Most organizations start their data governance journey by asking how to track where data comes from and where it goes.…
Every enterprise is being told to go agentic. Meanwhile, the platforms holding your most critical business data are tightening control…
Two toolchains, two skill sets, two CI/CD pipelines — that has been the reality for data engineers working across batch…
Confluent and Databricks enable a modern data architecture that unifies real-time streaming and lakehouse analytics. By combining shift-left principles with…
Modernizing legacy systems doesn’t have to mean a risky big-bang rewrite. This blog explores how the Strangler Fig Pattern, when…
Discover when Apache Flink is the right tool for your stream processing needs. Explore its role in stateful and stateless…
This blog explores Cardinal Health’s journey, exploring how its event-driven architecture and data streaming power use cases like supply chain…
Data integration is a hard challenge in every enterprise. Batch processing and Reverse ETL are common practices in a data…
Data streaming unifies OT/IT workloads by connecting information from sensors, PLCs, robotics and other manufacturing systems at the edge with…
The integration between Apache Kafka and Snowflake is often cumbersome. Options include near real-time ingestion with a Kafka Connect connector,…