The Profile job runs statistical analysis on in-scope tables and columns. Profile runs can be scheduled or triggered manually from the asset page.Table-level metrics:
The Performance job queries ACCOUNT_USAGE to surface query efficiency and cost data. This requires IMPORTED PRIVILEGES on the SNOWFLAKE database.
Category
Metrics
Source
Query Performance
Execution time, queue time, compilation time, bytes scanned, bytes written, rows produced, status
ACCOUNT_USAGE.QUERY_HISTORY
Warehouse Compute
Credits used per warehouse per hour
ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY
Storage
Average bytes stored (tables, fail-safe, stage)
ACCOUNT_USAGE.DATABASE_STORAGE_USAGE_HISTORY
Data Transfer
Bytes transferred to external destinations
ACCOUNT_USAGE.DATA_TRANSFER_HISTORY
Access History
User, query, objects read/written, timestamp
ACCOUNT_USAGE.ACCESS_HISTORY
ACCOUNT_USAGE views have a data latency of up to 45 minutes. Performance metrics shown in Prizm reflect the data available at the time the Performance job last ran.
Once Prizm completes its initial catalog and observability runs, every Snowflake table and view gets a unified asset detail page. The Overview tab surfaces the most important signals at a glance.
Section
What Prizm Shows
Quality Score
Overall data quality percentage computed across all active metrics
Status
Review state (e.g., READY FOR REVIEW) and criticality badge (e.g., CRITICAL)
Key Metrics
VOLUME (row count), SCHEMA (column count), FRESHNESS (time since last update), METRICS (total quality metrics defined)
Description
AI-generated or manually verified description of the asset
Semantic Context
Domain, Application, Product, and Tag classifications
Owners
Business owner, Technical owner, and Steward contacts
Audience
Verified statement of who should use this asset
Lineage Summary
Upstream sources and immediate downstream consumers
Conversations
Threaded comments and alert notifications attached to the asset
Context Panel
AI-generated context narrative, context completeness score (0–100%), and freshness timestamps for description, terms, and owner verification
The Attribute tab lists every column Prizm has cataloged for the asset, including its data type, current quality score, alert and issue counts, and the number of quality metrics defined against it.
The Metric tab lists all quality metrics defined on the asset, grouped by type. Each row shows the metric name, the column it applies to, its domain, current score, alert count, issue count, and action controls.
Metric Type
Count
Description
CUSTOM
150
User-defined business rules and threshold checks
DISTRIBUTION
123
Statistical distribution checks (min, max, mean, std dev, percentile ranges)
The Usage tab surfaces per-asset query intelligence derived from the Performance job.
Metric
Description
Total Queries
Total number of queries that touched this asset
Average Execution Time
Mean query execution time in milliseconds
Query Success Rate
Ratio of successful queries to total queries
Total Consumed Credit
Snowflake credits consumed by queries against this asset
Unique Users
Number of distinct users who queried this asset
Unique Warehouses
Number of distinct warehouses used to query this asset
The query log table shows each query with: query text, query date, user, start/end time, status, execution time, and credits used. Queries can be filtered by EXPENSIVE, SLOWER, and POPULAR.
The Lineage tab renders an interactive graph of all upstream sources and downstream consumers. Prizm derives lineage from Snowflake query history and DDL analysis.
Direction
What Prizm Shows
Upstream
Tables and views this asset reads from (e.g., REF_CALENDAR → BRONZE_REF_CALENDAR → SILVER_DIM_DATE)
Downstream
Tables, views, and pipelines that depend on this asset (e.g., SILVER_STG_POS_STORE_DAILY, SILVER_STG_TMS_SHIPMENTS, VW_MONTHLY_SALES, and 28+ more)
Click any node in the lineage graph to navigate to that asset’s detail page. The Overview tab also shows a one-hop upstream/downstream summary for quick reference.
