Transforming Data Engineering with DevOps on the Databricks Platform 

Transforming Data Engineering with DevOps on the Databricks Platform - A data pipeline morphing into a sleek, automated production line or circuit pattern

The role of the Data Engineer is rapidly changing, from writing ETL scripts to engineering production-grade data products. On the Databricks Lakehouse Platform, this shift demands more than technical know-how; it requires a DevOps mindset. By embracing software engineering best practices, automated testing, and CI/CD pipelines, data teams can deliver scalable, reliable, and secure solutions. This blog explores how DevOps principles and tools like Git Folders and Databricks Asset Bundles are transforming data engineering into a discipline of continuous innovation and delivery.

Data Strategy Diagnostic: Building a Robust Data Strategy on AWS

Cevo's Data Strategy Diagnostic

Data is everywhere but without a clear strategy, it can hold your business back instead of moving it forward. In this blog, we share how the AWS Data Strategy Diagnostic helps organisations assess their data maturity, uncover gaps, and build a practical roadmap to turn data into real business value.

Deploying an Open-Source Vector Database on AWS – Part 2

In this lab, we will create a Kafka producer application using AWS Lambda, which sends fake taxi ride data into a Kafka topic on Amazon MSK. A configurable number of the producer Lambda function will be invoked by an Amazon EventBridge schedule rule. Therefore, we are able to generate test data concurrently based on the desired volume of messages.

Deploying an Open-Source Vector Database on AWS – Part 1

In this lab, we will create a Kafka producer application using AWS Lambda, which sends fake taxi ride data into a Kafka topic on Amazon MSK. A configurable number of the producer Lambda function will be invoked by an Amazon EventBridge schedule rule. Therefore, we are able to generate test data concurrently based on the desired volume of messages.