Why Data Quality Should Start At The Beginning, Not The End

Data quality issues emerge from multiple failure points from development practices to production life cycle, each compounding ...
dbta

Building Modern Data Pipelines Using dbt—Tips and Tricks

Earlier this year, I had the privilege of serving on the organizing committee for the DataTune conference in my hometown of Nashville, Tenn. Unlike many database-specific or platform-specific ...
Forbes

AI-Driven Automation: Revolutionizing Data Engineering With Agentic Mesh Architecture

The demand for data engineering solutions is growing significantly. According to a Market Data Forecast report, the global big data and data engineering market was valued at $75 billion in 2024 and is ...
InfoQ

Data Pipelines & Data Mesh: Where We Are and What the Future Looks Like

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...
VentureBeat

Databricks open-sources declarative ETL framework powering 90% faster pipeline builds

Today, at its annual Data + AI Summit, Databricks announced that it is open-sourcing its core declarative ETL framework as Apache Spark Declarative Pipelines, making it available to the entire Apache ...
TechRepublic

A guide to effective data migration testing

Data migration testing ensures that all your data sets and system integrity are maintained when they’re transferred to a different host. Depending on the size of your organization and the work it does ...