DataOps
DataOps is an automated, process-oriented methodology, used by analytic and data teams, to improve the quality and reduce the cycle time of data analytics. While DataOps began as a set of best practices, it has now matured to become a new and independent approach to data analytics. DataOps applies to the entire data lifecycle from data preparation to reporting, and recognizes the interconnected nature of the data analytics team and information technology operations.
- GitHub: https://github.com/topics/dataops
- Wikipedia: https://en.wikipedia.org/wiki/DataOps
- Related Topics: open-data,
- Aliases: data-ops,
- Last updated: 2026-06-14 00:07:55 UTC
- JSON Representation
https://github.com/carlos-descalzi/dkide
IntelliJ plugin for editing DataKitchen Platform recipes.
datakitchen dataops docker intellij-plugin java python
Last synced: 06 May 2026
https://github.com/effinchang/integrity-risk-analytics-azure
Cloud-native risk scoring (FastAPI + Streamlit), Azure CI/CD, Responsible AI
azure dataops devsecops fastapi fraud-analytics graph-database pattern-detection procurement responsible-ai streamlit world-bank
Last synced: 08 May 2026
https://github.com/arthurcornelio88/dataops_pipeline
⚙️ Data Engineering pipeline for the MLOps workflow. Automates ETL and feature engineering with Airflow on GCP/BigQuery.
airflow bigquery data-engineering dataops gcp mlops mlops-workflow
Last synced: 05 Oct 2025
