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This is a profile from the 2022 version of the DataIQ 100.

The latest list is available here.

Steve Neat, GM EMEA, Alation

What has been your path to power?

I have spent the last 35 years working in the software industry helping large enterprises to maximise the return on their IT investments. I’ve always worked on the supplier side, specialising in areas such as CRM, ERP, BI, analytics and database technologies. Over the past six years, I have moved into the data management space and have focused on helping companies to understand the power of data through data cataloguing, governance and data intelligence.

Steve Neat.jpg

What impact has the pandemic had on demand from your clients?

Demand for data transformation has certainly accelerated during the pandemic, predominantly for two reasons: firstly, organisations are having to ask questions they’ve never asked before about business continuity and the impact of lockdown, and they need the right data to be able to refine those questions and reach an answer; secondly, organisations are having to adapt to remote working, which means collaborative solutions are needed to enable data-driven decisions without the organic watercooler discussions in the office. We’re supporting organisations by helping them to collaborate faster while understanding and trusting the data so that they can adapt to this new world of work.

 

Do you get a seat at your clients’ strategic discussions? If not, what will it take to get you there?

Yes, with a wealth of experience, we’re often consulted by clients who are wrestling with the challenge of how to drive a data culture within their organisation and become more data-driven. We advise some of the largest companies around the world on how to embark on their data journey, many of whom are only just starting out on their data transformation. We find that we’re often asked to get involved quite early as cataloguing their data helps them to establish confidence in what data they have and builds a solid foundation before making investments in areas such as data science, AI and advanced analytics.

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