Big data analysis generally involves piping large data sets into processing systems such as Apache Spark and Hadoop, walking away for a very long coffee, and returning later to a hopefully successful result. The DevOps and continuous build ecosystem have long employed linters, code analyzers, and application profilers to discern potential trouble and optimization points in code, and Pepperdata wants to bring that practice to the big data world. I spoke with CEO , formerly CTO of Yahoo! and consultant to other data heavy tech companies, about what the company offers and how their customers save hours from running inefficient processing jobs. Ash Munshi Originally published at dzone.com . Opinions expressed by DZone contributors are their own. Join the DZone community and get the full member experience.

Apache

Pepperdata: Bringing DevOps Practices to the Big Data World

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

Untitled Story

5 Docker Desktop Alternatives

The Noonification: Feature Optimization for Price Prediction (11/26/2023)

10 Ways to Optimize Your Database

10 Essential Computer Skills for Data Mining

10 Most Evolving Big Data Technologies to Catch Up on in 2022

5 Docker Desktop Alternatives

The Noonification: Feature Optimization for Price Prediction (11/26/2023)

10 Ways to Optimize Your Database

10 Essential Computer Skills for Data Mining

10 Most Evolving Big Data Technologies to Catch Up on in 2022

Light-Mode

Classic

Newspaper

Dark-Mode

Neon Noir

Minty

HN StartUps