5 Jan

Life at Mesh-AI: Interview with Mike Stypik, Principal Data Consultant

Mike Stypik

Mike Stypik recently joined Mesh-AI as a Principal Data Consultant.

We sat down with him to learn more about his background and what led him to join the Mesh-AI team.

Hi Mike, can you tell us a bit about your most recent data transformation experience?

Most recently, I was involved in a large-scale data transformation at a financial services enterprise. At a high level, the project was focused on building modern data infrastructure, the public cloud (AWS), creating new data capabilities and enabling their teams to use new technologies and ways of working.

Personally, I helped with the data discovery work as well as building out high-performance data systems both on-premise and in the cloud.

How did you get into the technology industry?

I started my career as a sysadmin and operations engineer. But that all changed when I discovered the practice and philosophy of automation, cloud and DevOps! I saw that these were such incredible ways of not only creating immediate business value, but also experimenting at speed and scale.

I’m now just as excited about the new concepts around the data mesh and new ways of building data infrastructure. I think it’s going to be like the DevOps of data, in terms of impact.

Why did you join Mesh-AI?

I was very interested in joining early so I can participate in the creation of an amazing company culture and cutting-edge technical offerings.

Another important point is that many of the people on the team share my interest in modern data systems and ways of working. I have spent many years building various enterprise data systems, not always seeing the kind of success I wanted. But now I believe that the data mesh concept is the best available approach to enterprise data at the minute.

I am also keen to learn more about ML/AI, especially about MLOps and deploying and running models in production.

What makes a good company culture?

It’s really hard to create a truly great company culture.

I would say that the most important thing is transparency from the senior leadership, first and foremost. If the people at the top cannot embody the culture, how can they expect others to?

Next is collaboration. Without collaboration your culture is doomed. The company should make sure they invest lots of resources (time, energy and money) into laying the foundations for collaboration across the business.

Third would be empowering the technologists and subject matter experts to help develop the direction of the company. They know the reality on the ground and it’s crucial that their perspective is included.

How can we make tech more inclusive?

Inclusivity is a long-term project that I think is best supported with widespread education. People need to see, on the one hand, how subtle unconscious biases do affect their decisions and, also, the massive benefits of inclusivity for them and the company.

When it comes to delivering transformation for enterprises, what are you most passionate about?

My passion lies in finding the real problems (not always what people think) and then using best practice to deliver a technical solution that delivers real business value.

I also love enabling the clients’ teams to use those solutions, coaching them in the new technologies and modern ways of working.

What do you think enterprises should be investing in and why?

I think enterprises need to invest more in strong data fundamentals: decentralisation, data infrastructure capabilities, data governance and so on. For my money, the best approach to that is currently the data mesh. Traditional approaches are very limited in comparison.

With those fundamentals in place things like machine learning and artificial intelligence can be implemented as specific use cases within a wider data framework that will make sure there is sufficient data quality and infrastructure capability to support them at scale.

What would your message be to C-levels who are looking to invest in big data/AI projects?

Data is your most powerful asset and it is criminally underutilised! It can enable much better decision-making at all levels of the business, helping it to move in new directions.

But data is an extremely complex problem and must be carefully managed by people who have the right experience and expertise or it will create more problems than it solves!

Thanks, Mike!

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