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Can you tell us a bit about your background and career to date?
I went back to school when I was 21 and pursued a graduate degree in Business Information Systems at UCC. My career began with roles in software organisations, primarily as a Business Intelligence (BI) developer. I then gained experience working on various technology projects in different industries. A few years later, in 2020, I joined KPMG, focusing on the implementation of data analytics.
In your opinion what technologies are likely to be disruptive over the next 18 months?
From an analytics perspective, we’re seeing applications like Microsoft Fabric emerge. It’s a unified data platform with a single interface for all your analytics needs – building data warehouses, data pipelines, generating reports, and so on. Accessing structured and unstructured data sources from a single platform is a game-changer. I expect other vendors to follow suit and develop similar unified platforms. These solutions will become increasingly common, and organisations will invest heavily in them. Microsoft Fabric’s integration with their Copilot offering is a prime example of leveraging existing technology for further advantage.
Could you give us a high-level perspective on the type of project work the analytics teams are engaged with at the moment?
I work in a division of Management Consulting named Connected Technology. We provide services across IT advisory, Cloud & Digital Transformation, IT Infrastructure & Operations, Tech enablement, as well as Data & Analytics. There are around 200 people, of which approximately 40 are data analytics professionals. We are involved in a wide range of analytics initiatives from data architecture review and advisory, to the design and implementation of data solutions both on-prem and in the cloud, helping clients to migrate their data reporting infrastructures to the cloud, all the way through to large digital transformations programmes which include a significant analytics footprint.
How far along are companies in general with their analytics or technology journey? Because technology is moving so fast, are organisations trying to catch up with it, or are there some organisations that are getting ahead of the pace?
Most organisations are playing catch-up, but some are extremely far ahead. For example, at a recent analytics conference, a CTO from one company shared their impressive journey. They’re a data-driven organisation, enabling users to perform self-service analytics. The infrastructure and capabilities behind their data usage were remarkable, positioning them as a leading entity. However, the rapid pace of change makes it challenging to develop and stick to a strategy. Often, the difference lies in leadership. Do you have technology-focused leaders who champion these initiatives or those lagging, hindering progress? To me, that’s a critical factor.
How do you see AI impacting the analytics field over the coming years?
Generative AI tools are poised to significantly affect analytics. Take GitHub’s Copilot, a successful example – it’s fundamentally changing how software developers work by automating parts of coding. I expect similar trends in analytics with the integration of these “general-purpose” AI plugins into analytics toolsets. However, it’s crucial to understand both the strengths and limitations of these tools. Just because you can use a generative AI tool for a task doesn’t mean you should. A strong understanding of what you’re asking the tool to do is vital. For example, an analytics user might leverage a generative AI plugin to quickly create a data extract. However, without understanding the underlying data structure and relationships, the generated query might be highly inefficient. This highlights the importance of human expertise when working alongside these tools. It’s the combination of AI capabilities and human understanding that will drive success in the evolving world of analytics.
What are the main challenges you face in attracting and retaining top analytics talent?
The analytics job market is fiercely competitive. Organisations increasingly recognise the value of data and are actively seeking skilled professionals to unlock its potential. This has driven up competition for talent significantly. Offering stimulating work that utilises the latest tools is crucial. Additionally, providing flexible work arrangements is no longer a perk, but a standard expectation for many information workers. While the market has changed, the core needs haven’t. Interesting projects, cutting-edge tools, and flexibility – these remain the cornerstones of attracting and retaining top talent.
What advice would you give to people aspiring to be a Leader in Analytics/Data Engineering?
I don’t often give advice, but there’s one approach that’s served me well: surround yourself with people who impress you. Early in my career, I actively sought opportunities to work with highly skilled individuals. These weren’t just technically strong people but also demonstrated strong leadership qualities. By working alongside them, I learned valuable lessons and grew significantly. With regard to people management, it’s important to treat everyone equally and fairly. In essence, be sound!