Trends in Business Intelligence & Analytics for 2026
Key Takeaways:- Learn about the most important trends in analytics and BI for 2026.
- Understand how analysts can evolve their skills and workflows to stay relevant in the age of AI.
- Discover how leaders can build forward-looking analytics strategies that align with emerging technologies and business goals.
Description
The field of business intelligence and analytics is evolving rapidly, driven by advances in AI, automation, and data accessibility. As new technologies reshape how insights are generated and consumed, data professionals must adapt to stay relevant and add value in an increasingly AI-driven world.
In this panel interview, Sameer Al-Sakran, CEO at Metabase, Michael Berthold, Co-Founder and CEO at KNIME, and Hjalmar Gislason, Founder and CEO of GRID, discuss the major trends shaping BI and data analytics in 2026. You’ll learn how AI is transforming the analyst role, which technical and soft skills will matter most, and how executives can rethink their analytics strategies for the year ahead.
Presenter Bio
Sameer Al-Sakran is the CEO at Metabase, a low-code self-service analytics company. Sameer has a background in both data science and data engineering so he's got a practitioner's perspective as well as executive insight. Previously, he was CTO at Expa and Blackjet, and the founder of SimpleHadoop and Adopilot.
Hjalmar Gislason is the founder and CEO of GRID, with their main product being a smart spreadsheet with an interactive data visualization layer and integrated AI assistance. Hjalmar previously served as VP of Product Management at Qlik. He was the founder and CEO of DataMarket, founded in 2008 and sold to Qlik in 2014. A career data nerd and entrepreneur, GRID is Hjalmar’s fifth software startup as a founder.
Michael Berthold is CEO and co-founder at KNIME, an open source data analytics company. He has more than 25 years of experience in data science, working in academia, most recently as a full professor at Konstanz University (Germany) and previously at University of California (Berkeley) and Carnegie Mellon, and in industry at Intel’s Neural Network Group, Utopy, and Tripos. Michael has published extensively on data analytics, machine learning, and artificial intelligence.