Apiome Data Profile
Profile any source dataset before you load it — know the nulls, the cardinality, and the PII up front.
Apiome Data Profile is a pre-load profiling and schema inference studio. Sample source datasets to measure null rates, cardinality, distributions, and value patterns per column; detect PII with confidence scores; and turn the results into a draft apiome Class ready to import into the Designer. Understand your data before it ever reaches apiome-db.
What ships with Data Profile
Every Data Profile surface is wired into the rest of the Apiome platform — no glue code, no separate identity, no bolt-on integrations.
Interactive column profiler
A live 3-pane studio showing null rate, cardinality, distribution histograms, pattern frequency, and PII detection for every column.
PII detection
Scan for names, emails, phones, SSNs, credit-card patterns, and IP addresses with confidence scores and masking recommendations.
Anomaly heatmap
Highlight columns that deviate in null rate or cardinality from similar classes already in the tenant schema library.
Schema inference wizard
Convert profiling output into a draft apiome Class + Property definition importable straight into the Designer.
Multi-source connections
Profile from PostgreSQL, MySQL, Snowflake, BigQuery, S3 Parquet, and local CSV / JSON uploads before loading.
Auto-generated quality rules
Derive not-null constraints, format patterns, enum lists, range checks, and regex validators directly from profiling results.
A look inside Apiome Data Profile
Live design previews from the Data Profile mockup pack — 8 surfaces in total.
Detect names, emails, phones, SSNs, credit-card patterns, and IP addresses across every profiled dataset with confidence scores and masking recommendations.
A visual heatmap flags columns that are outliers in null rate or cardinality relative to similar classes in the tenant's schema library.
Translate profiling results into a draft apiome Class and Property definition that imports directly into the Designer.
Use cases
Data Profile is designed around the way real teams actually work — not the way a tool wants them to work.
Sample a new Snowflake table and see its null rates, cardinality, and distributions before writing a single load job.
Catch 31 PII columns — 6 of them unmasked — across incoming datasets and route them for remediation.
Turn a profiled CSV into a draft Class and import it into the Designer instead of hand-typing property definitions.
- Sampling controls and profiling on data that never leaves the source boundary
- Confidence-scored PII catalog with masking policy recommendations
- Cross-tenant schema library baselines for anomaly detection
- Profile run history with lineage back to source connections
- Governed connections via data_source_connections and batch_file_sources
- Classify column semantics and detect PII beyond regex patterns
- Explain why a column was flagged as an anomaly
- Draft a complete apiome Class from a profiled dataset
- Suggest data quality rules from observed value distributions
AI data profiler and schema drafter
Data Profile applies AI to interpret profiling output — classifying columns, spotting anomalies, and proposing the schema so onboarding a new source is a review step, not a manual build.
Every Data ProfileAI feature is grounded in your tenant's data, runs under your data-residency policy, and respects every role and ACL the platform enforces.
Every surface in Apiome Data Profile
A look at the 8 screens designed for this suite — covering everything from day-1 onboarding to day-100 operations.
