Скачать или смотреть How Startups Should Build Their Data Stack in 2026

If you're a founder or executive at a startup, how you set up your data stack determines whether you get answers in 30 minutes or 6 months.

Most startups follow the enterprise playbook from 2020: data warehouse, ETL tool, transformation layer, BI tool. Four products, four bills, probably a data engineer to keep it running.

But there's another way: start AI-native from day one and skip all of that.

This video breaks down both approaches so you can decide what makes sense for your stage.

🔗 Links:
Definite: https://www.definite.app/
Connectors: https://www.definite.app/connector-db
Pricing: https://www.definite.app/pricing
Fi (AI Agent): https://www.definite.app/fi

⏱️ Chapters:
0:00 The choice you need to make
0:45 How the traditional data stack works
1:44 The part that surprises most founders
1:56 Why this doesn't work for startups
2:42 The AI-native alternative
3:11 Definite demo
4:50 What AI-native unlocks
5:29 When to use traditional vs AI-native
6:03 The move for 2026

📊 What You'll Learn:
The 4-tool traditional data stack (Snowflake, Fivetran, dbt, Looker)
Why the traditional approach breaks down at startups
What "AI-native" actually means for data infrastructure
When to use each approach based on your stage

💡 Who Is This For:
Founders at seed, Series A, or early Series B startups
Technical co-founders evaluating data infrastructure
Executives who need answers, not infrastructure

#startup #datastack #analytics #ai #founder #dataengineering #snowflake #definite