Adventure Works

Adventure Works

In this Use Case we're going to follow the journey of Adventure Works Cycles as they implement enterprise data governance using Pentaho Data Catalog. Through a combination of automation and machine learning, participants will learn to ingest, profile, and curate structured and unstructured data while building a secure and comprehensive inventory of data assets.

Target Audience

Data Stewards:

Business Analysts:

Data Engineers:

IT Administrators:

Compliance Officers:

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Overview

Challenge: Adventure Works Cycles is expanding globally and must comply with GDPR, CCPA, and emerging data privacy regulations while maintaining operational efficiency. The company needs to implement comprehensive data governance to ensure data quality, lineage tracking, and regulatory compliance across their enterprise.

Journey: Follow Adventure Works as they transform from a data-scattered organization to a governance-first enterprise, learning to balance accessibility with security, compliance with innovation, and automation with human oversight.

Outcome: A fully implemented, best-practice data governance framework that serves as a blueprint for modern organizations navigating the complex landscape of data privacy, security, and business intelligence.

1

Mapping the AW Organization to PDC Roles

AW Users need to be authenticated - Keycloak - to access the PDC assets. PDC Roles authorizes which assets; with Communities determining the scope and permissions.

2

Glossaries & Terms

Glossaries / Business Terms serve as the critical bridge between technical data assets and business value, enabling everyone from C-suite executives to business analysts to speak the same data language when discussing key performance indicators, business rules, and strategic metrics.

3

Data Identification

Data Dictionaries and Patterns are used

4

Connecting to AW Data Source

Connect to the AW data source and ingest the metadata.

5

Process the data

Once profiled the resulting Key Metrics display: Overall Data Quality, Sensitivity Level, Trust Scores, Risk Level, along with: Auditing - Timestamps & Ownership, Data Lineage - PK & FK detection,

6

Canvas & Collections

7

Business Rules

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