We helped an organization move from a messy and risky way of handling vendor files to a modern system that is secure, automated, and ready to scale.
Using Azure Data Lake and Databricks, we designed the entire platform around the Medallion Architecture — a layered approach (Bronze, Silver, and Gold) that cleans and improves data step-by-step as it moves through the system.
With Unity Catalog providing strong governance and access controls, the platform now protects sensitive data, meets compliance requirements, and gives full transparency into how information is stored, transformed, and used across the business.
Problem: Manual Processes, Security Gaps & High Costs
Before this change, the client was struggling with several big challenges:
1. Disconnected File Handling
Vendor files came in through manual uploads, old FTP servers, and other informal methods.
This led to inconsistent data, no tracking, and a lot of effort to manage quality.
2. Weak Security
Sensitive files were stored without proper encryption.
Even worse, decryption keys were shared manually across teams, which is a major security and compliance risk.
3. Environment Mix-ups
There was no clear separation between development and production environments.
As a result, code worked differently in each place, causing errors, failures, and downtime.
4. No Central Data Tracking
Teams couldn’t see where data came from, how it changed, or who accessed it — a serious problem for handling PII.
5. Wasted Cloud Spend
Old data stayed in costly storage because there was no lifecycle management policy.
Our goal became clear:
Build a fully automated platform that is secure by default and compliant by design — without relying on manual work.
Solution: A Secure, Layered and Automated Platform
1. Strong Infrastructure and Separation
We created three separate environments — DEV, UAT, and PROD — each in its own Azure subscription.
Key protections included:
- All traffic stays inside the private Azure network
- Encryption at rest and in transit
- No public endpoints
- Production access only through Service Principals (no direct human access)
This eliminated accidental changes in production and ensured every environment behaved the same.
2. A Structured Lakehouse Using the Medallion Model
We set up a clear data flow that organizes, cleans, and prepares data step by step:
- Landing Zone: Vendors upload encrypted files into their own containers
- Bronze: Databricks securely decrypts and stores raw data
- Silver: Data is cleaned, validated, and enriched
- Gold: Reports and analytics use polished, trusted datasets
- Sandbox: A protected area for experimentation without affecting real data
This system ensures data quality improves with every layer.
3. Strong Governance with Unity Catalog
Unity Catalog became the control center for data security and access.
- One place to manage who can see what
- Permissions down to table or column level
- Automatic tracking of where data flows
To cut cost, raw files are automatically moved to archival storage after 24 hours — a huge saving without losing history.Tier) after 24 hours, ensuring long-term retention at a fraction of the cost.
Implementation Methodology
We followed DevSecOps principles to deliver fast, safe, and repeatable improvements:
- Terraform builds every environment exactly the same way
- CI/CD pipelines deploy all changes automatically
- Key Vault handles secrets and rotates keys safely without downtime
No changes happen manually — everything is documented and controlled.
Results
The new system brought immediate and lasting benefits:
✔ Better Security — No unencrypted data, no shared keys
✔ Less Manual Work — Files flow automatically end-to-end
✔ Lower Costs — Storage auto-tiering stops waste
✔ Compliance Confidence — Audit trails and lineage tracking built in
✔ Room to Scale — Add new vendors and data sources easily
Built to Work Across Industries
This pattern can be reused in multiple sectors:
- Finance: Secure log ingestion for fraud analytics
- Healthcare: PII protection and HIPAA-ready controls
- Retail: Reliable onboarding of large numbers of suppliers
Conclusion
This project shows how Infivit combines security, automation and scalability in real-world solutions.
By bringing together Azure’s strong security features, Databricks processing power and DevSecOps practices, we created a modern lakehouse that is safe, reliable and ready for future growth.