Problem Statement

Enterprises, modernising to Databricks expect a fast, unified source of truth. However, while aiming to meet the timeline, pipelines remain fragile, governance is patched on later and trust erodes quickly.

Why It Matters

• Cost: DBU spend grows 30–60% due to poor workload and cluster design

  
  

• Risk: Lack of consistent access control or lineage across teams

  
  

• Reliability: Nightly pipeline failures become normalised

  
  

• Compliance: Audits expose missing ownership and controls

  
  

• Velocity: Engineers spend time fixing instead of building

What Cloudaeon Delivers

Cloudaeon modernises end-to-end Databricks, right from Unity Catalog–led governance, workspace consolidation, resilient ingestion patterns, optimised Delta Lake design to FinOps guardrails. The result is a stable, governed and cost-efficient Lakehouse that supports analytics and AI at scale, thereby delivering through a Solution - POD - Ops model.

Ideal For

• Enterprises already on Databricks but struggling at scale

  
  

• Data Platform, Analytics and Engineering leaders

  
  

• Teams blocked on Unity Catalog adoption or cost control

Pain Signals

Most of the teams we speak with notice the following challenges:

• “Our pipelines fail every night”

  
  

• “DBU costs keep climbing”

  
  

• “We can’t roll out Unity Catalog safely”

  
  

• “BI teams don’t trust the data”

Conclusion

I would like to go with the below conclusion: If Databricks reliability, cost or governance are slowing teams down, the platform is no longer serving the business. Modernisation is a decision to stop firefighting and start scaling. The real question is not whether your Lakehouse needs attention, but how long you can afford to run it as-is.

That’s the conversation worth having. Talk to a Databricks expert now.