Susan Walsh is the Founder and Managing Director of The Classification Guru Ltd, a specialist data classification, taxonomy customisation and data cleansing consultancy. She is an industry thought leader, TEDx speaker and author of ‘Between the Spreadsheets: Classifying and Fixing Dirty Data’, and also the creator of the COAT method. Susan was recently listed as one of Engati’s Top 50 Unstoppable Women Leaders, and one of DataIQ’s 2022 top 100 most influential people in data in the UK.
In her presentation at our recent Brighton Data Forum meetup (which you can watch here), Susan shared real-life examples of dirty data and the consequences it has on decision making, reporting, analytics, AI and machine learning. She taught us how to make quick, accurate checks and changes to our own data in excel, regardless of experience level, and explained why data accuracy and maintenance is so important and implement best practices for this.
We caught up with Susan to learn more about her career, the future of the data industry, her tips for those looking to enter the data scene, and more…
Hey Susan, can you tell us a bit about you and the work that you do?
I’m the Classification Guru, fixer of dirty data. I’m super passionate about data quality and at TCG we help organisations classify and clean their data. For procurement teams, we help show them what they are spending and who with so they can negotiate better rates with their suppliers, make cost savings and detect rogue spending. For other parts of the organisation we can clean data for CRM or ERP upgrades or changes, you would be amazed at the number of duplicates, typos and missing information you can find in there!
My team and I do this using a mixture of manual work and automation using a tool called Omniscope. I truly believe you need both to make data clean and accurate.
What’s a moment that helped define your career?
Just one? For me, this year I was listed in the DataIQ100 most influential people in data and that was huge. I’m not trained in data science, analytics or anything else data related, but I’ve earned my experience working from the ground up and to be recognised by my peers was a huge honour and real validation of the work I’m doing.
A turning point for the business was around two years ago when a global client signed up for my services, it was my first large project and kept me in business for the rest of the year, it was a turning point because I knew if I could win one client of that calibre, there would be more…
What piece of advice would you give your younger self?
You are capable of way more than you think, own your successes and focus on what you are good at.
What was the inspiration for your recent talk?
I wanted to push myself out of my comfort zone, I talk a lot about data, but the theme for TEDx was resilience, and I wanted to see if I was not just a good speaker for data, but a good speaker full stop. I think it worked out ok!
I also wanted to share with people that even through the hardest of challenges you can still thrive, but you have to have the right mindset.
In your presentation, you mentioned your unusual career path. How do you feel that your experience has moulded you as a data professional?
I have a much wider view of business and data, I can see how they fit together and can communicate both ways to make sure everyone gets what they want. Plus, in the spend classification world I just know what companies are buying, it’s helps me be more efficient and accurate in my work. And along the way I’ve learned from my many failures which have helped on my current path.
You have made a successful business, a career, a book, and a superhero out of the need/demand for improved data hygiene and data quality. What skills would you advise a fresh young enthusiast, inspired by your successes, to acquire? What pitfalls should they avoid?
Firstly, ignore the stereotypes. You can be any personality you like and work in data, heck I can’t even do maths and yet I’m a data expert! Data is such a huge field, try out different types of roles and see which one suits you best. And don’t feel you have to conform, I’m the only one out there with a pink sparkly background but I don’t care!
I would also always advise starting from the bottom and working your way up. It will make you the best at your job, your knowledge will be superior and you will be able to problem solve the hell out of any situation.
And say yes to every opportunity that’s right for you. Don’t waver just grab it with both arms. Had I not taken this approach I would not have written a book or have a TEDx talk.
What’s your ideal client like?
Possibly not what you might think. Basically someone who is like-minded and fun to work with. That’s it.
What would be a data task that you haven’t yet tackled that you would love to try your hand at?
Just getting my hands on any global company’s procurement spend data would make me happy!
If it could be learned effortlessly, via a magic pill, what data/tech skill would you most like to acquire?
I’d like to be able to code, I just don’t have the time to learn and I’m delegating more of the day to day work each week but I wish I’d pursued that more when I was younger.
The field of data seems to constantly evolve, and quite rapidly at that. What big changes have you already observed in your corner of the field and what new developments are you expecting to see in the near future? (Bonus: Are there any changes that you are hoping to see, even though you are not optimistic they will materialise?)
There’s definitely more roles available in the data space, and a great number of women coming up which is fantastic to see. There’s so much amazing tech but yet we still aren’t teaching them the fundamentals of things like data cleaning properly, and tech won’t work without it.
I’d also like to see more role models in the data space, and not just the stereotypes but those that stand out for being different.
What’s your big tech prediction for 2022?
It’s more of a wish really. And it’s not really a tech prediction but it’s related I promise. I’d like everyone to focus in on data quality, get those data sets accuate and correct before you start your tech/AI/ML process and I promise it will save you a lot of time and stress in the long run!
And finally, Silicon Brighton wouldn’t be here without people like you giving back to the community, so… what does the word community mean to you?
Community is sharing and supporting to me. Whether it’s data, business or personal it’s a place you can go to feel better.
Missed Susan’s talk at the Brighton Data Forum, or want to watch it again? Check it out here…
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