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The Adaptavist Group is a family of companies working together to deliver enterprise software and quality services across the world’s most trusted ecosystems.
Adaptavist has over 30 employees working in data across many different teams. There is a central data team responsible for core reports and dashboards. There are also embedded analysts around the business working closely with stakeholders.
Two of those embedded analysts are Kate Dickinson and James Brogan, who work directly with Adaptavist’s C-Suite for all their data needs. Kate and James sat down with Count’s Taylor Brownlow to discuss how Count has helped them better serve their stakeholders and work better together.
The data stack at Adaptavist includes Snowflake, Matillion, S3, Airflow, dbt, Quicksight, and Count.
When James joined Adaptavist a year ago he had never written any SQL. Like many in his shoes, he started by trying to make sense of queries his colleagues had written. Instead of using an IDE, however, James used the Count canvas:
“I was thrown in the deep end and asked to pick it up right away. It was overwhelming at first, but with Count, I could take the queries Kate had written, explode out the CTEs, and make sense of each part, step-by-step.” - James
Being able to break down complex logic and piece it together with live data helped accelerate James’s learning exponentially.
“I’ve had to train many people before, and I’ve never seen anyone get up to speed as quickly as James. A lot of that is due to James’s hard work, but also how the canvas makes complex SQL so simple, and how easily I was able to jump in and help when he needed it.” - Kate
As Kate worked with James on his SQL, she quickly saw the potential for the canvas to change how she engaged with her wider data team.
“I’m able to jump into a canvas and leave notes, maybe write a few bits of code if someone is stuck. Without Count, I don’t know what we’d do - probably send Excel files back and forth - it would be a nightmare. I’m able to offer much more support in a less intrustive way.” - Kate
Very quickly Kate saw the impact of working collaboratively - the data team was leaving notes and comments in anticipation of their code being looked at. These comments differed from the typical code comments seen in productionalized code which are meant to explain. These new comments asked to verify logic, or for advice. As a result of more input on their code, they were also writing more efficient code.
“I can look at a colleague’s code and see how they approached something and compare it to my own. I can break down each of our queries and see where in my chain I’m being inefficient and learn how they’ve done something efficiently. It’s much better than just being told to follow guidelines - I can see why some approaches are better than others.” - James
Collaboration wasn’t confined to only the data team. Kate and James began using the canvas with the wider business to rapidly prototype reports and answer ad-hoc requests.
“It’s so easy to throw something together that makes sense. I can get feedback from stakeholders before I’ve built something in our BI tool to see if it’s even the right thing to build. So often I change a metric definition or a filter while they’re in there with me which would be impossible in another tool.” - Kate
The effect of this is far less waste. Far less time wasted building dashboards no one looks at, or time iterating on the wrong things, something the wider organization is taking notice of.
Kate has her sights set on how the wider business uses data. Today the data team and wider embedded analysts are still the main way people get information, but she wants to make sure there’s a path for self-service for those that want it.
“I want to use Count alongside our dbt docs as a way to help people understand our data. I want people to see the joining, see how things are coming together in a very visual way that gives them confidence in using the data themselves.” - Kate
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