45 docs tagged with "metadata-lakehouse"

Use Lakehouse to analyze which Atlan features users are adopting and how deeply they engage with each feature area.

Understand the core technologies and architectural components of the Lakehouse platform

Use Lakehouse to measure how deeply users engage with Atlan through pageview rates, session depth, duration, and user tier analysis.

Reference documentation for the ASSETS table, a unified asset registry that serves as the central lookup for all Gold namespace queries

Open, interoperable data lakehouse platform that makes all of your Atlan metadata instantly accessible to power reporting and AI use cases

Understand how automated table maintenance optimizes query performance and storage utilization

Reference documentation for the BI_ASSET_DETAILS table containing BI-specific attributes across PowerBI, Tableau, Looker, and Sigma

Connect Amazon Athena to Lakehouse via AWS Glue Catalog Federation

Connect PySpark to Lakehouse and run your first query

Connect Snowflake to Lakehouse and run your first query

Overview of namespaces, schemas, and tables available in the Lakehouse

Reference documentation for the DATA_MESH_DETAILS table containing data domain and data product metadata

Reference documentation for the DATA_QUALITY_DETAILS table containing all data quality rules and checks

Use Lakehouse to analyze database usage, optimize query performance, and manage storage and compute costs

Step-by-step guide to enable Lakehouse for your Atlan workspace

Step-by-step tutorial to set up and run your first query on the Lakehouse

Reference documentation for the ENTITY_HISTORY namespace containing historical snapshots of asset metadata

Reference documentation for the ENTITY_METADATA namespace containing raw metadata tables for all Atlan assets

Analyse glossary content, including terms, categories, and assigned assets.

Reference documentation for the GLOSSARY_DETAILS table containing glossary, category, and term details

Understand the Gold namespace and how it makes Lakehouse metadata ready for analytics and AI.

Reference documentation for the GOLD namespace containing curated tables for human users and AI tools

Use Lakehouse to run advanced lineage analysis across systems and connectors.

Export complete lineage information from your metadata lakehouse for reuse across impact, dashboard, and root cause analysis.

Use Lakehouse to find all downstream dashboards impacted by upstream data changes.

Use Lakehouse to understand downstream impact before making changes to data assets.

Use Lakehouse to trace upstream dependencies and find the source of data issues.

Use Lakehouse to measure and improve tag coverage and propagation across systems.

Use Lakehouse to measure user activation, churn, reactivation, and cohort retention for a customer domain.

Use Lakehouse to track metadata enrichment coverage across assets and systems.

Reference guide for building metadata enrichment dashboards using Lakehouse data

Use Lakehouse to export rich metadata for AI applications, data marketplaces, and syncing context back to source systems.

Use Lakehouse to identify and consolidate duplicate metrics and glossary terms to keep reporting consistent and maintain a single source of truth

Reference documentation for the OBSERVABILITY namespace containing job execution metrics and data quality scores in the Atlan Lakehouse

Explore practical Lakehouse use cases across metadata quality, lineage, cost optimization, and glossary analysis.

Reference documentation for the PIPELINE_DETAILS table containing data pipeline and orchestration assets

Set up the atlan-lakehouse agent skill to query Lakehouse using natural language in AI agents like Claude Code.

Best practices for querying and using the Gold namespace efficiently.

Reference documentation for the RELATIONAL_ASSET_DETAILS table containing all relational database and data warehouse assets

Frequently asked questions about security controls and access protections for Lakehouse.

Create the LINEAGE table in your warehouse for multi-hop lineage queries on Lakehouse data.

Use Lakehouse to measure daily, weekly, and monthly active users from the usage_analytics namespace.

Resolve common Snowflake errors when querying Lakehouse Iceberg tables and Polaris catalog-linked databases.

Reference for Segment-derived usage analytics tables available in the Lakehouse

Understand the Lakehouse platform and its role as a single source of truth for metadata across your data estate