinet Office) were among the first participants on the programme. In part two of our Accelerator blog series, they talk about their mentorship experience, and how the benefits of the programme are already being realised across the UK public sector.

Here, Maria summarises their Accelerator project:

“I developed a dashboard to visualise and share large datasets with local authorities and their contractors. I wanted to come up with a minimum viable product which ended up using R and Shiny.”

Remote working has been the norm for many in the last two years. This can be daunting when learning and building an effective working relationship. Maria and George shared some of the tools they used to help establish their mentoring relationship.

Maria: “We used Microsoft Teams for catch ups and Github to share code. We were also able to meet in person occasionally and code together when restrictions allowed. That was a lot of fun, as well as being educational.”

George: “Meeting in person was useful because it allowed us to do pair programming. However, most of our work was done remotely, and we shared screens a lot. Even when we were working on different things, we stayed on our Teams calls to replicate that feeling of being in a shared working environment.”

One of the biggest challenges of the Accelerator is overcoming unforeseen challenges quickly, to make the most of the limited time available. Maria and George shared how they tackled the challenges they encountered.

Maria: “Time management was my biggest challenge. Good diary management, planning my week flexibly, spreading my learning and development time flexibly over the week to prioritise other commitments, and good communication with my line manager all helped manage the demands on me.

My mentor also supported me with ideas on how to manage the large dataset and how to make code more efficient. Colleagues in my department also gave alternatives on packages to help with optimisation.”

George: “Maria’s Minimum Viable Product goals for her team were clear even if the solutions to the challenges were not. Maria could have taken the easy route by using existing, familiar proprietary tools but by using R and open-source packages, she created a product that was extendable and reproducible in the long-run.”

The Accelerator programme doesn’t just benefit the mentee. Even when coaching and mentoring others, mentors are learning and developing skills themselves. So what did Maria and George get out of their mentoring relationship?

Maria: “Even before the accelerator I really enjoyed coding, so this project gave me a chance to use those skills and improve them. I had no experience of Shiny or dashboarding which I thought would be useful in my current role.

George also encouraged me to do what would be useful to me in my career in the long term. While I was used to coding, I was not using a lot of coding best practices, so George demonstrated how to set up code so others could collaborate with me and how to make it more readable.”

George: “Maria was clear what she wanted out of the mentoring relationship from the start, which is really the best characteristic that a mentee can have!

This was my first experience formally mentoring someone, and I’ve realised that I didn’t need the perfect set of skills or knowledge. My previous experience combined with dedicated time on the project was enough to support Maria. She picked up new skills so quickly that I was often learning from her about how to use Shiny with large datasets. As someone with an interest in transport data, this was a great project for me to mentor on.”

The mentor and mentee’s organisations can benefit from the time they invest in the Accelerator programme. So how did it benefit the Cabinet Office and Department for Transport?

Maria: “I changed roles while I was on the Accelerator, but there is already a need for dashboarding skills in my new role so my current team benefits from my knowledge on how to visualise data!”

George: “I’ve started to look at how I can use these skills to train up other analysts through formal learning opportunities and building a data-oriented community within my directorate. I have also been evangelising the Accelerator throughout, so hopefully more people from my department will apply this year!”

If you’re considering applying for the Data Visualisation Accelerator programme, Maria and George have some advice to help you.

Maria: “Apply for something that is really going to challenge you. That gives you the opportunity to develop the skills that are lacking in your team. For me, this was figuring out how to visualise large datasets. Our teams could create dashboards, but don’t work with large datasets and hadn’t developed tools that considered dataset size.

The Accelerator is more than just time to do a project. You have a mentor whose experience you can use and the support of your fellow participants whose trials, errors and successes you can build on. Use all of that.”

George: “If you want data science or data visualisation mentoring experience from outside your own organisation, the Accelerator programme is for you. As a mentor, you develop the soft skills of professionally supporting someone through listening, collaborating, and providing constructive feedback, but like the mentee, you are still continuing to develop your own technical skillset.

Don’t worry if you’re not sure if you are technically “qualified”. If you’ve worked as a government data scientist or data analyst long enough, you can help mentees – relaying your experience alone can be invaluable.”

Both Accelerator programmes are open for applications until 4 February 2022 (Data Science) and 11 February 2022 (Data Visualisation), respectively. Visit the Accelerator page on Gov.UK for more information and to apply or contact the team.

The Accelerator programmes are delivered by the Campus and the Analysis Function on behalf of the Government Data Science Partnership (GDSP).

In our final blog post we will hear from a mentor and mentee who took part in the pilot of the International Data Science Accelerator programme. It launched for its first full round of applications on 31 January 2022, adapting the successful model of the UK Data Science Accelerator programme. It is already making a significant impact on data science skills and capacity internationally.

You can also read part one of our Accelerator blog series, where Daniel O’Callaghan (Forestry Commission) and Sam Taylor (DWP) talk about their mentoring relationship and how that helped to deliver a successful data science project.