[Blog] Building a Scalable Telco CDR Processing Pipeline with Databricks Delta Live Tables - Part 1

[Pat]

Hey everyone! 👋

I wanted to share what I'm working with daily in the Databricks ecosystem and how amazing it is that we can achieve everything within one platform!

Just published a deep dive on building a Telco CDR Processing Pipeline using:
🔹 Delta Live Tables (DLT) - for streaming data ingestion
🔹 Databricks Asset Bundles (DAB) - for deployment automation
🔹 Medallion Architecture - bronze layer implementation
🔹 Unity Catalog - for governance and lineage
🔹 Serverless Compute - for auto-scaling

Part 1 covers the bronze layer - streaming billions of telecom records (voice, data, SMS, VoIP) from Kafka with secure credential management and automated deployments.

Next steps: Silver/Gold layers, DQX expectations, alerting workflows, and CI/CD pipelines for production-ready operations.

What I love most: Everything integrated in one platform - from data ingestion to dashboards to alerts! 🚀

📖 Full article: DLT Telco Part1

💻 Code repo: https://github.com/cloud-data-engineer/data/blob/main/dlt_telco/README.md 

Would love to hear about your DLT experiences and any feedback on the approach!

#DLT #DataEngineering

[WiliamRosa]

Hi @Pat,
tks for sharing!

[Sujitha]

@Pat thank you so much for posting your blog with us! Very insightful 👏

[BS_THE_ANALYST]

@Pat here I was, cup of tea in hand, ready and eager to read the blog, only then did I discover I was redirected to another place that actually hosts the full blog 😔🤔.

Personally, I think it'd be nice for it to be on here, especially if it's dedicated to Databricks, which it is 🙂. If you set and follow that standard, it'll trickle to others. Before you know it, we'll have a thriving spot for blogs. Gotta lead by example @Pat 😎👑.

All the best,
BS

[Pat]

@BS_THE_ANALYST thanks, you are totally right. I have faced some issues with formatting and wanted to push this forward, my Confluent free tier expired :). I will have more time and fix it. Thanks for the feedback.