Interview with Teresa Madej - PowerBI Data Analyst/Product Owner, Ivenium Marketing

You've had an impressive progression through various roles - from MA Specialist to your current position as a PowerBI Data Analyst/Product Owner. How has this diverse experience shaped your approach to problem-solving? 

In each role I’ve held so far, I’ve dealt with various kinds of problems – technical, organizational/operational, or business-related. Every experience helped me develop different skills and gave me a unique perspective on solving problems. Thanks to that, I can approach challenges more holistically – depending on the issue, I reach into my mental toolbox, pick the right skill, and get to work. 

Having worked with the team for over six years, you’ve seen Ivenium grow and evolve. What has been the most exciting or rewarding part of this journey for you? 

Over the years, I’ve worked with many people, but I think I’ll always have a soft spot for those I had the chance to onboard – whether as a teammate or later as a team leader. Watching them grow, knowing I played even a small part in their development, has been the most rewarding part for me. Every time I see their success, I feel incredibly proud and grateful for the opportunity to work with and learn from them. 

From your experience, what are some of the biggest challenges businesses face when implementing data analytics solutions, and how can they overcome them? 

1. Implementing too many technologies before defining key needs, goals, and KPIs – this leads to increased costs and low efficiency/ROI.  This process should be approached like product development – start by clearly identifying the business need, build an MVP, test it, gather feedback from key users, draw conclusions, and only then move toward a full-scale implementation. It’s more cost-effective and leads to better adoption because users are involved from the start. 

1. Chaos and lack of awareness of data sources, poor data quality, and unstructured data.  Again, it’s important to start from the basics – assess your data sources, eliminate unnecessary ones, prevent low-quality data from entering systems, and implement a process for data standardization and automation. 

Many organizations struggle with turning raw data into actionable insights. What strategies or best practices do you recommend to bridge this gap? 

Great question – we know that data is only as good as our ability to turn it into actionable insights. We need to be proactive, not reactive. That’s why long-term, regular analysis is essential – it helps us prevent issues or detect them early on. 

Once business goals and needs are clearly defined (as mentioned in the previous question), reports and dashboards should be designed to answer questions directly tied to those goals and KPIs. Every visualization, table, or calculation should serve a specific purpose in the report. 

After analyzing such a report, we should be able to quickly identify both challenges and highlights. We should celebrate the highlights and learn from them. Then, we can assess potential risks associated with the challenges and determine how to prevent or solve them. Based on an impact vs. effort analysis, we prioritize and define the next steps — and that’s how we turn data into actionable insights. 

Collaboration plays a big role in your work. What do you think makes a team truly effective, especially when combining diverse skill sets? 

Building a team starts with understanding the skill sets, needs, and goals of each member. This way, everyone can contribute efficiently while aligning their tasks with personal growth goals. Work becomes much more enjoyable when we know we’re supporting business goals and shaping our own development path. 

I really appreciate the diversity of skills in my team – each of us has a different background and experience. Working in such a setup helps me grow and provides a sense of security – knowing that my teammates are there to support me. 

What’s your favorite part of working with data - finding patterns, solving problems, or telling stories with numbers? 

Definitely solving problems. Everything around that process is just a tool, and although I enjoy each stage, doing something just for the sake of it doesn’t satisfy me. I like seeing the tangible results of my work and how they impact business needs or users’ daily tasks. 

How do you unwind after a day of working with numbers, dashboards, and automation? 

I need a little closing ritual after work – and that’s always a walk with my dog. It helps me clear my mind, reflect on the day, and think ahead to tomorrow. After the walk, I try to unplug from work completely. Although, let’s be honest – sometimes those great ideas strike unexpectedly! In such cases, I jot them down and revisit them the next day. 

What’s one skill or hobby outside of work that surprisingly helps you in data analysis? 

I’ve always been a left-brained, analytical person, so anything that activates my right brain is a great break for me. Last year, I got back into crocheting and knitting – it’s calming and gives my analytical mind a rest. Though, let’s be honest – there’s a lot of planning and math there too!  

What’s the best piece of advice you’ve received from a colleague or mentor? 

Learn to rest and let go.  Being passionate about your job can be tricky – it’s easy to burn out. Thanks to many supportive conversations with my work besties and my own experience, I’ve learned that maintaining work-life balance is essential to being effective day-to-day. 

How do you stay creative and innovative in your role, especially when working on technical solutions? 

By talking to people who think differently than I do – like my teammates, who each bring something unique to the table. Those conversations always open up new doors in my mind and are super inspiring. I’m really glad I’ve had the chance to work with so many of these people at Ivenium.