Has the Data Warehouse Lost Its Luster?
The Rise of AI-Driven Data Warehousing
Has the data warehouse lost its luster? Have dashboards fallen out of fashion? They have, according to Eldad Farkash, the CEO and co-founder of Firebolt. What’s driving sales of the humble data warehouse these days, he says, is a whole new ballgame: Serving clean and correct data to AI models.
The Deconstruction of the Dashboard
For starters, the search for the perfect dashboard is over. "Nobody’s looking for a dashboard anymore," Farkash says. "Everyone is using the same dashboards, but as embeddings within answers, versus starting with the dashboard and looking for the right data."
The New Stack
Companies that placed the data warehouse and dashboard at the center of their enterprise analytics universe were suddenly reconsidering their assumptions and their options. "There is not a single data team out there or a single engineer out there that isn’t sitting right now and rethinking their whole stack," Farkash says. "And I think one of the big changes is the role of the data warehouse within that framework."
The Rise of AI-Driven Data Warehousing
Early in the generative AI revolution, administrators were hesitant to let LLMs loose on their most prized asset: structured data describing customers and transactions. LLMs were lousy at writing SQL, and would make errors or hallucinate the responses to questions. Business intelligence and analytics companies either sought to supercharge the data analyst herself with AI, or created their own intermediate models to compensate for the shortcomings of the language model itself.
The Future of Data Warehousing
But that has changed, Farkash says. LLMs have demonstrated remarkable growth in their capabilities. The SQL itself is much-improved, he says (although you still wouldn’t let an LLM write a massive 50-page SQL query hitting multiple databases). Everyday business questions are capably handled by AI models that can understand nuances in questions, turn natural language into SQL code, submit the SQL to the data warehouse, reason about the results, and then generate a natural language response.
Conclusion
The demand is exploding, and we want to make sure we’re leading with the new thing that’s happening with data warehousing. We’re opening three or four new offices around the globe, moving fast, moving aggressive, moving big.
FAQs
Q: What is driving the sales of data warehouses these days?
A: Serving clean and correct data to AI models.
Q: What is the new ballgame in data warehousing?
A: Serving clean and correct data to AI models.
Q: Is the search for the perfect dashboard over?
A: Yes, according to Eldad Farkash.
Q: What is the new stack in data warehousing?
A: The data warehouse, AI model, and database.
Q: What is the role of the data warehouse in the new stack?
A: The data warehouse is a key component in the new stack, providing fast and accurate data for AI models.
