By Stijn Dolphen

Traditional BI has been the cornerstone of business analytics for years, providing data visualization, reporting features and a user-friendly interface. Its integration and governance capabilities have made it a go-to choice for businesses seeking reliable data insights. However, in a data-centric world where speed, flexibility, and predictive analytics are increasingly important, traditional BI tools face new challenges.

BI dynamics

Traditional BI excels in creating dynamic visualizations and offering robust data connectivity and modeling. Its integration within a bigger ecosystem - like Power BI and the Microsoft ecosystem - increases its appeal, providing a seamless experience.

Yet, as the tide of business needs turns towards more agile and intuitive solutions, I've observed areas where traditional BI tools face challenges. While its capabilities are vast, the platform's need for a tailored skillset can be a challenge for some users. Additionally, when it comes to integrating AI and data science workflows directly, traditional architecture often requires more steps, potentially slowing down the insight generation process.

Modern BI

Let’s use a modern BI tool like Hex as a comparison and further explore what is and what it could be for our current modern data stack. So in short, Hex is a modern BI tool designed with simplicity and collaboration at its core. Its intuitive interface and collaborative features allow teams to quickly derive and share insights.

Involving everyone in the data workflow - also known as data democratization - is about breaking down barriers, making data accessible to everyone within an organization, not just the IT or data teams. This is where the concept of self-service BI gains its momentum, empowering users across departments to generate, share, and act on insights independently, without relying on specialized technical expertise.

Data Democratization

Collaboration together with GenAI can simplify the data exploration process, offering an intuitive interface tailored to all skill levels. Collaboration in BI means enabling users to share insights, work on projects simultaneously, and make collective decisions based on real-time data. This collaborative approach not only speeds up the decision-making process but also stimulates a culture of transparency and shared responsibility in data teams.

GenAI isn't just an add-on anymore - it's a transformative tool that enables more natural data interactions, automated insight generation and assistance in generating code. This shift towards AI-driven analytics is a real effiency boost for data teams and we should start making use of it. With GenAI, complex data sets can be analyzed and interpreted through natural language processing, making it easier for non-technical users to query data and receive insights in a format that's easy to understand.

As we integrate GenAI into our workflows, it's important to remember that the skill to interpret and critically evaluate results is key. In this era of self-service analytics, users must be able to recognize the accuracy and relevance of the AI-generated insights. While GenAI democratizes data, ensuring the integrity of insights requires critical thinking.

A modern BI tool like Hex, does already focus on integrating the value of GenAI and collaboration in the data workflow. Next to prompt engineering for generating insights and visuals, you can write and generate code in your prefered language. By allowing people to use either python, SQL or no code at all, you make them comfortable using the data to answer their own questions - regardless of technical proficiency. That is what democratizing data is about, right?


The comparison of modern and more traditional BI is not about switching tools - it's about embracing new trends in business intelligence. Hex represents a move towards more accessible, collaborative, and agile BI tools that can adapt to the rapid pace of data today. This evolution in BI tooling reflects a broader trend towards democratizing data and making advanced analytics accessible to a wider audience.

As we look to the future, the choice between traditional and modern BI tools will increasingly depend on an organization's specific needs, costs and maturity. Both tools can even serve different purposes - they could coexist to support different contexts. Traditional BI remains an excellent choice for complex, enterprise-level analytics. Meanwhile, modern tools stands out as a flexible, user-friendly platform that focus on democratizing data analysis. Not taking into account that cost, security and partner integrations can play a crucial role in determining the best data workflow for your organization.