Apache Superset is a Data Visualization and Data Exploration Platform
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Apache Superset is a Data Visualization and Data Exploration Platform
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
Open-source data movement for ELT pipelines and AI agents — from APIs, databases & files to warehouses, lakes, and AI applications. Both self-hosted and Cloud.
Turns Data and AI algorithms into production-ready web applications in no time.
An orchestration platform for the development, production, and observation of data assets.
The Data Engineering Cookbook
Always know what to expect from your data.
🐚 Python-powered shell. Full-featured, cross-platform and AI-friendly.
The Open Source Feature Store for AI/ML
data load tool (dlt) is an open source Python library that makes data loading easy 🛠️
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
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.
Python Stream Processing
Python Streaming DataFrames for Kafka
Clean APIs for data cleaning. Python implementation of R package Janitor
No description provided by the repository host.
The data transformation tool the open-source community deserves.
Open Lakehouse Compute Fabric: an open-source lakehouse platform with Microsoft Fabric Compute Extension.
Free Course : Data, Machine Learning, Deep Learning and AI Engineering, the long way round: the math, the code, the systems and the security. 173 lessons, 166 runnable labs, no shortcuts. Free under CC BY-NC 4.0.
Realistic synthetic events for testing, demos, and pipelines — streamed live or generated in bulk
Reverse ETL for the code-first data stack
Declarative data quality engine. Define checks in YAML, run anywhere.