Data Inventory SOP¶

Sub-procedure for Innovate pillar digital transformation

Overview¶

This sub-procedure defines the systematic approach for discovering, cataloging, and documenting all data assets within an organization. It establishes the foundation for data governance by creating a comprehensive inventory of structured and unstructured data across all systems.

Scope¶

Pillar: Innovate (Digital Transformation) Service Area: Data Governance Related Services: Cloud Migration, Compliance (HIPAA, SOC 2, PCI)

Prerequisites¶

Executive sponsorship for data governance initiative
Data governance charter approved
Access to all data systems (read-only credentials)
Stakeholder identification (data owners, stewards, custodians)
Data inventory tooling provisioned (if automated)
NDA and data handling agreements in place

Procedure¶

Step 1: Scope Definition¶

Objective: Define boundaries of data inventory effort

Identify all data domains in scope:
Customer data
Employee data
Financial data
Operational data
Third-party data
Document systems containing data:
Production databases
Data warehouses and lakes
File shares and document repositories
SaaS applications
Shadow IT systems (if known)
Establish inventory depth:
System-level inventory
Schema/table-level inventory
Field/column-level inventory
Define out-of-scope boundaries

Duration: 1-2 days Owner: Data Governance Lead

Step 2: System Discovery¶

Objective: Catalog all data-containing systems

Review existing IT asset inventory
Interview IT and business stakeholders
Scan network for database services
Inventory cloud data services
Document SaaS applications with data storage
Identify data integrations and ETL pipelines
Catalog backup and archive systems

Duration: 3-5 days Owner: Data Analyst

Step 3: Data Asset Cataloging¶

Objective: Create detailed inventory of data assets

For each system, document:

Technical Metadata:
System name and type
Database/schema/table names
Column names and data types
Record counts and data volumes
Storage location (on-premises, cloud, region)
Business Metadata:
Business description and purpose
Data owner (accountable executive)
Data steward (day-to-day governance)
Data custodian (technical management)
Business criticality (high/medium/low)
Operational Metadata:
Data freshness and update frequency
Data quality indicators
Backup and recovery classification
Retention requirements

Duration: 5-10 days (varies by scope) Owner: Data Analyst

Step 4: Data Lineage Mapping¶

Objective: Document data flows and transformations

Identify data sources and origins
Map data movement between systems
Document ETL/ELT processes
Trace data transformations
Identify data consumption endpoints
Document data sharing (internal and external)
Create lineage visualizations

Duration: 3-5 days Owner: Data Engineer / Data Analyst

Step 5: Data Owner Assignment¶

Objective: Establish accountability for all data assets

Define data ownership model:
Data Owner: Accountable executive
Data Steward: Day-to-day governance
Data Custodian: Technical management
Identify ownership gaps
Facilitate ownership discussions
Document ownership assignments
Communicate responsibilities
Establish governance cadence

Duration: 2-3 days Owner: Data Governance Lead

Step 6: Inventory Validation and Publication¶

Objective: Validate and publish data inventory

Review inventory with data owners
Validate technical metadata accuracy
Fill gaps in business metadata
Publish inventory to data catalog tool
Establish inventory maintenance process
Define refresh frequency