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Trillium — Data Quality & Data Governance

Last reviewed: 2026-05-29

Trillium (now part of Precisely) is a comprehensive data quality and data governance platform. It enables organizations to profile, cleanse, standardize, match, and monitor data across enterprise systems to ensure accuracy, consistency, and reliability.

Overview

Trillium is used by data engineers, data stewards, and compliance teams to:

  • Profile data — Analyze structure, completeness, and patterns
  • Cleanse data — Correct, standardize, and enrich records
  • Match/merge — Identify duplicates across datasets (MDM)
  • Monitor quality — Track data quality metrics over time
  • Govern data — Define policies, rules, and ownership

Training Content

  • Docker Compose file for standing up Trillium services
  • Configuration for connecting to data sources
  • Port mappings and environment variables

Key Trillium Capabilities

Data Profiling

Automated analysis of data sources to uncover: - Column statistics (min, max, mean, nulls, distinct values) - Data type inference and pattern detection - Frequency distributions and value ranges - Referential integrity between tables - Anomaly detection (outliers, unexpected values)

Data Quality Rules

Define quality dimensions:

Dimension Description Example Rule
Completeness Missing values "Email must not be null"
Uniqueness No duplicates "Customer ID must be unique"
Validity Correct format "Phone number must match +1-XXX-XXX-XXXX"
Accuracy Correct values "Zip code must match city"
Timeliness Up-to-date "Last contact must be < 90 days"
Consistency Cross-system agreement "Same customer, same name in CRM and ERP"

Data Matching & Deduplication

  • Deterministic matching — Exact field matches (SSN, email)
  • Probabilistic matching — Fuzzy/statistical matching (name + address + DOB)
  • Survivorship — Rules for which record "survives" in a merge
  • Householding — Group related records (same family, same address)

Data Enrichment

  • Address validation (via postal databases)
  • Geocoding (lat/long from address)
  • Name parsing (given name, surname, prefix, suffix)
  • Phone/email standardization

Integration (from Docker Compose training)

# Trillium Docker Compose (conceptual)
services:
  trillium:
    image: precisely/trillium:latest
    ports:
      - "8080:8080"
    environment:
      - TRILLIUM_LICENSE_KEY=${LICENSE_KEY}
      - DB_CONNECTION=${DB_CONNECTION_STRING}
    volumes:
      - ./config:/etc/trillium
      - ./data:/data

Enables running Trillium data quality jobs as containerized batch processes.

Use Cases

  • Data migration — Profile and cleanse data before moving to a new system
  • Data warehouse — Ensure quality before loading into analytical databases
  • Master Data Management (MDM) — Match and merge customer/product records
  • Regulatory compliance — GDPR right-to-erasure, data accuracy requirements
  • Data lake governance — Catalog, profile, and monitor source data
Tool Category Trillium Relationship
Precisely Spectrum Data integrity suite Rebranded platform
Great Expectations Open-source data quality Lightweight alternative
dbt (data build tool) Data transformation Can integrate with Trillium profiles
Apache Atlas Data governance Open-source governance catalog
Alation / Collibra Data catalog Enterprise competition

Resources