How Does SPAN work?
SPAN is a Snowflake-native identity and semantic modeling platform.
It resolves fragmented records into governed identity profiles and transforms them into standardized, business-ready dimensions — entirely inside your data warehouse.
SPAN consists of two core modules:
ID Graph — Identity resolution
Compiler — Semantic layer for metrics and segments
Identity becomes transparent, versioned, and configuration-driven.
Identity Graph
The ID Graph resolves records from multiple systems (e.g., Shopify, Ticketmaster, CRM) into unified profiles.
Each profile is assigned a stable profile_id.
Deterministic Blocking Rules
Identity resolution is defined explicitly in configuration.
Examples:
Email + Last Name
Phone + Zip Code
First Name + Last Name + Birthdate
Each rule generates clusters of related records. Overlapping clusters merge into a single identity.
There is no hidden matching logic.
Overrides
SPAN includes an explicit Override Table to manage edge cases.
Users can:
Merge records
Split records
Assign orphaned records
Overrides are reapplied automatically every time the graph runs.
Snapshots & Lineage
The ID Graph stores historical states.
You can:
Compare graph versions
Inspect cluster changes
Audit identity evolution over time
Identity is versioned and queryable.
The Compiler
The Compiler transforms resolved profiles into structured business attributes.
All behavior is defined in configuration (e.g., c360_config.yml).
There are no hardcoded SQL scripts.
What the Compiler Produces
Four profile-linked dimensions:
Demographics — Name, Email, Phone, Address
Metrics — LTV, Orders, Engagement
Segments — Cohorts and flags
Consent — Unified marketing permissions
All outputs are keyed by profile_id.
Precedence Logic
When attributes conflict across systems, SPAN applies configurable rules.
Examples:
Prefer Shopify shipping address over CRM
Take the greatest value for Last Active Date
Compute Total LTV from component metrics
Attribute logic remains explicit and auditable.
DevOps for Identity
SPAN introduces structured change management to identity logic.
Rules are defined in configuration
Changes are tested before promotion
Diff reports show impact before deployment
This prevents unintended merges and silent logic drift.
Where SPAN Fits
SPAN operates in the Silver Layer of the data stack.
It:
Resolves identity
Standardizes attributes
Produces governed profile tables
Downstream tools consume SPAN outputs for analytics, marketing, and AI workflows.
In Summary
SPAN makes identity:
Deterministic
Transparent
Versioned
Config-driven
Native to Snowflake
Identity becomes infrastructure and not a black box.
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