Dagster can play an important role in enabling data governance and metadata management in a few ways: Dagster's asset-centric approach provides metadata and lineage about the data assets being produced, which can serve as a foundation for data governance and a "lightweight data catalog". As pedum mentioned, having asset lineage allows visibility into things like data quality, freshness, and runtime metrics. Dagster can integrate with other data governance tools like Secoda.
How does Dagster support data governance and metadata management?
Dagster is an advanced data orchestration tool that can help organizations enable data governance by defining and enforcing policies within data pipelines. Dagster can help with: Data governance: Defining and enforcing policies, managing access, and setting permissions. Data quality: Validating data against rules, performing profiling and statistical analysis, and raising alerts. Workflow automation: Defining dependencies between tasks, scheduling pipeline execution, and monitoring progress.
Metadata attachment
Dagster is a data orchestrator that allows users to attach metadata to jobs. This metadata can be used to track the team responsible for a job, link to relevant documentation, or display the Git hash.
- Data governance: Defining and enforcing policies, managing access, and setting permissions.
- Data quality: Validating data against rules, performing profiling and statistical analysis, and raising alerts.
- Workflow automation: Defining dependencies between tasks, scheduling pipeline execution, and monitoring progress.
Storage options
Dagster storage lets you define how job and asset history get persisted. The information captured includes metadata on runs, event logs, schedule/sensor ticks, and other useful data. You have three storage options: SQLite (the default option), Postgres, and MySQL.
- Data lineage and governance: Providing visibility into data lineage and governance.
- Data pipelines: Creating modular and reusable pipelines.
- Data lakes: Providing a framework for orchestrating workflows, and defining and managing assets.
How can Secoda enhance data governance in a Dagster workflow?
Secoda can enhance data governance in a Dagster workflow by providing features like data search, catalog, lineage, monitoring, and governance. It can connect data quality, observability, and discovery to provide a comprehensive view of the data landscape. Secoda's automated workflows can enhance efficiency and productivity, and its AI can connect to an organization's data sources, models, pipelines, databases, warehouses, and visualization tools. Its data requests portal can streamline the process of data access and usage, and its automated lineage model can enhance visibility into data origins and transformations.
What role can Secoda play in metadata management in a Dagster workflow?
Secoda can play an important role in metadata management in a Dagster workflow.
- Integration with other tools: Secoda can ingest metadata from Dagster and other tools to provide a centralized place for documenting, cataloging, and applying data governance policies across the data assets and pipelines.
- Metadata management: The metadata captured by Dagster about data assets could potentially enable use cases like identifying high cost or inefficient assets that need optimization.
- Empowering AI: As generative AI becomes more prevalent, the asset metadata managed by Secoda can play a role in empowering AI applications by providing context and governance around the data being used.
