Why Most Cloud Data Platform Migrations Fail After the First Year

Most companies don’t fail when they move to the cloud. They fail one year later. The first few months feel like success: ✔ Faster dashboards ✔ Scalable infrastructure ✔ Excited teams But then things start to break: Costs begin to spiral Pipelines become fragile Data trust disappears In this video, we break down why cloud data platform migrations fail over time — even when they seem successful at the start. We cover: The biggest mistake companies make during migration Why “lift and shift” creates long-term problems How cloud cost models silently explode Why lack of governance kills data trust How pipeline complexity grows out of control What successful teams do differently If you're working with platforms like Snowflake or Databricks, this will change how you think about your data architecture. 👇 Who this is for Head of Data / CDO Data Engineers & Architects Analytics Leaders Anyone involved in cloud data platform decisions 🔔 Subscribe for more insights on: Data platform strategy Snowflake & Databricks architecture AI-ready data systems Real-world data engineering lessons 📩Let’s connect If you're dealing with similar challenges or want to discuss your data platform strategy, feel free to reach out at [email protected]