Meet Mike McKee, Founder at AI-Powered Data Management Company: Ataccama

Tell us about Ataccama

 

Ataccama is a global, AI-powered, data management company, founded in Prague in 2008 by a group of entrepreneurial technologists. Through our Ataccama data management platform, we deliver data quality, data governance, and master data management solutions to help enterprises profile, clean, and govern their data, ensuring they are ready to maximise the transformation potential of AI. 

In March this year, we were proud to be one of only three software companies to be recognised by Gartner as a Market Leader for Augmented Data Quality in 2024.

 

 

How did you go from professional sports to data management CEO?

 

My first job after leaving ice hockey was banking at Goldman Sachs. I’d talk to the companies who came to us to raise money and get to know their stories, and I discovered that I really wanted to be on the other side of the table with them. After two years, I went to business school to get exposure to a lot of businesses and understand how they worked, and then made the move from the finance side to the tech side. 

There are a lot of similarities between the sports world and the business world – the best teams in both are the ones that really work as teams, not as a group of individual players. I have always focused on bringing that energy to every role I’ve had and worked deliberately to cultivate a strong team player culture. 

 

 

What are the key trends you’ve noticed over the past 6 months?

 

Companies are starting to use generative AI to create business value. 

Beyond the hype, some organisations have now started to incorporate it into their daily operations while others are still exploring how to use it effectively. There’s still a challenge there in the practical implementation of it into specific operational areas, but we’re seeing companies focusing on the questions they need to solve to pinpoint the right use cases for it. 

Data quality is growing in importance.

Often relegated in the conversations around trending technology, the adoption of AI has put data quality firmly in the spotlight. Once the domain of the data function, business leaders are now recognising that the output quality of AI is intrinsically linked to the data it processes.

The advent of unified platforms.

Unified platforms offer a comprehensive solution that balance legacy monolithic systems and add-on single-purpose tools. They address a broad spectrum of data management needs while seamlessly integrating other essential technologies to make the stack more cohesive and user-friendly.

Automation as the only way forward.

In 2024, the mantra for data management is clear: do more with the same resources you have today. This reality is steering organisations towards one inevitable solution: automation. Automation tools can handle repetitive, time-consuming tasks, freeing data professionals to focus on more strategic, high-value activities. 

 AI governance is a key focus.

This is the process of establishing and enforcing rules, policies, and ethical guidelines for developing and using AI technologies. It ensures that AI systems operate fairly, responsibly, and transparently within an organisation and align with data policies and the ethical standards that form the core of corporate and data governance. 

 

What role is AI playing in data management?

 

There are two core areas where AI is used in data management processes: 

Getting data AI ready: organisations need high quality data to feed machine learning models. If bad data is used in model training, the output from AI systems will reflect this and be inaccurate and untrustworthy. 

Data automation: AI is used to streamline data management practices. Data teams benefit from the automation of manual tasks which are usually heavily time-consuming, and business users can use natural language capabilities to be able to work with data without requiring technical knowledge.