DataOps topic
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.
awesome-dataops
:sunglasses: A curated list of awesome DataOps tools
modern-data-warehouse-dataops
DataOps for the Modern Data Warehouse on Microsoft Azure. https://aka.ms/mdw-dataops.
argilla
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
beast
[Deprecated] Load data from Kafka to any data warehouse. BQ sink is being supported in Firehose now. https://github.com/odpf/firehose
elementary
The dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features.
optimus
Optimus is an easy-to-use, reliable, and performant workflow orchestrator for data transformation, data modeling, pipelines, and data quality management.
SREWorks
Cloud Native DataOps & AIOps Platform | 云原生数智运维平台
meltano
Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.
flyte
Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.