Data Governance & Data Quality
The Best Dashboard Built on Bad Data Still Misleads
The same customer sits in the system under three different names, product codes vary by department, and nobody knows which report is right. Buying a new BI tool into that picture solves nothing; it simply shows the wrong answer faster.
We run governance engagements that inventory your data, measure its quality problems and assign ownership. The goal is not to sell new software but to make your existing data trustworthy and to establish the rules that keep it that way.
Key Capabilities
Data Inventory & Source Mapping
Where each piece of data is created, where it is copied and which report it feeds, mapped end to end — exposing shadow systems and spreadsheet islands.
Data Dictionary & Shared Definitions
Corporate definitions for terms such as "active customer" or "net sales" are written down, so departments stop quoting different numbers.
Ownership & Governance Model
An owner and a steward are named for each data domain, and change, correction and access requests follow a defined process.
Cleansing & Duplicate Merging
Spelling variants, missing fields and repeated records are detected and merged, with address and legal-name standardisation applied.
Quality Measurement & Monitoring
Completeness, uniqueness, validity and consistency metrics measured regularly, alerting the responsible owner when quality drops.
Personal Data Inventory
Which system holds which personal data and for how long — an inventory aligned to data protection requirements. See data protection compliance for detail.
Where It Is Used
- Preparation before BI and reporting projects
- Data cleansing ahead of ERP migration
- Data consolidation in mergers
- CRM customer record deduplication
- Data preparation for AI projects
- Data standardisation in public institutions
- Multi-branch or dealer data alignment
- Audit and reporting compliance
How We Work
Current State Assessment
Systems, data flows and reports are reviewed, and priority domains and known issues identified.
Quality Measurement & Reporting
Selected domains are measured and the scale and business impact of problems reported numerically.
Cleansing & Rule Definition
Cleansing is carried out and entry rules and validations added to prevent the data degrading again.
Governance Structure & Handover
Data owners are appointed, regular measurement reporting established and the process handed to your team.
Cleanse First, Analyse Second
We recommend measuring data quality before starting any BI, forecasting or AI project. A model trained on bad data automates the bad decision — and because the model gets the blame, the real cause goes unnoticed for months.