data-pipeline-monitoring 话题在 GitHub 上没有填写简介，这里按 Star 数汇总最相关的热门仓库。
This dbt package captures metadata, artifacts, and test results so you can detect anomalies, monitor data quality, and build metadata tables. It powers Elementary OSS and feeds the wider context layer used by Elementary Cloud’s full Data & AI Control Plane.
Easiest way to monitor asynchronous data pipelines
Real-Time M-Pesa Transaction Streaming Pipeline built using modern data engineering technologies to ingest, process, stream, and analyze transaction data in real time. Demonstrates event-driven architecture, stream processing, data pipelines, and scalable analytics for fintech applications.
Building a next-generation hybrid data pipeline architecture that combines the power of Microsoft Fabric, Azure Cloud, and Power BI. This pipeline is engineered to tackle the challenges of real-time data ingestion, multi-layered processing, and analytics, delivering business-critical insights.
Logging for pandas
DataBridge Quality Control
This Project demonstrates the Technology shift in Automobile Firm to resolve the data engineering challenge of manual data ops. AWS Cloud Services implemented here as: S3 bucket for lake storage incoming batches, Lambda Python Script for automating the validation function call and Glue Crawler to generate relational table with successful testing.
The OpenWeatherMap Data Pipeline Engineering Project collects real-time weather data from multiple cities, processes it through a robust ETL pipeline, and generates insightful visualizations to reveal patterns and trends in temperature, humidity, and wind conditions
Every thing about designing installing and implementing data pipelines to include kafka zookeeper hadoop If you enjoy my content please consider supporting what I do Thank you.
Analyzed flight delay data using Python and Power BI to identify delay patterns across airlines and airports.
Pantomath — independent third-party profile of a public API surface, by API Evangelist. Pantomath is an AI-powered Data Operations Center that monitors, manages, and automatically resolves issues across an organization's entire data analytics ecosystem. The platform combines 24/7 automated data monitoring, cross-platform data lineage and impact ana