Data Science Festival: What makes an effective data team?
It was great to be able to speak at the Data Science Festival in London on April 13. DSF is an annual, week long celebration of data science that culminates in a one-day main event. It’s a place for current and future data scientists to meet, discuss challenges and opportunities and network with fellow data enthusiasts.
The original topic of my talk was “Why high quality data is crucial for your machine learning models.” but I decided at a late stage to widen the talk to “What makes an effective data team?”. You can find the slides here:
You can also find a video of my talk here:
Based on the enthusiastic questions and feedback afterwards, I am glad I opted for the wider topic. In the run-up to the talk, I had some wide-ranging discussions with a handful of Heads of Data from the Snowplow community. I went into these conversations expecting to talk a lot about technology and platforms, but instead I found that these leaders had mostly moved beyond those challenges and were fundamentally grappling with people and culture issues – both inside their Data Team and in the interface between their team and the wider company.
From this insight I started to put together a kind of “Maslow’s hierarchy of needs” for the data team – starting with data availability at the bottom and moving towards a self-actualised team at the top of the triangle. This idea seemed to resonate with the audience – so I hope to keep evolving it throughout the year.
To sum up, it was an exciting talk to give – and hopefully one that provides data scientists with a different lens to view their professional work and interactions through. Thanks Data Science Festival – and my thanks too to Dani Sola at Simply Business, Dejan Petelin at Gousto and Niels Reijmer at de Bijenkorf for their insights which formed the genesis of my talk.