Data Governance, Quality and Risk

Data Quality Works is a consulting firm specialising in data governance, quality, and risk. We create and implement data governance, quality, and risk policies and frameworks, evaluate and roll out data governance tools, build business glossaries, and ensure high data quality during migrations and data platform development.

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Data Governance Policies and Data Risk Management Frameworks
Data governance policy, data risk management framework, data risk management handbook, data risk training, data quality control standards. Read more about benefits.
Data Governance as-a-Service
Critical Data Element register, business glossary, data lineage, data quality dashboards and control assessment documentation. Read more about benefits.
Data Governance Tool Selection, Design and Implementation
Data governance tool requirements, recommendation papers, pilot plans, solution design, implementation. Read more about benefits.
Custom Metadata Scanners Implementation
Custom metadata model requirements, solution design, custom metadata scanner source code integrating with a data governance tool, data governance tool configuration. Read more about benefits.
Data Quality for Data Migration and Data Platform Programs
Data migration risk assessments, test plans, machine-readable source to target mapping, automated testing framework, test reporting. Read more about benefits.

Posts, Presentations and Open Source Projects

Photograph of a tray of tools organised by the task for which they are used.
Organising in Microsoft Purview Classic
There are many ways to organise resources in Microsoft Purview Classic, from Glossaries to Classifications, Tags, Sensitivity Labels, Collections, and more. This post provides an at-a-glance view of their interaction.
Processed scan of a print of a letter G.
Building Business Glossaries in Microsoft Purview
Building Business Glossaries in Microsoft Purview without clear requirements and without making upfront design decisions will cause pain later on. The critical decisions are whether to catalogue concepts or terms, how to deal with facets, and how to structure glossaries based on who has the authority over definitions.
Screenshot of Tableau data quality dashboard.
Data Quality Analytics
Developing a business glossary using faceted classification, a set of hierarchies across mutually exclusive fundamental concepts, can effectively connect business language with dimensional data quality measurements.
Photo of a folded paper shape illustrating faceted classification.
Taxonomies for Confluence is Now Open-Source
Taxonomies for Confluence add-on is now available under the MIT license from Github.
Photo of store shelves stacked with spices.
Data Beliefs
Somewhat contrarian data beliefs and their consequences for implementing data governance. These beliefs are about definitions of data and information, aboutness, classification and metaphors.
Outline of the foldable 3D shape to help communicate faceted classification ideas.
Data Governance Stationery
Outline of the foldable 3D shape to help communicate faceted classification ideas.
Abstract pattern.
SKOS Version of ANZSIC
SKOS version of Australian and New Zealand Standard Industrial Classification (ANZSIC) that can be loaded into SKOS-compatible taxonomy tools.
Image of stacked boxes.
Capability Models with TOGAF Ontology
Capturing capability models using TOGAF Metamodel Ontology provides an excellent opportunity to visualise, share and debate them.
Screenshot from PROV-O Viz showing provenance of risk information about a repo trade.
Data Centric Architecture Forum 2020 Demo
The purpose of this demo presented at the Data Centric Architecture Forum 2020 is to show capturing of the provenance information using common vocabulary of PROV-O in a repo trading and risk reporting scenario.
Fragment of a scan of the Tree of Life diagram.
Development of Regulatory Taxonomies
Looking into benefits and challenges of developing harmonised regulatory taxonomies, benefits in the absence of such harmonisation, and the role that regulators, regulated firms and vendors can play in the taxonomy development.
Photo of an 80-column punched card.
Uses of Machine Readable Regulatory Rulebooks
Looking into the main beneficiaries of Model Driven Machine Executable Regulation (MDMER), and the role of third party service providers in its adoption.
Photo of a red panda.
RdfPandas is a module providing RDF support for Pandas. It consists of two simple functions for Graph to DataFrame conversion and DataFrame to Graph conversion.
Photo of sweets that look like a heatmap.
Anomaly Detection in Performance Testing
Building software performance testing analytics pipeline involves defining the analysis question, getting and cleaning data, performing analysis and integrating the results with the testing frameworks.