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How can data governance frameworks enhance data trust and transparency?

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Data is a valuable asset for any organization, but it also comes with risks and challenges. How can you ensure that your data is accurate, secure, compliant, and accessible to the right people? How can you foster a culture of data literacy and accountability among your stakeholders? How can you leverage your data to drive innovation and value creation? These are some of the questions that data governance frameworks can help you answer.

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Himanshu Gaur

Junior Privacy Advisor @ Yahoo EMEA | LLM, IP and IT Laws Trinity College Dublin
Vinicius Massullo

Data Manager | Data Science | BA | BI | ETL | DAX | AmorSaúde
Tambe Elvis Akem, MD, MSc, MPH, FETP, ADVAC.

Epidemiologist at Médecins Sans Frontières Belgium | Public Health, Immunization and Health Risks Specialist | One…

1 What is data governance?

Data governance is the set of policies, processes, roles, and standards that define how data is collected, stored, used, and shared within an organization. Data governance aims to align data strategy with business goals, ensure data quality and integrity, protect data privacy and security, and enable data-driven decision making. Data governance is not a one-time project, but a continuous practice that requires collaboration, communication, and coordination across different functions and levels.

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Himanshu Gaur

Junior Privacy Advisor @ Yahoo EMEA | LLM, IP and IT Laws Trinity College Dublin
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In the context of today's AI-driven landscape, judicious and ethical implementation of AI holds immense potential for enhancing data governance practices. AI-driven data governance frameworks can track data lineage and audit trails in real-time, allowing stakeholders to understand how data has been processed, transformed, and used. This level of transparency boosts?confidence in?consumers and regulators by demonstrating that the data governance framework provides transparency throughout the data lifecycle.

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Vinicius Massullo

Data Manager | Data Science | BA | BI | ETL | DAX | AmorSaúde
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A governan?a de dados é um conjunto de práticas e processos que visa garantir a qualidade, seguran?a e uso ético dos dados em uma organiza??o. Ela desempenha um papel fundamental na melhoria da confian?a e transparência dos dados. Ela promove transparência, responsabilidade e conformidade com regulamenta??es. Além disso, contribui para a reputa??o sólida da empresa e tomada de decis?es informadas.

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Tambe Elvis Akem, MD, MSc, MPH, FETP, ADVAC.

Epidemiologist at Médecins Sans Frontières Belgium | Public Health, Immunization and Health Risks Specialist | One Health Researcher
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Data governance is essential for organizations that rely on data to make informed decisions. It ensures that data is managed effectively throughout its lifecycle, from collection to disposal (considering retention period based on the law). By implementing strong data governance practices, organizations can improve data quality, security, and compliance. It important to discuss with all the parties involved in building the data governance structure, this will ensure trust, transparency and sustainability.

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2 Why is data trust and transparency important?

Data trust and transparency are essential for building confidence and credibility in your data assets. Data trust is the degree of confidence that your data is accurate, reliable, and consistent, while data transparency is the degree of visibility and accessibility of your data for the intended users and audiences. These two aspects can help improve data quality, reduce errors and inconsistencies, enhance data security and compliance with regulations, increase data literacy among stakeholders, foster data collaboration across teams and departments, and boost data innovation and value generation.

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Vinicius Massullo

Data Manager | Data Science | BA | BI | ETL | DAX | AmorSaúde
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A confian?a e a transparência dos dados s?o fundamentais por várias raz?es. Primeiramente, permitem tomadas de decis?es informadas, pois gestores podem basear suas escolhas em informa??es sólidas quando os dados s?o transparentes e confiáveis. Além disso, a rela??o com clientes e parceiros é fortalecida quando as partes interessadas confiam nos dados fornecidos por uma organiza??o. A transparência também é essencial para cumprir regulamenta??es e leis, demonstrando responsabilidade e evitando riscos legais. A reputa??o, preven??o de fraudes, ética e responsabilidade também s?o impactadas pela confian?a e transparência dos dados, contribuindo para o sucesso organizacional.

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Tambe Elvis Akem, MD, MSc, MPH, FETP, ADVAC.

Epidemiologist at Médecins Sans Frontières Belgium | Public Health, Immunization and Health Risks Specialist | One Health Researcher
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Data trust and transparency are indeed crucial for maximizing the value of your data. By ensuring the accuracy, reliability, and accessibility of your data, you can unlock a range of benefits, from improved decision-making to enhanced collaboration and innovation. It is important to spell out the terms of collaboration between organisations with respect to data sharing.

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3 How can data governance frameworks enhance data trust and transparency?

Data governance frameworks can provide a structured and systematic approach to improve data trust and transparency in your organization. These frameworks can help define roles and responsibilities for data ownership, stewardship, and custodianship, as well as establish consistent data definitions, classifications, and metadata. Additionally, they can be used to implement data quality controls, audits, and metrics, enforce data security policies, access rights, and encryption methods, document data sources, flows, and lineage, communicate data policies, standards, and best practices, and monitor data performance, usage, and feedback.

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Himanshu Gaur

Junior Privacy Advisor @ Yahoo EMEA | LLM, IP and IT Laws Trinity College Dublin
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Data governance frameworks act like rulebooks for your data. They define who manages it (ownership), how it's maintained (quality checks), and who can see it (access controls). This clarity builds trust: everyone uses the same data, understands its meaning, and feels confident that it's accurate and secure.

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4 What are some examples of data governance frameworks?

Organizations can adopt or adapt different types of data governance frameworks to suit their needs and context. The Data Management Body of Knowledge (DMBOK) framework covers 11 knowledge areas such as data governance, data quality, data security, and data architecture. The Data Governance Institute (DGI) framework focuses on 10 components of data governance, including governance structure, roles, processes, and metrics. Additionally, the COBIT framework is a business framework for the governance and management of enterprise IT, including data governance, data quality, and security. Lastly, the DAMA-DMBOK framework is a wheel model that illustrates the interrelationships among 11 data management functions like data governance, quality, security and integration.

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Himanshu Gaur

Junior Privacy Advisor @ Yahoo EMEA | LLM, IP and IT Laws Trinity College Dublin
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Some more examples are: ISO/IEC 27001:2013 - Information technology - Security techniques - Information security management systems: This international standard provides a comprehensive framework for managing information security, including data governance aspects. GDPR (General Data Protection Regulation): While not strictly a data governance framework, the GDPR sets legal requirements for organizations to manage personal data. These requirements often influence how organizations design their data governance frameworks.

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5 How to implement data governance frameworks?

Implementing data governance frameworks can be a complex and challenging process, requiring careful planning, execution, and evaluation. To begin, you must assess your current data maturity, capabilities, and gaps. Additionally, it is essential to define your data vision, goals, and objectives. Furthermore, you must select or customize a data governance framework that fits your needs and context. Establishing a data governance organization and assigning roles and responsibilities is also important. Developing and documenting data policies, standards, and procedures is essential for success. Implementing data quality, security, and compliance controls and tools is also necessary. Educating and training stakeholders on data governance principles and practices is essential to the process. Finally, monitoring and measuring your data governance outcomes and impacts is key to success.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can data governance frameworks enhance data trust and transparency?

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1 What is data governance?

2 Why is data trust and transparency important?

3 How can data governance frameworks enhance data trust and transparency?

4 What are some examples of data governance frameworks?

5 How to implement data governance frameworks?

6 Here’s what else to consider

Data Management

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How can data governance frameworks enhance data trust and transparency?

1

2

3

4

5

6

1 What is data governance?

2 Why is data trust and transparency important?

3 How can data governance frameworks enhance data trust and transparency?

4 What are some examples of data governance frameworks?

5 How to implement data governance frameworks?

6 Here’s what else to consider

Data Management

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