Working in BI in Japan vs Europe: A Data MVP’s Perspective with Bernat Agulló Roselló (MVP)

In the world of data analytics, the journey from being an Excel power user to becoming a Microsoft Most Valuable Professional (MVP) is a path many aspire to, but few navigate with as much international flair as Bernat Agulló Roselló. A senior BI developer and a prominent figure in the Power BI community, Bernat’s story is a testament to the power of curiosity, the importance of foundational knowledge, and the transformative potential of automation.

In a recent deep dive into his career and technical philosophy, Bernat shared how he transitioned from managing factory macros at Nissan to mastering the complexities of DAX (Data Analysis Expressions) and Tabular Editor scripting. His insights offer a roadmap for any developer looking to elevate their skills from basic reporting to high-level data engineering and automation.

[embed]

The Accidental BI Professional: A Global Perspective

Bernat’s career began not in a dedicated data department, but on the factory floors of Nissan. Like many in the industry, he was doing Business Intelligence long before he knew it had a formal name. By using Excel macros to aggregate files and produce reports, he was already grappling with the core concepts of data granularity and attribute storage.

“I thought I only knew macros,” Bernat reflects, “but when I wanted to do this for real, I rebranded all these experiences. I remember reading the Warehouse Toolkit from Kimball and thinking, ‘Oh my god, this is what I’ve been doing all this time. This is the name this has.’”

His journey is also uniquely global. Having lived in the United States, Germany, and Japan, Bernat speaks five languages. This international experience didn’t just broaden his horizons; it gave him a unique perspective on how data communities operate across cultures. For instance, he notes the striking difference between the high number of MVPs in Barcelona versus Japan, attributing it to cultural nuances in how professionals share knowledge and step into the spotlight.

The DAX Epiphany: Why Modeling is Everything

For many transitioning from Excel to Power BI, DAX is the biggest hurdle. Bernat admits that he initially struggled with the same misconceptions that plague many beginners. The most dangerous assumption? Thinking that DAX is just like Excel.

“DAX is nothing without the model,” Bernat emphasizes. While Excel users are accustomed to working with cells and ranges, Power BI requires a deep understanding of filter context and row context. He credits the legendary work of Marco Russo and Alberto Ferrari, the “SQL BI guys”, for providing the logical framework necessary to master the language.

The Importance of the Basics

Bernat advocates for a “basics-first” approach. Many developers try to “Google their way” through a project, copy-pasting snippets of code without understanding the underlying logic. However, Bernat argues that true mastery comes from understanding how CALCULATE modifies the filter context and how the storage engine processes data. Without these fundamentals, developers will inevitably hit a wall when trying to build complex, performant reports.

Mastering Automation with Tabular Editor and C

As a developer who loved the flexibility of Excel macros, Bernat felt restricted by the standard Power BI Desktop interface. This led him to Tabular Editor, a powerful third-party tool that allows for advanced manipulation of the Power BI model. Specifically, he focused on C# scripting to automate repetitive tasks.

One of his most significant breakthroughs involved Calculation Groups. Before they were even natively supported in the Power BI Desktop UI, Bernat was using Tabular Editor to build them. Calculation groups allow developers to reduce the number of measures in a model by applying generic logic (like Time Intelligence) across multiple base measures.

From Manual Work to Scripted Efficiency

Bernat describes the “struggle” of learning the Tabular Object Model (TOM) and C# scripting. His goal was to take the elegant DAX patterns from resources like daxpatterns.com and turn them into automated scripts. Instead of manually creating “Year-to-Date” or “Year-over-Year” measures for every single metric, he developed scripts that could generate these complex structures in seconds.

“I really wanted to replicate the flexibility and power I had in Excel but for Power BI,” he explains. “I kept struggling until I reached the point where I could build whatever I want.”

Cultural Nuances in the BI Community

Bernat’s experience in Japan highlights an interesting aspect of the tech world: community building. He noticed that while Japan has incredibly talented engineers, the “MVP culture” of public speaking and self-promotion is less common than in Europe or the US. This realization encouraged him to bridge the gap, even presenting technical sessions in Japanese during the pandemic.

This cross-cultural communication has not only led to high-level consulting opportunities but has also enriched his understanding of how different teams approach data problems. It serves as a reminder that the “soft skills” of communication and community involvement are just as vital as technical expertise in a successful BI career.

Key Takeaways for Power BI Developers

• Master the Model First: Don’t just write DAX; understand your data model. DAX logic is inextricably linked to the relationships and structure of your tables.
• Invest in Foundational Resources: Bernat highly recommends The Definitive Guide to DAX. Reading it multiple times is often necessary for the concepts of filter context to truly “click.”
• Embrace Tabular Editor: To move beyond the limitations of the standard UI, learn Tabular Editor. It is the industry standard for professional model management.
• Automate Repetitive Tasks: If you find yourself building the same Time Intelligence measures in every report, look into C# scripting and Calculation Groups to save hours of manual work.
• Engage with the Community: Whether it’s through Twitter (X), local user groups, or global forums, sharing knowledge is one of the fastest ways to accelerate your own learning.

Conclusion

Bernat Agulló Roselló’s journey reminds us that becoming an expert is a process of constant iteration. From “accidental” reporting in a factory to scripting complex automation for global clients, his success is built on a foundation of deep technical curiosity and a willingness to share knowledge. By focusing on the core principles of data modeling, embracing advanced tools like Tabular Editor, and engaging with the global community, any Power BI developer can transform their workflow and deliver more impactful, efficient data solutions.

As the Power BI ecosystem continues to evolve with Fabric and new DAX features, the lesson remains the same: learn the basics, master the logic, and then automate everything you can.