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In this blog, we explore how the introduction of SQL Asset Type enhances the metadata enrichment process within the IBM Knowledge Catalog , enhancing data governance and consumption. Introducing SQL Asset Type A significant enhancement to the metadata enrichment process is the introduction of SQL Asset Type.
Align your data strategy to a go-forward architecture, with considerations for existing technology investments, governance and autonomous management built in. Look to AI to help automate tasks such as data onboarding, dataclassification, organization and tagging.
Global policies such as data dictionaries ( business glossaries ), dataclassification tags, and additional information with metadata forms can be created by the governance team to ensure standardization and consistency within the organization. For the simplicity, we chose the SQL analytics project profile.
Establishing a data culture changes this paradigm. Data pipelines are standardized to ingest data to Snowflake to provide consistency and maintainability. Data transformation introduces dataquality rules, such as with dbt or Matillion, to establish trust that data is ready for consumption.
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