// MODEL OPTIMIZATION AND PROMPT SYNTAX TERM
Dagster
A data orchestrator that helps define, develop, and monitor data assets and the computations that produce them.
TECHNICAL DEFINITION
Dagster is an open-source data orchestrator designed for developing, testing, and operating data assets and the computations that create them, providing a unified programming model for data pipelines with strong type-checking and a rich UI (Dagit).
SYNONYMS & ALIASES
- Data Orchestrator
- Data Asset Management
- Dagit
- Data Pipeline Tool
USAGE NOTE
Focuses on data asset lineage and testing, making it suitable for data-intensive ML pipelines.
DEVELOPERS
Organizations developing technology related to Dagster.
The creator and primary developer of Dagster, an open-source data orchestrator designed for the modern data stack and MLOps, enabling robust AI engineering workflows.
Develops a leading MLOps platform for experiment tracking, model versioning, and pipeline visualization, providing direct integrations with Dagster to orchestrate and manage machine learning development cycles for AI engineering.
Offers an ML monitoring and observability platform, providing integrations with Dagster to orchestrate data pipelines for capturing model inputs, outputs, and performance metrics crucial for AI system health and continuous improvement.
Develops an open-source framework for building maintainable and portable data and machine learning pipelines, with an integration that allows these complex workflows to be orchestrated by Dagster for efficient MLOps and AI model development.
Creator of the unified Lakehouse Platform for data engineering, machine learning, and AI. Dagster integrates with Databricks to orchestrate data transformations, model training, and serving for scalable AI applications and prompt engineering data pipelines.
Provides a cloud data warehousing platform widely used for AI and analytics. Dagster offers robust integrations with Snowflake to orchestrate the ingestion, transformation, and preparation of data for large-scale AI engineering projects, including those supporting LLMs.