Driven by Data | The Newsletter, Edition 50!

Welcome to the 50th edition of the Driven by Data Newsletter! The only place to get all your latest updates and insights from the Driven by Data community.

50 editions have come and gone so fast. As of today, we have published 50 podcast episodes, insight blogs and hilarious weekly data jokes, amongst so many other exciting updates, celebrations and launches.

Thank you for being part of the journey!

Let's dive into this week's edition.

Driven by Data | The Podcast

In Episode 17, of Season 4, of?Driven By Data: The Podcast, host Kyle Winterbottom was joined by?Antje Bustamante, VP of Data at?Funding Circle UK

Where they discuss the role of "leadership" in Data & Analytics, which includes, why the fun comes from generating revenue for your business and giving people amazing careers. Why businesses don’t ask for data transformation, learning from personal experience that the Data Leader role is undefined and why titles are often intentionally misused.

Listen now

How to Implement GenAI in Your Organisation

If you missed the LinkedIn Live event with Dr. Raoul-Gabriel Urma & Kyle Winterbottom last week, worry not you can now watch on demand!

Thank you for all the amazing questions that came in comments, it always makes the live sessions far more fun with audience interaction!

Data & Analytics Hiring!

We have some fabulous positions currently open, make sure you've seen the latest listings! If you have any questions about the open positions, be sure to message Natalia Kurasinski today!

Are Grandma’s the answer to the Data Talent Shortage?

This week's insight blog is brought to us by Catherine King

It’s a very common generational stereotype that all grandmothers can sew, knit, crochet, or embroider – in fact, in my own life, I don’t know a single grandmother who can’t do some kind of needlecraft. If you’ve ever had the privilege of watching someone craft, it can look like some form of magic. How they can take basic materials and weave and stitch them into something truly wonderful. The next time you visit your grandmother, look at the bookshelf and I bet you’ll find some form of pattern/instructions for needlework. What you’ll find is nothing short of amazing in terms of language, diagrams and essentially coding.?

So, what does this have to do with the data talent shortage?

I can’t help but feel like we’re continuing to dig on the spot that is well and truly mined. We know where the most traditional forms of talent come from, which universities and courses. There is only so much talent in these spaces to meet the demands of the data and analytics space. With the growth of GenAI, I think we can all be certain this demand is only going to increase. Of course, there will always be a huge need for these traditional routes into data science and engineering etc, but why don’t we apply some creative thinking to these challenges?

Tell me why a textile student who can follow these complex patterns couldn’t be taught Python?

Why couldn’t a sociology student, who is labelling their research with semantic code, be brought into a team to work on data governance models?

A psychology graduate who has a deep understanding of ethics, be brought into a team to work on the latest AI regulation and research?

A lawyer who has spent their career honing their communication skills, leading a data literacy programme?

You see the point I am labouring.

I think too often we have such a traditional view of who a data person is, even now in 2024, that we exclude so many other routes into data. Very often when we have this discussion we talk about the soft skills, but as I’ve mentioned above, I see no reason why the traditional “hard” skills of data can’t be taught and transferable, too.

It would be amiss of me to not mention the DEI element, too. The more routes into the data and analytics field, the more backgrounds we’ll have access to. From ethnicity to gender and social class, suddenly the talent pool reflects the society we serve far better. Which can only be a good thing for competition and social good.

We need to review our hiring practices, and what we need in our team vs what are we in the knee-jerk habit of asking for. So, whilst I don’t expect data teams to suddenly rush out and hire our Grandmas I’d like them to consider what we could learn from them.

That's everything this week, but not before our fiftieth weekly data joke!

Why did the data scientist bring knitting needles to work?

Because they wanted to "unravel" complex datasets, one stitch at a time! ????

Thanks,

Orbition Content Team