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I can’t help but notice the stark contrast between the excitement generated at industry-leading events and the day-to-day realities of data teams. While I’ve had the privilege of attending numerous data events and consuming an abundance of data-related content, it’s become evident that many of us are still grappling with fundamental challenges. I wanted to spend some time looking at the gap between the glitzy world of data as appears on LinkedIn and industry events, and the practical issues that often take precedence within data teams’ day-to-day.

You cannot deny the allure of data events and conferences. They showcase cutting-edge technologies, awe-inspiring case studies, and the promise of unlimited possibilities with data. Attendees leave these events with a sense of exhilaration, inspired by the advanced techniques and possibilities presented on the keynote stage. However, I think it’s time we confront a harsh reality: most organisations are not engaged in the glamorous work depicted at these events.

In truth, only a select few organisations are delving into the realm of complex models generated from pristine datasets, where businesses willingly hand over their credit card details for data-driven experimentation. While these are exciting prospects, they remain largely elusive for most data and analytics teams. So, why do we continually focus on advanced skills and techniques when many of us are still addressing foundational issues?

Rather than dwelling on the flashy aspects of AI modelling and futuristic data endeavours, it’s imperative that we prioritise resolving fundamental challenges. I know many leaders feel so much pressure from the business to pursue concepts like Gen AI, as they’ve taken the media by storm, and it’s the latest buzzword. I can imagine that pressure can be overwhelming at times. Yet the leaders who are put under that pressure are often the ones whose organisations are still grappling with data governance, struggling to understand the needs of the business, and attempting to establish robust data engineering processes – let alone implementing Gen AI business-wide!

To put it into stark reality, I personally know several companies that are operating with basic tools like Google Sheets and Excel instead of adopting formal data platform systems. That’s what we’re talking about here.

Of course, there’s nothing wrong with working in a centre of excellence and developing very specific use cases for more advanced work. This is where I think the message gets confused. In many organisations, there are pockets of awesome transformation, but that’s exactly what they are. Pockets. Very few are adopting huge and advanced change company-wide.

Now don’t get me wrong, I am not pointing my finger here. The reason we often fixate on advanced concepts is that they garner attention and engagement. It’s sexy. It’s exciting. It’s not the fault of event organisers or content creators; they know their audience seeks stimulation and innovation. (Would also be a bit hypocritical of me too…) However, the problem arises when attendees are left feeling inspired but lack actionable takeaways or, worse, are left feeling isolated while dealing with foundational issues on their own.

With the latter in mind, I spoke with a few data leaders about this challenge, and this is what they had to say…

“I heard a great quote at an event recently about how everybody wants quality data, but nobody wants to do data quality. The current interest at a senior level in leveraging AI got me thinking whether this is the key that properly unlocks the door to investment in DQ. Being responsible for governance of AI along with the governance of our data, I’m hoping puts me in strong position to push the DQ agenda even further by highlighting the risks associated with feeding AIs with data of poor or unknown quality” Mark Beckwith, Director of Data Strategy & Governance, Financial Times


“I love hearing the successes and drivers of others, but as the first Head of Data and Analytics in a 100+ year old organisation, I can say there are some things we are pushing ahead in the chatbot AI space, but much of what our ambition really is (at the moment) is getting good quality data that we can be confident in basing decision on and trust no matter who drew it out of our systems, into the hands of the people who need it, at the time they need it and ensuring it provide relevant insights! This is no small task!” – Katy Gooblar, Head of Group Data & Analytics, Royal College of Nursing


“I feel the focus is so much now on generative AI and it seems to be ‘solving everything’, except that it is not. There’s still lots to still do on getting the data properly governed and increasing the data literacy in the organizations so that more decisions can be based on data rather than intuition and opinions.”Minna Karha, Data Driven Business Lead, Solita


“The ‘overnight’ success of AI is actually the result of a 25-year journey. Amidst the talk of advanced analytics, AI’s true power lies in a combination of strong data management fundamentals and recognizing it as a business, not just an IT initiative, essential for fully embracing the ‘Gen AI’ era.” – Austen King, Data Management Specialist, Datavation


“I can say with 100% certainty that the majority of organisations are still dealing with the day-to-day mundane tasks of building their data foundations rather than working on the sexy, advanced areas.  There’s nothing wrong with that! In fact, getting your house in order will likely get you ahead in the long run. Prioritise building solid foundations whilst innovating in pockets of specific use cases” – Kyle Winterbottom, CEO & Founder, Orbition Group


So don’t worry, you’re not alone. It’s not all AI & Robots, most of it is still Excel and Google Sheets.

About the Author

Catherine King

Global Head of Brand Engagement

Catherine works passionately to provide senior executives with the hottest content and insights in the areas of Digital, Data, Analytics, Information, Business Development & Innovation. She hosts and moderates large events as well as directs, produces, and hosts industry-leading podcasts.

She is an award-winning event prof with a wealth of experience directing and designing Conferences, Bespoke Roundtables, Online events, and more! Catherine is especially passionate about diversity, inclusion, and accessibility work – and is an active ally and advocate for female and BAME leaders. Read more.

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