ISO 8000 Masterclass: Build Future-Proof Data Quality Systems That Drive Enterprise Value
You're drowning in data initiatives that promise transformation but deliver confusion, not clarity. Silos, inconsistent definitions, and unreliable systems are costing your organisation millions-while your stakeholders demand clean, accurate, and trustworthy data yesterday. You’re expected to build trust in data, but without a rigorous, globally recognised framework, you’re left guessing what good looks like. That uncertainty puts your credibility at risk and stalls your career momentum. The ISO 8000 Masterclass is your breakthrough. This isn't just theory. It’s the exact system used by leading enterprises to design, deploy, and govern data quality frameworks that withstand audits, scale across departments, and generate measurable ROI. One senior data architect at a Fortune 500 firm used this methodology to align data definitions across 12 legacy systems, reducing reconciliation errors by 93% and cutting onboarding time for new analytics teams by 67%. She was promoted within 6 months. Imagine walking into your next leadership meeting with a board-ready data quality blueprint, grounded in ISO 8000 standards, that execs can finally understand and support. Here’s how this course is structured to help you get there.Course Format & Delivery Details Designed for Maximum Flexibility, Minimum Risk
This course is self-paced, with immediate online access upon enrollment. You control when and where you learn, with no deadlines, no live sessions, and no mandatory attendance. Most professionals complete the program in 6 to 8 weeks while working full time. Early implementation of even the first two modules often delivers visible improvements in data governance clarity within 2 weeks. You receive lifetime access to all course materials, including detailed frameworks, checklists, audit-ready templates, and process workflows. All content is mobile-friendly and fully compatible across devices, so you can study during travel, on breaks, or from your desk. As part of your enrollment, you’ll gain ongoing future updates at no extra cost. Whenever ISO 8000 standards evolve or industry practices shift, your materials are refreshed-ensuring your knowledge remains current for years to come. Instructor Support & Professional Certification
You’re not learning in isolation. Direct guidance from certified data governance specialists is available through structured support channels. Whether you’re clarifying complex clauses in ISO 8000-61 or needing feedback on a sector-specific data model, expert insight is embedded into key milestones. Upon successful completion, you’ll earn a Certificate of Completion issued by The Art of Service, a globally recognised authority in professional frameworks and standards-based training. This certification is referenced by employers across industries, from financial services to healthcare and government agencies, and validates your ability to implement data quality systems that meet stringent compliance and operational demands. Transparent Pricing & Zero-Risk Enrollment
The course fee is straightforward with no hidden fees. Payment is accepted via Visa, Mastercard, and PayPal. We do not use subscription traps, trial conversions, or artificial scarcity tactics. What you see is exactly what you get. After enrollment, you’ll receive a confirmation email, and your access details will be sent separately once the course materials are fully prepared. This ensures you begin with a polished, reliable learning experience. To eliminate any hesitation, we offer a 30-day money-back guarantee. If the course does not meet your expectations, simply request a full refund-no questions asked. This is our promise: your investment is risk-free. “Will This Work for Me?” – We’ve Got You Covered
This program works even if you’re new to ISO standards, operate in a highly regulated industry, or have previously struggled with abstract data governance models that failed in practice. For example, a data compliance officer in a European healthcare network used this course to redesign their master data management strategy. Despite no prior ISO experience, she led her team to pass a critical regulatory audit with zero non-conformities-using the exact checklists from Module 4. Whether you’re a data steward, IT manager, enterprise architect, or analytics lead, the ISO 8000 Masterclass gives you the structure, tools, and confidence to deliver systems that endure. You’re backed by a decade of proven methodology, used in over 40 countries, and trusted by practitioners who’ve transformed data from a cost centre into a strategic asset.
Extensive and Detailed Course Curriculum
Module 1: Foundations of Data Quality and the ISO 8000 Standard - Understanding the global data quality crisis and its business impact
- History and evolution of the ISO 8000 standard series
- Key objectives and scope of ISO 8000 across industries
- Why data quality is a strategic imperative, not just an IT issue
- Core principles of intrinsic, contextual, representational, and accessible data quality
- Differentiating ISO 8000 from other data standards like DAMA-DMBOK and ISO 25012
- The role of metadata in achieving conformance to ISO 8000
- Defining data quality at the enterprise level
- Overview of ISO 8000-110: The foundation standard
- Introduction to data quality metrics and measurement frameworks
- Common data quality failure modes and business consequences
- Building a business case for ISO 8000 adoption
- Identifying executive sponsors and data quality champions
- Aligning ISO 8000 with corporate governance and regulatory requirements
- Data lineage and traceability fundamentals
Module 2: ISO 8000-61 – Data Quality Management: Requirements - Deep dive into ISO 8000-61: Purpose and structure
- Organisational responsibilities for data quality
- Establishing a data quality policy aligned with ISO 8000
- Defining roles: Data owners, stewards, custodians, and users
- Setting data quality objectives and KPIs
- Implementing a data quality management system (DQMS)
- Integrating DQMS with existing quality management systems
- Documentation requirements for ISO 8000 compliance
- Auditing data quality processes and outputs
- Conducting internal reviews and management evaluations
- Handling non-conformities and corrective actions
- Change control procedures for data assets
- Training and competence requirements for data roles
- Monitoring and measurement of data quality performance
- Continuous improvement cycles based on ISO 8000-61
Module 3: ISO 8000-110 – Data Quality: Concepts and Using the Framework - Overview of ISO 8000-110 and its relationship to the rest of the standard
- The Data Quality Framework: Four dimensions and eight characteristics
- Understanding intrinsic data quality: Accuracy, objectivity, freedom from error
- Contextual quality: Relevancy, completeness, timeliness, value-added
- Representational quality: Interpretability, clarity, coherence, conciseness
- Accessible quality: Access security, availability, ease of use
- How to score data quality across all 8 characteristics
- Weighting factors based on business context and use case
- Using the framework to prioritise data quality improvements
- Mapping data assets to the ISO 8000-110 framework
- Creating data quality scorecards for executive reporting
- Case studies: Applying the framework in financial, supply chain, and HR data
- Tailoring the framework for sector-specific needs
- Data quality maturity assessment using ISO 8000-110
- Integrating the framework with data governance policies
Module 4: Data Modelling and Conformance to ISO 8000-130 - Introduction to ISO 8000-130: Data quality in exchange
- Principles of data modelling for quality assurance
- Designing exchangeable data sets with embedded quality metadata
- Using XML, JSON, and other formats to represent ISO-compliant data
- Structuring metadata to support validation, transformation, and usability
- Data dictionary requirements under ISO 8000
- Schema design patterns that enforce data quality rules
- Conformance testing for data exchange formats
- Developing reusable data models for cross-system consistency
- Example models: Customer, product, supplier, employee master data
- Using ISO 11179 metadata registries in alignment with ISO 8000
- Validating semantic consistency across data exchanges
- Version control for data models and schema evolution
- Automating validation using defined rules and constraints
- Creating templates for common data exchange scenarios
Module 5: Master Data Management (MDM) and ISO 8000 Alignment - Linking MDM strategy to ISO 8000 data quality requirements
- Establishing a single source of truth using ISO principles
- Defining authoritative sources for master data entities
- Designing golden records with embedded quality attributes
- Data matching, merging, and survivorship rules based on ISO 8000
- Handling duplicates, conflicts, and inconsistencies in master data
- Implementing data quality rules in MDM workflows
- Onboarding new data sources with ISO-compliant metadata
- Monitoring data quality in real time within MDM systems
- Reporting on MDM data quality using ISO 8000 scorecards
- Integrating reference data management with ISO standards
- Managing hierarchies and classifications with traceability
- Conducting MDM audits against ISO 8000 benchmarks
- Scaling MDM across global operations with consistent quality
- Aligning MDM with enterprise data governance councils
Module 6: Data Quality Assurance and Testing Methodologies - Designing test plans based on ISO 8000 quality dimensions
- Developing data quality test cases and expected outcomes
- Static vs dynamic data quality testing approaches
- Automated data validation using rule-based engines
- Sampling strategies for large data sets
- Testing for accuracy, completeness, uniqueness, and consistency
- Validating conformance to business rules and constraints
- Using data profiling tools to identify quality issues
- Implementing data reconciliation and exception handling
- Designing feedback loops for corrective actions
- Test documentation and evidence for audit trails
- Regression testing for data quality after system changes
- Performance benchmarking of data quality processes
- Case study: Testing a customer data migration project
- Continuous testing in DevOps and data pipelines
Module 7: Data Quality in Data Integration and Exchange - Ensuring data quality across ETL, ELT, and API workflows
- Validating data at ingestion points
- Handling transformation errors and data drift
- Embedding quality checks in data pipelines
- Monitoring data quality in real time during integration
- Designing fault-tolerant data exchange architectures
- Using ISO 8000 metadata to describe data quality in transit
- Validating third-party data feeds and external sources
- Establishing data quality SLAs with vendors and partners
- Documenting data lineage and transformation history
- Handling time zone, language, and formatting differences
- Conducting pre- and post-integration data quality reviews
- Building audit-ready integration reports
- Securing data quality during cloud migrations
- Case study: Cross-border supply chain data integration
Module 8: Data Governance and Organisational Enablement - Aligning data governance with ISO 8000 standards
- Establishing a data governance council with clear accountabilities
- Defining data domains and assigning data owners
- Developing data quality policies and procedures
- Creating data quality charters for business units
- Integrating ISO 8000 into data governance frameworks
- Hosting data quality review meetings and governance cycles
- Managing data quality issues through formal escalation paths
- Using issue tracking systems for data quality defects
- Communicating data quality performance to stakeholders
- Training business users on data quality expectations
- Embedding data quality into project lifecycles
- Conducting data governance maturity assessments
- Leveraging ISO 8000 to enhance data culture
- Measuring the ROI of data governance initiatives
Module 9: Industry-Specific Applications of ISO 8000 - Applying ISO 8000 in financial services and banking
- Meeting Basel III, MiFID II, and other regulatory demands
- Healthcare data quality for patient records and reporting
- Compliance with GDPR, HIPAA, and data privacy laws
- Manufacturing and supply chain: Ensuring product data accuracy
- Retail and e-commerce: Managing product and customer data
- Public sector: Improving citizen service data reliability
- Energy and utilities: Metering, billing, and asset data quality
- Telecommunications: Customer and network data integrity
- Transport and logistics: Shipment, tracking, and scheduling data
- Aerospace and defence: High-integrity data requirements
- Education: Student records, funding, and accreditation data
- Tailoring ISO 8000 for small vs large organisations
- Adapting frameworks for startups and scale-ups
- Global implementation considerations across regions
Module 10: Auditing and Certification Against ISO 8000 - Preparing for internal and external ISO 8000 audits
- Documentation requirements for auditor review
- Conducting gap assessments against ISO 8000 clauses
- Developing audit checklists and evidence collection plans
- Responding to non-conformities and observations
- Coordinating with certification bodies
- Understanding the certification process timeline
- Training auditors and internal reviewers on ISO 8000
- Running mock audits to test readiness
- Measuring compliance maturity across business units
- Using audit findings to drive continuous improvement
- Reporting audit outcomes to senior leadership
- Maintaining certification through surveillance audits
- Re-certification cycles and ongoing compliance
- Publicly communicating ISO 8000 certification achievements
Module 11: Data Quality Metrics, Reporting, and Executive Communication - Designing executive dashboards for data quality
- Selecting KPIs that matter to CFOs and CIOs
- Creating data quality health scores
- Translating technical issues into business impact
- Reporting on data quality trends over time
- Using visualisations to communicate data quality status
- Linking data quality improvements to cost savings
- Measuring reduction in rework, disputes, and errors
- Calculating financial impact of poor data quality
- Building board-level presentations with ISO 8000 alignment
- Using storytelling to gain executive buy-in
- Creating data quality business cases for funding
- Presenting audit-ready reports and compliance status
- Automating quarterly data quality reporting cycles
- Establishing a data quality communication rhythm
Module 12: Advanced Topics in Data Quality and Future Trends - AI and machine learning: Ensuring data quality for model training
- Using anomaly detection to identify data quality issues
- Automated data quality rule generation using AI
- Blockchain and immutable ledgers for data provenance
- Zero-trust data architectures and ISO 8000 alignment
- Real-time data quality monitoring in streaming systems
- Edge computing and data quality at the source
- Federated data systems and cross-organisation quality
- The role of data contracts in ensuring quality
- Data observability platforms and ISO 8000 principles
- Quantum computing and long-term data integrity planning
- Preparing for emerging ISO data standards
- Evolving regulatory landscapes and global compliance
- Sustainability data and ESG reporting quality
- Future-proofing your data quality strategy
Module 13: Hands-On Implementation Projects - Project 1: Conduct a full ISO 8000 gap assessment for a sample organisation
- Project 2: Design a data quality policy aligned with ISO 8000-61
- Project 3: Build a data quality scorecard using ISO 8000-110
- Project 4: Create a master data model for customer data
- Project 5: Develop a data exchange specification using ISO 8000-130
- Project 6: Draft an internal audit checklist for ISO 8000 compliance
- Project 7: Design a data governance charter for a business unit
- Project 8: Simulate a data reconciliation process with error handling
- Project 9: Write test cases for a product data migration
- Project 10: Create an executive presentation on data quality ROI
- Using templates and checklists to standardise implementation
- Documenting decisions and rationale for audit purposes
- Integrating feedback from peer review exercises
- Finalising project portfolios for professional presentation
- Preparing implementation playbooks for organisational roll-out
Module 14: Certification, Career Advancement, and Next Steps - Preparing for your final assessment and Certificate of Completion
- Reviewing key concepts and common pitfalls
- Submitting your capstone project for evaluation
- Understanding the grading criteria and feedback process
- Receiving your Certificate of Completion issued by The Art of Service
- Adding the certification to LinkedIn, CV, and professional profiles
- Using the credential in job applications and promotions
- Networking with other ISO 8000 practitioners
- Accessing alumni resources and community forums
- Continuing education pathways in data governance and quality
- Exploring advanced certifications in related domains
- Joining ISO technical committees and industry groups
- Presenting your work at conferences and events
- Building a personal brand as a data quality leader
- Lifetime access reminder and future update roadmap
Module 1: Foundations of Data Quality and the ISO 8000 Standard - Understanding the global data quality crisis and its business impact
- History and evolution of the ISO 8000 standard series
- Key objectives and scope of ISO 8000 across industries
- Why data quality is a strategic imperative, not just an IT issue
- Core principles of intrinsic, contextual, representational, and accessible data quality
- Differentiating ISO 8000 from other data standards like DAMA-DMBOK and ISO 25012
- The role of metadata in achieving conformance to ISO 8000
- Defining data quality at the enterprise level
- Overview of ISO 8000-110: The foundation standard
- Introduction to data quality metrics and measurement frameworks
- Common data quality failure modes and business consequences
- Building a business case for ISO 8000 adoption
- Identifying executive sponsors and data quality champions
- Aligning ISO 8000 with corporate governance and regulatory requirements
- Data lineage and traceability fundamentals
Module 2: ISO 8000-61 – Data Quality Management: Requirements - Deep dive into ISO 8000-61: Purpose and structure
- Organisational responsibilities for data quality
- Establishing a data quality policy aligned with ISO 8000
- Defining roles: Data owners, stewards, custodians, and users
- Setting data quality objectives and KPIs
- Implementing a data quality management system (DQMS)
- Integrating DQMS with existing quality management systems
- Documentation requirements for ISO 8000 compliance
- Auditing data quality processes and outputs
- Conducting internal reviews and management evaluations
- Handling non-conformities and corrective actions
- Change control procedures for data assets
- Training and competence requirements for data roles
- Monitoring and measurement of data quality performance
- Continuous improvement cycles based on ISO 8000-61
Module 3: ISO 8000-110 – Data Quality: Concepts and Using the Framework - Overview of ISO 8000-110 and its relationship to the rest of the standard
- The Data Quality Framework: Four dimensions and eight characteristics
- Understanding intrinsic data quality: Accuracy, objectivity, freedom from error
- Contextual quality: Relevancy, completeness, timeliness, value-added
- Representational quality: Interpretability, clarity, coherence, conciseness
- Accessible quality: Access security, availability, ease of use
- How to score data quality across all 8 characteristics
- Weighting factors based on business context and use case
- Using the framework to prioritise data quality improvements
- Mapping data assets to the ISO 8000-110 framework
- Creating data quality scorecards for executive reporting
- Case studies: Applying the framework in financial, supply chain, and HR data
- Tailoring the framework for sector-specific needs
- Data quality maturity assessment using ISO 8000-110
- Integrating the framework with data governance policies
Module 4: Data Modelling and Conformance to ISO 8000-130 - Introduction to ISO 8000-130: Data quality in exchange
- Principles of data modelling for quality assurance
- Designing exchangeable data sets with embedded quality metadata
- Using XML, JSON, and other formats to represent ISO-compliant data
- Structuring metadata to support validation, transformation, and usability
- Data dictionary requirements under ISO 8000
- Schema design patterns that enforce data quality rules
- Conformance testing for data exchange formats
- Developing reusable data models for cross-system consistency
- Example models: Customer, product, supplier, employee master data
- Using ISO 11179 metadata registries in alignment with ISO 8000
- Validating semantic consistency across data exchanges
- Version control for data models and schema evolution
- Automating validation using defined rules and constraints
- Creating templates for common data exchange scenarios
Module 5: Master Data Management (MDM) and ISO 8000 Alignment - Linking MDM strategy to ISO 8000 data quality requirements
- Establishing a single source of truth using ISO principles
- Defining authoritative sources for master data entities
- Designing golden records with embedded quality attributes
- Data matching, merging, and survivorship rules based on ISO 8000
- Handling duplicates, conflicts, and inconsistencies in master data
- Implementing data quality rules in MDM workflows
- Onboarding new data sources with ISO-compliant metadata
- Monitoring data quality in real time within MDM systems
- Reporting on MDM data quality using ISO 8000 scorecards
- Integrating reference data management with ISO standards
- Managing hierarchies and classifications with traceability
- Conducting MDM audits against ISO 8000 benchmarks
- Scaling MDM across global operations with consistent quality
- Aligning MDM with enterprise data governance councils
Module 6: Data Quality Assurance and Testing Methodologies - Designing test plans based on ISO 8000 quality dimensions
- Developing data quality test cases and expected outcomes
- Static vs dynamic data quality testing approaches
- Automated data validation using rule-based engines
- Sampling strategies for large data sets
- Testing for accuracy, completeness, uniqueness, and consistency
- Validating conformance to business rules and constraints
- Using data profiling tools to identify quality issues
- Implementing data reconciliation and exception handling
- Designing feedback loops for corrective actions
- Test documentation and evidence for audit trails
- Regression testing for data quality after system changes
- Performance benchmarking of data quality processes
- Case study: Testing a customer data migration project
- Continuous testing in DevOps and data pipelines
Module 7: Data Quality in Data Integration and Exchange - Ensuring data quality across ETL, ELT, and API workflows
- Validating data at ingestion points
- Handling transformation errors and data drift
- Embedding quality checks in data pipelines
- Monitoring data quality in real time during integration
- Designing fault-tolerant data exchange architectures
- Using ISO 8000 metadata to describe data quality in transit
- Validating third-party data feeds and external sources
- Establishing data quality SLAs with vendors and partners
- Documenting data lineage and transformation history
- Handling time zone, language, and formatting differences
- Conducting pre- and post-integration data quality reviews
- Building audit-ready integration reports
- Securing data quality during cloud migrations
- Case study: Cross-border supply chain data integration
Module 8: Data Governance and Organisational Enablement - Aligning data governance with ISO 8000 standards
- Establishing a data governance council with clear accountabilities
- Defining data domains and assigning data owners
- Developing data quality policies and procedures
- Creating data quality charters for business units
- Integrating ISO 8000 into data governance frameworks
- Hosting data quality review meetings and governance cycles
- Managing data quality issues through formal escalation paths
- Using issue tracking systems for data quality defects
- Communicating data quality performance to stakeholders
- Training business users on data quality expectations
- Embedding data quality into project lifecycles
- Conducting data governance maturity assessments
- Leveraging ISO 8000 to enhance data culture
- Measuring the ROI of data governance initiatives
Module 9: Industry-Specific Applications of ISO 8000 - Applying ISO 8000 in financial services and banking
- Meeting Basel III, MiFID II, and other regulatory demands
- Healthcare data quality for patient records and reporting
- Compliance with GDPR, HIPAA, and data privacy laws
- Manufacturing and supply chain: Ensuring product data accuracy
- Retail and e-commerce: Managing product and customer data
- Public sector: Improving citizen service data reliability
- Energy and utilities: Metering, billing, and asset data quality
- Telecommunications: Customer and network data integrity
- Transport and logistics: Shipment, tracking, and scheduling data
- Aerospace and defence: High-integrity data requirements
- Education: Student records, funding, and accreditation data
- Tailoring ISO 8000 for small vs large organisations
- Adapting frameworks for startups and scale-ups
- Global implementation considerations across regions
Module 10: Auditing and Certification Against ISO 8000 - Preparing for internal and external ISO 8000 audits
- Documentation requirements for auditor review
- Conducting gap assessments against ISO 8000 clauses
- Developing audit checklists and evidence collection plans
- Responding to non-conformities and observations
- Coordinating with certification bodies
- Understanding the certification process timeline
- Training auditors and internal reviewers on ISO 8000
- Running mock audits to test readiness
- Measuring compliance maturity across business units
- Using audit findings to drive continuous improvement
- Reporting audit outcomes to senior leadership
- Maintaining certification through surveillance audits
- Re-certification cycles and ongoing compliance
- Publicly communicating ISO 8000 certification achievements
Module 11: Data Quality Metrics, Reporting, and Executive Communication - Designing executive dashboards for data quality
- Selecting KPIs that matter to CFOs and CIOs
- Creating data quality health scores
- Translating technical issues into business impact
- Reporting on data quality trends over time
- Using visualisations to communicate data quality status
- Linking data quality improvements to cost savings
- Measuring reduction in rework, disputes, and errors
- Calculating financial impact of poor data quality
- Building board-level presentations with ISO 8000 alignment
- Using storytelling to gain executive buy-in
- Creating data quality business cases for funding
- Presenting audit-ready reports and compliance status
- Automating quarterly data quality reporting cycles
- Establishing a data quality communication rhythm
Module 12: Advanced Topics in Data Quality and Future Trends - AI and machine learning: Ensuring data quality for model training
- Using anomaly detection to identify data quality issues
- Automated data quality rule generation using AI
- Blockchain and immutable ledgers for data provenance
- Zero-trust data architectures and ISO 8000 alignment
- Real-time data quality monitoring in streaming systems
- Edge computing and data quality at the source
- Federated data systems and cross-organisation quality
- The role of data contracts in ensuring quality
- Data observability platforms and ISO 8000 principles
- Quantum computing and long-term data integrity planning
- Preparing for emerging ISO data standards
- Evolving regulatory landscapes and global compliance
- Sustainability data and ESG reporting quality
- Future-proofing your data quality strategy
Module 13: Hands-On Implementation Projects - Project 1: Conduct a full ISO 8000 gap assessment for a sample organisation
- Project 2: Design a data quality policy aligned with ISO 8000-61
- Project 3: Build a data quality scorecard using ISO 8000-110
- Project 4: Create a master data model for customer data
- Project 5: Develop a data exchange specification using ISO 8000-130
- Project 6: Draft an internal audit checklist for ISO 8000 compliance
- Project 7: Design a data governance charter for a business unit
- Project 8: Simulate a data reconciliation process with error handling
- Project 9: Write test cases for a product data migration
- Project 10: Create an executive presentation on data quality ROI
- Using templates and checklists to standardise implementation
- Documenting decisions and rationale for audit purposes
- Integrating feedback from peer review exercises
- Finalising project portfolios for professional presentation
- Preparing implementation playbooks for organisational roll-out
Module 14: Certification, Career Advancement, and Next Steps - Preparing for your final assessment and Certificate of Completion
- Reviewing key concepts and common pitfalls
- Submitting your capstone project for evaluation
- Understanding the grading criteria and feedback process
- Receiving your Certificate of Completion issued by The Art of Service
- Adding the certification to LinkedIn, CV, and professional profiles
- Using the credential in job applications and promotions
- Networking with other ISO 8000 practitioners
- Accessing alumni resources and community forums
- Continuing education pathways in data governance and quality
- Exploring advanced certifications in related domains
- Joining ISO technical committees and industry groups
- Presenting your work at conferences and events
- Building a personal brand as a data quality leader
- Lifetime access reminder and future update roadmap
- Deep dive into ISO 8000-61: Purpose and structure
- Organisational responsibilities for data quality
- Establishing a data quality policy aligned with ISO 8000
- Defining roles: Data owners, stewards, custodians, and users
- Setting data quality objectives and KPIs
- Implementing a data quality management system (DQMS)
- Integrating DQMS with existing quality management systems
- Documentation requirements for ISO 8000 compliance
- Auditing data quality processes and outputs
- Conducting internal reviews and management evaluations
- Handling non-conformities and corrective actions
- Change control procedures for data assets
- Training and competence requirements for data roles
- Monitoring and measurement of data quality performance
- Continuous improvement cycles based on ISO 8000-61
Module 3: ISO 8000-110 – Data Quality: Concepts and Using the Framework - Overview of ISO 8000-110 and its relationship to the rest of the standard
- The Data Quality Framework: Four dimensions and eight characteristics
- Understanding intrinsic data quality: Accuracy, objectivity, freedom from error
- Contextual quality: Relevancy, completeness, timeliness, value-added
- Representational quality: Interpretability, clarity, coherence, conciseness
- Accessible quality: Access security, availability, ease of use
- How to score data quality across all 8 characteristics
- Weighting factors based on business context and use case
- Using the framework to prioritise data quality improvements
- Mapping data assets to the ISO 8000-110 framework
- Creating data quality scorecards for executive reporting
- Case studies: Applying the framework in financial, supply chain, and HR data
- Tailoring the framework for sector-specific needs
- Data quality maturity assessment using ISO 8000-110
- Integrating the framework with data governance policies
Module 4: Data Modelling and Conformance to ISO 8000-130 - Introduction to ISO 8000-130: Data quality in exchange
- Principles of data modelling for quality assurance
- Designing exchangeable data sets with embedded quality metadata
- Using XML, JSON, and other formats to represent ISO-compliant data
- Structuring metadata to support validation, transformation, and usability
- Data dictionary requirements under ISO 8000
- Schema design patterns that enforce data quality rules
- Conformance testing for data exchange formats
- Developing reusable data models for cross-system consistency
- Example models: Customer, product, supplier, employee master data
- Using ISO 11179 metadata registries in alignment with ISO 8000
- Validating semantic consistency across data exchanges
- Version control for data models and schema evolution
- Automating validation using defined rules and constraints
- Creating templates for common data exchange scenarios
Module 5: Master Data Management (MDM) and ISO 8000 Alignment - Linking MDM strategy to ISO 8000 data quality requirements
- Establishing a single source of truth using ISO principles
- Defining authoritative sources for master data entities
- Designing golden records with embedded quality attributes
- Data matching, merging, and survivorship rules based on ISO 8000
- Handling duplicates, conflicts, and inconsistencies in master data
- Implementing data quality rules in MDM workflows
- Onboarding new data sources with ISO-compliant metadata
- Monitoring data quality in real time within MDM systems
- Reporting on MDM data quality using ISO 8000 scorecards
- Integrating reference data management with ISO standards
- Managing hierarchies and classifications with traceability
- Conducting MDM audits against ISO 8000 benchmarks
- Scaling MDM across global operations with consistent quality
- Aligning MDM with enterprise data governance councils
Module 6: Data Quality Assurance and Testing Methodologies - Designing test plans based on ISO 8000 quality dimensions
- Developing data quality test cases and expected outcomes
- Static vs dynamic data quality testing approaches
- Automated data validation using rule-based engines
- Sampling strategies for large data sets
- Testing for accuracy, completeness, uniqueness, and consistency
- Validating conformance to business rules and constraints
- Using data profiling tools to identify quality issues
- Implementing data reconciliation and exception handling
- Designing feedback loops for corrective actions
- Test documentation and evidence for audit trails
- Regression testing for data quality after system changes
- Performance benchmarking of data quality processes
- Case study: Testing a customer data migration project
- Continuous testing in DevOps and data pipelines
Module 7: Data Quality in Data Integration and Exchange - Ensuring data quality across ETL, ELT, and API workflows
- Validating data at ingestion points
- Handling transformation errors and data drift
- Embedding quality checks in data pipelines
- Monitoring data quality in real time during integration
- Designing fault-tolerant data exchange architectures
- Using ISO 8000 metadata to describe data quality in transit
- Validating third-party data feeds and external sources
- Establishing data quality SLAs with vendors and partners
- Documenting data lineage and transformation history
- Handling time zone, language, and formatting differences
- Conducting pre- and post-integration data quality reviews
- Building audit-ready integration reports
- Securing data quality during cloud migrations
- Case study: Cross-border supply chain data integration
Module 8: Data Governance and Organisational Enablement - Aligning data governance with ISO 8000 standards
- Establishing a data governance council with clear accountabilities
- Defining data domains and assigning data owners
- Developing data quality policies and procedures
- Creating data quality charters for business units
- Integrating ISO 8000 into data governance frameworks
- Hosting data quality review meetings and governance cycles
- Managing data quality issues through formal escalation paths
- Using issue tracking systems for data quality defects
- Communicating data quality performance to stakeholders
- Training business users on data quality expectations
- Embedding data quality into project lifecycles
- Conducting data governance maturity assessments
- Leveraging ISO 8000 to enhance data culture
- Measuring the ROI of data governance initiatives
Module 9: Industry-Specific Applications of ISO 8000 - Applying ISO 8000 in financial services and banking
- Meeting Basel III, MiFID II, and other regulatory demands
- Healthcare data quality for patient records and reporting
- Compliance with GDPR, HIPAA, and data privacy laws
- Manufacturing and supply chain: Ensuring product data accuracy
- Retail and e-commerce: Managing product and customer data
- Public sector: Improving citizen service data reliability
- Energy and utilities: Metering, billing, and asset data quality
- Telecommunications: Customer and network data integrity
- Transport and logistics: Shipment, tracking, and scheduling data
- Aerospace and defence: High-integrity data requirements
- Education: Student records, funding, and accreditation data
- Tailoring ISO 8000 for small vs large organisations
- Adapting frameworks for startups and scale-ups
- Global implementation considerations across regions
Module 10: Auditing and Certification Against ISO 8000 - Preparing for internal and external ISO 8000 audits
- Documentation requirements for auditor review
- Conducting gap assessments against ISO 8000 clauses
- Developing audit checklists and evidence collection plans
- Responding to non-conformities and observations
- Coordinating with certification bodies
- Understanding the certification process timeline
- Training auditors and internal reviewers on ISO 8000
- Running mock audits to test readiness
- Measuring compliance maturity across business units
- Using audit findings to drive continuous improvement
- Reporting audit outcomes to senior leadership
- Maintaining certification through surveillance audits
- Re-certification cycles and ongoing compliance
- Publicly communicating ISO 8000 certification achievements
Module 11: Data Quality Metrics, Reporting, and Executive Communication - Designing executive dashboards for data quality
- Selecting KPIs that matter to CFOs and CIOs
- Creating data quality health scores
- Translating technical issues into business impact
- Reporting on data quality trends over time
- Using visualisations to communicate data quality status
- Linking data quality improvements to cost savings
- Measuring reduction in rework, disputes, and errors
- Calculating financial impact of poor data quality
- Building board-level presentations with ISO 8000 alignment
- Using storytelling to gain executive buy-in
- Creating data quality business cases for funding
- Presenting audit-ready reports and compliance status
- Automating quarterly data quality reporting cycles
- Establishing a data quality communication rhythm
Module 12: Advanced Topics in Data Quality and Future Trends - AI and machine learning: Ensuring data quality for model training
- Using anomaly detection to identify data quality issues
- Automated data quality rule generation using AI
- Blockchain and immutable ledgers for data provenance
- Zero-trust data architectures and ISO 8000 alignment
- Real-time data quality monitoring in streaming systems
- Edge computing and data quality at the source
- Federated data systems and cross-organisation quality
- The role of data contracts in ensuring quality
- Data observability platforms and ISO 8000 principles
- Quantum computing and long-term data integrity planning
- Preparing for emerging ISO data standards
- Evolving regulatory landscapes and global compliance
- Sustainability data and ESG reporting quality
- Future-proofing your data quality strategy
Module 13: Hands-On Implementation Projects - Project 1: Conduct a full ISO 8000 gap assessment for a sample organisation
- Project 2: Design a data quality policy aligned with ISO 8000-61
- Project 3: Build a data quality scorecard using ISO 8000-110
- Project 4: Create a master data model for customer data
- Project 5: Develop a data exchange specification using ISO 8000-130
- Project 6: Draft an internal audit checklist for ISO 8000 compliance
- Project 7: Design a data governance charter for a business unit
- Project 8: Simulate a data reconciliation process with error handling
- Project 9: Write test cases for a product data migration
- Project 10: Create an executive presentation on data quality ROI
- Using templates and checklists to standardise implementation
- Documenting decisions and rationale for audit purposes
- Integrating feedback from peer review exercises
- Finalising project portfolios for professional presentation
- Preparing implementation playbooks for organisational roll-out
Module 14: Certification, Career Advancement, and Next Steps - Preparing for your final assessment and Certificate of Completion
- Reviewing key concepts and common pitfalls
- Submitting your capstone project for evaluation
- Understanding the grading criteria and feedback process
- Receiving your Certificate of Completion issued by The Art of Service
- Adding the certification to LinkedIn, CV, and professional profiles
- Using the credential in job applications and promotions
- Networking with other ISO 8000 practitioners
- Accessing alumni resources and community forums
- Continuing education pathways in data governance and quality
- Exploring advanced certifications in related domains
- Joining ISO technical committees and industry groups
- Presenting your work at conferences and events
- Building a personal brand as a data quality leader
- Lifetime access reminder and future update roadmap
- Introduction to ISO 8000-130: Data quality in exchange
- Principles of data modelling for quality assurance
- Designing exchangeable data sets with embedded quality metadata
- Using XML, JSON, and other formats to represent ISO-compliant data
- Structuring metadata to support validation, transformation, and usability
- Data dictionary requirements under ISO 8000
- Schema design patterns that enforce data quality rules
- Conformance testing for data exchange formats
- Developing reusable data models for cross-system consistency
- Example models: Customer, product, supplier, employee master data
- Using ISO 11179 metadata registries in alignment with ISO 8000
- Validating semantic consistency across data exchanges
- Version control for data models and schema evolution
- Automating validation using defined rules and constraints
- Creating templates for common data exchange scenarios
Module 5: Master Data Management (MDM) and ISO 8000 Alignment - Linking MDM strategy to ISO 8000 data quality requirements
- Establishing a single source of truth using ISO principles
- Defining authoritative sources for master data entities
- Designing golden records with embedded quality attributes
- Data matching, merging, and survivorship rules based on ISO 8000
- Handling duplicates, conflicts, and inconsistencies in master data
- Implementing data quality rules in MDM workflows
- Onboarding new data sources with ISO-compliant metadata
- Monitoring data quality in real time within MDM systems
- Reporting on MDM data quality using ISO 8000 scorecards
- Integrating reference data management with ISO standards
- Managing hierarchies and classifications with traceability
- Conducting MDM audits against ISO 8000 benchmarks
- Scaling MDM across global operations with consistent quality
- Aligning MDM with enterprise data governance councils
Module 6: Data Quality Assurance and Testing Methodologies - Designing test plans based on ISO 8000 quality dimensions
- Developing data quality test cases and expected outcomes
- Static vs dynamic data quality testing approaches
- Automated data validation using rule-based engines
- Sampling strategies for large data sets
- Testing for accuracy, completeness, uniqueness, and consistency
- Validating conformance to business rules and constraints
- Using data profiling tools to identify quality issues
- Implementing data reconciliation and exception handling
- Designing feedback loops for corrective actions
- Test documentation and evidence for audit trails
- Regression testing for data quality after system changes
- Performance benchmarking of data quality processes
- Case study: Testing a customer data migration project
- Continuous testing in DevOps and data pipelines
Module 7: Data Quality in Data Integration and Exchange - Ensuring data quality across ETL, ELT, and API workflows
- Validating data at ingestion points
- Handling transformation errors and data drift
- Embedding quality checks in data pipelines
- Monitoring data quality in real time during integration
- Designing fault-tolerant data exchange architectures
- Using ISO 8000 metadata to describe data quality in transit
- Validating third-party data feeds and external sources
- Establishing data quality SLAs with vendors and partners
- Documenting data lineage and transformation history
- Handling time zone, language, and formatting differences
- Conducting pre- and post-integration data quality reviews
- Building audit-ready integration reports
- Securing data quality during cloud migrations
- Case study: Cross-border supply chain data integration
Module 8: Data Governance and Organisational Enablement - Aligning data governance with ISO 8000 standards
- Establishing a data governance council with clear accountabilities
- Defining data domains and assigning data owners
- Developing data quality policies and procedures
- Creating data quality charters for business units
- Integrating ISO 8000 into data governance frameworks
- Hosting data quality review meetings and governance cycles
- Managing data quality issues through formal escalation paths
- Using issue tracking systems for data quality defects
- Communicating data quality performance to stakeholders
- Training business users on data quality expectations
- Embedding data quality into project lifecycles
- Conducting data governance maturity assessments
- Leveraging ISO 8000 to enhance data culture
- Measuring the ROI of data governance initiatives
Module 9: Industry-Specific Applications of ISO 8000 - Applying ISO 8000 in financial services and banking
- Meeting Basel III, MiFID II, and other regulatory demands
- Healthcare data quality for patient records and reporting
- Compliance with GDPR, HIPAA, and data privacy laws
- Manufacturing and supply chain: Ensuring product data accuracy
- Retail and e-commerce: Managing product and customer data
- Public sector: Improving citizen service data reliability
- Energy and utilities: Metering, billing, and asset data quality
- Telecommunications: Customer and network data integrity
- Transport and logistics: Shipment, tracking, and scheduling data
- Aerospace and defence: High-integrity data requirements
- Education: Student records, funding, and accreditation data
- Tailoring ISO 8000 for small vs large organisations
- Adapting frameworks for startups and scale-ups
- Global implementation considerations across regions
Module 10: Auditing and Certification Against ISO 8000 - Preparing for internal and external ISO 8000 audits
- Documentation requirements for auditor review
- Conducting gap assessments against ISO 8000 clauses
- Developing audit checklists and evidence collection plans
- Responding to non-conformities and observations
- Coordinating with certification bodies
- Understanding the certification process timeline
- Training auditors and internal reviewers on ISO 8000
- Running mock audits to test readiness
- Measuring compliance maturity across business units
- Using audit findings to drive continuous improvement
- Reporting audit outcomes to senior leadership
- Maintaining certification through surveillance audits
- Re-certification cycles and ongoing compliance
- Publicly communicating ISO 8000 certification achievements
Module 11: Data Quality Metrics, Reporting, and Executive Communication - Designing executive dashboards for data quality
- Selecting KPIs that matter to CFOs and CIOs
- Creating data quality health scores
- Translating technical issues into business impact
- Reporting on data quality trends over time
- Using visualisations to communicate data quality status
- Linking data quality improvements to cost savings
- Measuring reduction in rework, disputes, and errors
- Calculating financial impact of poor data quality
- Building board-level presentations with ISO 8000 alignment
- Using storytelling to gain executive buy-in
- Creating data quality business cases for funding
- Presenting audit-ready reports and compliance status
- Automating quarterly data quality reporting cycles
- Establishing a data quality communication rhythm
Module 12: Advanced Topics in Data Quality and Future Trends - AI and machine learning: Ensuring data quality for model training
- Using anomaly detection to identify data quality issues
- Automated data quality rule generation using AI
- Blockchain and immutable ledgers for data provenance
- Zero-trust data architectures and ISO 8000 alignment
- Real-time data quality monitoring in streaming systems
- Edge computing and data quality at the source
- Federated data systems and cross-organisation quality
- The role of data contracts in ensuring quality
- Data observability platforms and ISO 8000 principles
- Quantum computing and long-term data integrity planning
- Preparing for emerging ISO data standards
- Evolving regulatory landscapes and global compliance
- Sustainability data and ESG reporting quality
- Future-proofing your data quality strategy
Module 13: Hands-On Implementation Projects - Project 1: Conduct a full ISO 8000 gap assessment for a sample organisation
- Project 2: Design a data quality policy aligned with ISO 8000-61
- Project 3: Build a data quality scorecard using ISO 8000-110
- Project 4: Create a master data model for customer data
- Project 5: Develop a data exchange specification using ISO 8000-130
- Project 6: Draft an internal audit checklist for ISO 8000 compliance
- Project 7: Design a data governance charter for a business unit
- Project 8: Simulate a data reconciliation process with error handling
- Project 9: Write test cases for a product data migration
- Project 10: Create an executive presentation on data quality ROI
- Using templates and checklists to standardise implementation
- Documenting decisions and rationale for audit purposes
- Integrating feedback from peer review exercises
- Finalising project portfolios for professional presentation
- Preparing implementation playbooks for organisational roll-out
Module 14: Certification, Career Advancement, and Next Steps - Preparing for your final assessment and Certificate of Completion
- Reviewing key concepts and common pitfalls
- Submitting your capstone project for evaluation
- Understanding the grading criteria and feedback process
- Receiving your Certificate of Completion issued by The Art of Service
- Adding the certification to LinkedIn, CV, and professional profiles
- Using the credential in job applications and promotions
- Networking with other ISO 8000 practitioners
- Accessing alumni resources and community forums
- Continuing education pathways in data governance and quality
- Exploring advanced certifications in related domains
- Joining ISO technical committees and industry groups
- Presenting your work at conferences and events
- Building a personal brand as a data quality leader
- Lifetime access reminder and future update roadmap
- Designing test plans based on ISO 8000 quality dimensions
- Developing data quality test cases and expected outcomes
- Static vs dynamic data quality testing approaches
- Automated data validation using rule-based engines
- Sampling strategies for large data sets
- Testing for accuracy, completeness, uniqueness, and consistency
- Validating conformance to business rules and constraints
- Using data profiling tools to identify quality issues
- Implementing data reconciliation and exception handling
- Designing feedback loops for corrective actions
- Test documentation and evidence for audit trails
- Regression testing for data quality after system changes
- Performance benchmarking of data quality processes
- Case study: Testing a customer data migration project
- Continuous testing in DevOps and data pipelines
Module 7: Data Quality in Data Integration and Exchange - Ensuring data quality across ETL, ELT, and API workflows
- Validating data at ingestion points
- Handling transformation errors and data drift
- Embedding quality checks in data pipelines
- Monitoring data quality in real time during integration
- Designing fault-tolerant data exchange architectures
- Using ISO 8000 metadata to describe data quality in transit
- Validating third-party data feeds and external sources
- Establishing data quality SLAs with vendors and partners
- Documenting data lineage and transformation history
- Handling time zone, language, and formatting differences
- Conducting pre- and post-integration data quality reviews
- Building audit-ready integration reports
- Securing data quality during cloud migrations
- Case study: Cross-border supply chain data integration
Module 8: Data Governance and Organisational Enablement - Aligning data governance with ISO 8000 standards
- Establishing a data governance council with clear accountabilities
- Defining data domains and assigning data owners
- Developing data quality policies and procedures
- Creating data quality charters for business units
- Integrating ISO 8000 into data governance frameworks
- Hosting data quality review meetings and governance cycles
- Managing data quality issues through formal escalation paths
- Using issue tracking systems for data quality defects
- Communicating data quality performance to stakeholders
- Training business users on data quality expectations
- Embedding data quality into project lifecycles
- Conducting data governance maturity assessments
- Leveraging ISO 8000 to enhance data culture
- Measuring the ROI of data governance initiatives
Module 9: Industry-Specific Applications of ISO 8000 - Applying ISO 8000 in financial services and banking
- Meeting Basel III, MiFID II, and other regulatory demands
- Healthcare data quality for patient records and reporting
- Compliance with GDPR, HIPAA, and data privacy laws
- Manufacturing and supply chain: Ensuring product data accuracy
- Retail and e-commerce: Managing product and customer data
- Public sector: Improving citizen service data reliability
- Energy and utilities: Metering, billing, and asset data quality
- Telecommunications: Customer and network data integrity
- Transport and logistics: Shipment, tracking, and scheduling data
- Aerospace and defence: High-integrity data requirements
- Education: Student records, funding, and accreditation data
- Tailoring ISO 8000 for small vs large organisations
- Adapting frameworks for startups and scale-ups
- Global implementation considerations across regions
Module 10: Auditing and Certification Against ISO 8000 - Preparing for internal and external ISO 8000 audits
- Documentation requirements for auditor review
- Conducting gap assessments against ISO 8000 clauses
- Developing audit checklists and evidence collection plans
- Responding to non-conformities and observations
- Coordinating with certification bodies
- Understanding the certification process timeline
- Training auditors and internal reviewers on ISO 8000
- Running mock audits to test readiness
- Measuring compliance maturity across business units
- Using audit findings to drive continuous improvement
- Reporting audit outcomes to senior leadership
- Maintaining certification through surveillance audits
- Re-certification cycles and ongoing compliance
- Publicly communicating ISO 8000 certification achievements
Module 11: Data Quality Metrics, Reporting, and Executive Communication - Designing executive dashboards for data quality
- Selecting KPIs that matter to CFOs and CIOs
- Creating data quality health scores
- Translating technical issues into business impact
- Reporting on data quality trends over time
- Using visualisations to communicate data quality status
- Linking data quality improvements to cost savings
- Measuring reduction in rework, disputes, and errors
- Calculating financial impact of poor data quality
- Building board-level presentations with ISO 8000 alignment
- Using storytelling to gain executive buy-in
- Creating data quality business cases for funding
- Presenting audit-ready reports and compliance status
- Automating quarterly data quality reporting cycles
- Establishing a data quality communication rhythm
Module 12: Advanced Topics in Data Quality and Future Trends - AI and machine learning: Ensuring data quality for model training
- Using anomaly detection to identify data quality issues
- Automated data quality rule generation using AI
- Blockchain and immutable ledgers for data provenance
- Zero-trust data architectures and ISO 8000 alignment
- Real-time data quality monitoring in streaming systems
- Edge computing and data quality at the source
- Federated data systems and cross-organisation quality
- The role of data contracts in ensuring quality
- Data observability platforms and ISO 8000 principles
- Quantum computing and long-term data integrity planning
- Preparing for emerging ISO data standards
- Evolving regulatory landscapes and global compliance
- Sustainability data and ESG reporting quality
- Future-proofing your data quality strategy
Module 13: Hands-On Implementation Projects - Project 1: Conduct a full ISO 8000 gap assessment for a sample organisation
- Project 2: Design a data quality policy aligned with ISO 8000-61
- Project 3: Build a data quality scorecard using ISO 8000-110
- Project 4: Create a master data model for customer data
- Project 5: Develop a data exchange specification using ISO 8000-130
- Project 6: Draft an internal audit checklist for ISO 8000 compliance
- Project 7: Design a data governance charter for a business unit
- Project 8: Simulate a data reconciliation process with error handling
- Project 9: Write test cases for a product data migration
- Project 10: Create an executive presentation on data quality ROI
- Using templates and checklists to standardise implementation
- Documenting decisions and rationale for audit purposes
- Integrating feedback from peer review exercises
- Finalising project portfolios for professional presentation
- Preparing implementation playbooks for organisational roll-out
Module 14: Certification, Career Advancement, and Next Steps - Preparing for your final assessment and Certificate of Completion
- Reviewing key concepts and common pitfalls
- Submitting your capstone project for evaluation
- Understanding the grading criteria and feedback process
- Receiving your Certificate of Completion issued by The Art of Service
- Adding the certification to LinkedIn, CV, and professional profiles
- Using the credential in job applications and promotions
- Networking with other ISO 8000 practitioners
- Accessing alumni resources and community forums
- Continuing education pathways in data governance and quality
- Exploring advanced certifications in related domains
- Joining ISO technical committees and industry groups
- Presenting your work at conferences and events
- Building a personal brand as a data quality leader
- Lifetime access reminder and future update roadmap
- Aligning data governance with ISO 8000 standards
- Establishing a data governance council with clear accountabilities
- Defining data domains and assigning data owners
- Developing data quality policies and procedures
- Creating data quality charters for business units
- Integrating ISO 8000 into data governance frameworks
- Hosting data quality review meetings and governance cycles
- Managing data quality issues through formal escalation paths
- Using issue tracking systems for data quality defects
- Communicating data quality performance to stakeholders
- Training business users on data quality expectations
- Embedding data quality into project lifecycles
- Conducting data governance maturity assessments
- Leveraging ISO 8000 to enhance data culture
- Measuring the ROI of data governance initiatives
Module 9: Industry-Specific Applications of ISO 8000 - Applying ISO 8000 in financial services and banking
- Meeting Basel III, MiFID II, and other regulatory demands
- Healthcare data quality for patient records and reporting
- Compliance with GDPR, HIPAA, and data privacy laws
- Manufacturing and supply chain: Ensuring product data accuracy
- Retail and e-commerce: Managing product and customer data
- Public sector: Improving citizen service data reliability
- Energy and utilities: Metering, billing, and asset data quality
- Telecommunications: Customer and network data integrity
- Transport and logistics: Shipment, tracking, and scheduling data
- Aerospace and defence: High-integrity data requirements
- Education: Student records, funding, and accreditation data
- Tailoring ISO 8000 for small vs large organisations
- Adapting frameworks for startups and scale-ups
- Global implementation considerations across regions
Module 10: Auditing and Certification Against ISO 8000 - Preparing for internal and external ISO 8000 audits
- Documentation requirements for auditor review
- Conducting gap assessments against ISO 8000 clauses
- Developing audit checklists and evidence collection plans
- Responding to non-conformities and observations
- Coordinating with certification bodies
- Understanding the certification process timeline
- Training auditors and internal reviewers on ISO 8000
- Running mock audits to test readiness
- Measuring compliance maturity across business units
- Using audit findings to drive continuous improvement
- Reporting audit outcomes to senior leadership
- Maintaining certification through surveillance audits
- Re-certification cycles and ongoing compliance
- Publicly communicating ISO 8000 certification achievements
Module 11: Data Quality Metrics, Reporting, and Executive Communication - Designing executive dashboards for data quality
- Selecting KPIs that matter to CFOs and CIOs
- Creating data quality health scores
- Translating technical issues into business impact
- Reporting on data quality trends over time
- Using visualisations to communicate data quality status
- Linking data quality improvements to cost savings
- Measuring reduction in rework, disputes, and errors
- Calculating financial impact of poor data quality
- Building board-level presentations with ISO 8000 alignment
- Using storytelling to gain executive buy-in
- Creating data quality business cases for funding
- Presenting audit-ready reports and compliance status
- Automating quarterly data quality reporting cycles
- Establishing a data quality communication rhythm
Module 12: Advanced Topics in Data Quality and Future Trends - AI and machine learning: Ensuring data quality for model training
- Using anomaly detection to identify data quality issues
- Automated data quality rule generation using AI
- Blockchain and immutable ledgers for data provenance
- Zero-trust data architectures and ISO 8000 alignment
- Real-time data quality monitoring in streaming systems
- Edge computing and data quality at the source
- Federated data systems and cross-organisation quality
- The role of data contracts in ensuring quality
- Data observability platforms and ISO 8000 principles
- Quantum computing and long-term data integrity planning
- Preparing for emerging ISO data standards
- Evolving regulatory landscapes and global compliance
- Sustainability data and ESG reporting quality
- Future-proofing your data quality strategy
Module 13: Hands-On Implementation Projects - Project 1: Conduct a full ISO 8000 gap assessment for a sample organisation
- Project 2: Design a data quality policy aligned with ISO 8000-61
- Project 3: Build a data quality scorecard using ISO 8000-110
- Project 4: Create a master data model for customer data
- Project 5: Develop a data exchange specification using ISO 8000-130
- Project 6: Draft an internal audit checklist for ISO 8000 compliance
- Project 7: Design a data governance charter for a business unit
- Project 8: Simulate a data reconciliation process with error handling
- Project 9: Write test cases for a product data migration
- Project 10: Create an executive presentation on data quality ROI
- Using templates and checklists to standardise implementation
- Documenting decisions and rationale for audit purposes
- Integrating feedback from peer review exercises
- Finalising project portfolios for professional presentation
- Preparing implementation playbooks for organisational roll-out
Module 14: Certification, Career Advancement, and Next Steps - Preparing for your final assessment and Certificate of Completion
- Reviewing key concepts and common pitfalls
- Submitting your capstone project for evaluation
- Understanding the grading criteria and feedback process
- Receiving your Certificate of Completion issued by The Art of Service
- Adding the certification to LinkedIn, CV, and professional profiles
- Using the credential in job applications and promotions
- Networking with other ISO 8000 practitioners
- Accessing alumni resources and community forums
- Continuing education pathways in data governance and quality
- Exploring advanced certifications in related domains
- Joining ISO technical committees and industry groups
- Presenting your work at conferences and events
- Building a personal brand as a data quality leader
- Lifetime access reminder and future update roadmap
- Preparing for internal and external ISO 8000 audits
- Documentation requirements for auditor review
- Conducting gap assessments against ISO 8000 clauses
- Developing audit checklists and evidence collection plans
- Responding to non-conformities and observations
- Coordinating with certification bodies
- Understanding the certification process timeline
- Training auditors and internal reviewers on ISO 8000
- Running mock audits to test readiness
- Measuring compliance maturity across business units
- Using audit findings to drive continuous improvement
- Reporting audit outcomes to senior leadership
- Maintaining certification through surveillance audits
- Re-certification cycles and ongoing compliance
- Publicly communicating ISO 8000 certification achievements
Module 11: Data Quality Metrics, Reporting, and Executive Communication - Designing executive dashboards for data quality
- Selecting KPIs that matter to CFOs and CIOs
- Creating data quality health scores
- Translating technical issues into business impact
- Reporting on data quality trends over time
- Using visualisations to communicate data quality status
- Linking data quality improvements to cost savings
- Measuring reduction in rework, disputes, and errors
- Calculating financial impact of poor data quality
- Building board-level presentations with ISO 8000 alignment
- Using storytelling to gain executive buy-in
- Creating data quality business cases for funding
- Presenting audit-ready reports and compliance status
- Automating quarterly data quality reporting cycles
- Establishing a data quality communication rhythm
Module 12: Advanced Topics in Data Quality and Future Trends - AI and machine learning: Ensuring data quality for model training
- Using anomaly detection to identify data quality issues
- Automated data quality rule generation using AI
- Blockchain and immutable ledgers for data provenance
- Zero-trust data architectures and ISO 8000 alignment
- Real-time data quality monitoring in streaming systems
- Edge computing and data quality at the source
- Federated data systems and cross-organisation quality
- The role of data contracts in ensuring quality
- Data observability platforms and ISO 8000 principles
- Quantum computing and long-term data integrity planning
- Preparing for emerging ISO data standards
- Evolving regulatory landscapes and global compliance
- Sustainability data and ESG reporting quality
- Future-proofing your data quality strategy
Module 13: Hands-On Implementation Projects - Project 1: Conduct a full ISO 8000 gap assessment for a sample organisation
- Project 2: Design a data quality policy aligned with ISO 8000-61
- Project 3: Build a data quality scorecard using ISO 8000-110
- Project 4: Create a master data model for customer data
- Project 5: Develop a data exchange specification using ISO 8000-130
- Project 6: Draft an internal audit checklist for ISO 8000 compliance
- Project 7: Design a data governance charter for a business unit
- Project 8: Simulate a data reconciliation process with error handling
- Project 9: Write test cases for a product data migration
- Project 10: Create an executive presentation on data quality ROI
- Using templates and checklists to standardise implementation
- Documenting decisions and rationale for audit purposes
- Integrating feedback from peer review exercises
- Finalising project portfolios for professional presentation
- Preparing implementation playbooks for organisational roll-out
Module 14: Certification, Career Advancement, and Next Steps - Preparing for your final assessment and Certificate of Completion
- Reviewing key concepts and common pitfalls
- Submitting your capstone project for evaluation
- Understanding the grading criteria and feedback process
- Receiving your Certificate of Completion issued by The Art of Service
- Adding the certification to LinkedIn, CV, and professional profiles
- Using the credential in job applications and promotions
- Networking with other ISO 8000 practitioners
- Accessing alumni resources and community forums
- Continuing education pathways in data governance and quality
- Exploring advanced certifications in related domains
- Joining ISO technical committees and industry groups
- Presenting your work at conferences and events
- Building a personal brand as a data quality leader
- Lifetime access reminder and future update roadmap
- AI and machine learning: Ensuring data quality for model training
- Using anomaly detection to identify data quality issues
- Automated data quality rule generation using AI
- Blockchain and immutable ledgers for data provenance
- Zero-trust data architectures and ISO 8000 alignment
- Real-time data quality monitoring in streaming systems
- Edge computing and data quality at the source
- Federated data systems and cross-organisation quality
- The role of data contracts in ensuring quality
- Data observability platforms and ISO 8000 principles
- Quantum computing and long-term data integrity planning
- Preparing for emerging ISO data standards
- Evolving regulatory landscapes and global compliance
- Sustainability data and ESG reporting quality
- Future-proofing your data quality strategy
Module 13: Hands-On Implementation Projects - Project 1: Conduct a full ISO 8000 gap assessment for a sample organisation
- Project 2: Design a data quality policy aligned with ISO 8000-61
- Project 3: Build a data quality scorecard using ISO 8000-110
- Project 4: Create a master data model for customer data
- Project 5: Develop a data exchange specification using ISO 8000-130
- Project 6: Draft an internal audit checklist for ISO 8000 compliance
- Project 7: Design a data governance charter for a business unit
- Project 8: Simulate a data reconciliation process with error handling
- Project 9: Write test cases for a product data migration
- Project 10: Create an executive presentation on data quality ROI
- Using templates and checklists to standardise implementation
- Documenting decisions and rationale for audit purposes
- Integrating feedback from peer review exercises
- Finalising project portfolios for professional presentation
- Preparing implementation playbooks for organisational roll-out
Module 14: Certification, Career Advancement, and Next Steps - Preparing for your final assessment and Certificate of Completion
- Reviewing key concepts and common pitfalls
- Submitting your capstone project for evaluation
- Understanding the grading criteria and feedback process
- Receiving your Certificate of Completion issued by The Art of Service
- Adding the certification to LinkedIn, CV, and professional profiles
- Using the credential in job applications and promotions
- Networking with other ISO 8000 practitioners
- Accessing alumni resources and community forums
- Continuing education pathways in data governance and quality
- Exploring advanced certifications in related domains
- Joining ISO technical committees and industry groups
- Presenting your work at conferences and events
- Building a personal brand as a data quality leader
- Lifetime access reminder and future update roadmap
- Preparing for your final assessment and Certificate of Completion
- Reviewing key concepts and common pitfalls
- Submitting your capstone project for evaluation
- Understanding the grading criteria and feedback process
- Receiving your Certificate of Completion issued by The Art of Service
- Adding the certification to LinkedIn, CV, and professional profiles
- Using the credential in job applications and promotions
- Networking with other ISO 8000 practitioners
- Accessing alumni resources and community forums
- Continuing education pathways in data governance and quality
- Exploring advanced certifications in related domains
- Joining ISO technical committees and industry groups
- Presenting your work at conferences and events
- Building a personal brand as a data quality leader
- Lifetime access reminder and future update roadmap