Case Study

Enhances Mission Critical Subscriber Data Performance With Databricks

Discover how Entrada helped a global media company to improve the consistency, performance, cost, and simplicity of their pipeline with Databricks

Client Overview

A leading global media company running a flagship streaming platform faced performance, cost, and reliability issues with its mission-critical subscriber data pipelines.

Challenge

The client used Snowflake for data ingestion and Airflow for orchestration, which led to inconsistent performance, long execution times, frequent SLA violations, and high operational costs – delaying insights to business users for revenue analysis and subscriber trends.

The Solution

Entrada collaborated closely with the client to deliver a multistep program, starting with PoC.

Rewriting Snowflake SQL into Spark SQL

and leveraging the Databricks Photon engine.

Optimizing pipelines with Delta Lake

and adaptive query execution.

Using Databricks Workflows

to simplify scheduling, monitoring, and alerting.

Applying predicate pushdown and file pruning

to reduce data scanned and improve performance.

Summary

Streamlined and accelerated daily ingestion and transformation pipelines
Improved data quality, reliability, and SLA compliance
Enabled timely, accurate business insights
Reduced operational overhead and costs

24%Faster time to value