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Our dataset contains 1547 prioritized requirements, solutions, benefits, and real-life case studies/use cases that will guide you in asking the most important questions to align your data governance efforts with urgency and scope.
This comprehensive knowledge base is designed to cater to all your data governance needs, ensuring that your efforts yield the desired results efficiently and effectively.
But why choose our Data Governance Alignment in Data Governance Knowledge Base over competitors and alternative solutions? Firstly, it is tailor-made for professionals like you who understand the critical role of data governance in driving business success.
Secondly, our product is DIY and affordable, which means you can save on expensive consultancy fees while still achieving the same level of expertise and knowledge.
With an overview of product details and specifications, you can easily navigate through the dataset and align your data governance strategy according to your unique business needs.
Our product type also sets us apart from semi-related products, as our focus on data governance alignment makes us a clear leader in this specialized field.
But what are the benefits of using our Data Governance Alignment in Data Governance Knowledge Base? For starters, you can expect to see a significant improvement in your data governance practices, leading to better data quality and compliance.
This translates into improved decision-making, enhanced operational efficiency, and increased customer trust.
Don′t just take our word for it – our extensive research on data governance alignment and satisfied customers speak volumes about the effectiveness of our product.
Whether you are a small business or a large corporation, our Data Governance Alignment in Data Governance Knowledge Base is suitable for all businesses looking to unlock the full potential of their data.
And the best part? It comes at a reasonable cost with low maintenance and upkeep requirements.
Of course, every product has its pros and cons.
But with our Data Governance Alignment in Data Governance Knowledge Base, the pros far outweigh any potential cons.
Our detailed description of what our product does will allow you to make an informed decision and understand how it aligns your data governance efforts with your urgent business needs.
Say goodbye to data governance headaches and hello to a streamlined and effective approach with our Data Governance Alignment in Data Governance Knowledge Base.
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How to improve organization performance using big data analytics capability and business strategy alignment? How do you communicate effectively with stakeholders to maintain alignment and commitment?
Data Governance Alignment
Data governance alignment involves aligning the management and oversight of data with both the organization′s overall performance goals and its strategy for using big data analytics. This can improve decision-making, efficiency, and competitiveness.
- Develop a clearly defined data governance framework to ensure data is managed consistently and effectively. (Ensures data is used in line with the organization′s goals and objectives)
- Establish data stewardship roles and responsibilities to oversee the use and protection of data. (Promotes accountability and reduces the risk of misuse or mishandling of data)
- Implement data quality standards and processes to ensure accurate and reliable data. (Increases trust in the data and enables better decision-making)
- Utilize data analytics tools and techniques to gain insights into big data and inform business strategy. (Enables data-driven decision making and improves organizational performance)
- Create a data governance committee or council to regularly review and monitor data governance practices and make necessary improvements. (Promotes continuous improvement and ensures ongoing alignment with business strategy)
- Clearly communicate the importance of data governance and its impact on organization performance to all stakeholders. (Increases understanding and support for data governance efforts)
CONTROL QUESTION: How to improve organization performance using big data analytics capability and business strategy alignment?
Big Hairy Audacious Goal (BHAG) for 10 years from now:
In 10 years, Data Governance Alignment will be the leading solution for organizations looking to achieve maximum performance through the integration of big data analytics capability and business strategy alignment.
With a mature and robust framework in place, Data Governance Alignment will be able to provide organizations with actionable and data-driven insights that will drive strategic decision-making and performance improvement.
Data Governance Alignment will have established itself as the go-to partner for organizations across all industries, providing customized solutions that are tailored to their specific needs and objectives.
Through continuous innovation and investment in cutting-edge technology, Data Governance Alignment will set the standard for data governance and analytic capabilities, empowering organizations to leverage the full potential of their data and gain a competitive advantage in the market.
Moreover, Data Governance Alignment will become a thought leader in the field, with a strong community of experts and professionals collaborating and sharing best practices to drive continual improvement.
By 2031, Data Governance Alignment will have successfully transformed numerous organizations into data-driven enterprises, resulting in significant growth and measurable impact on their bottom line. Its success will serve as a catalyst for the widespread adoption of data governance and alignment in organizations worldwide, ultimately contributing to the advancement of global business intelligence and innovation.
"I am impressed with the depth and accuracy of this dataset. The prioritized recommendations have proven invaluable for my project, making it a breeze to identify the most important actions to take."
Introduction
Data governance alignment is essential for organizations of all sizes to maximize their performance and achieve their business goals. With the exponential growth of data and the increasing importance of data-driven decision making, it is crucial for organizations to align their big data analytics capabilities with their business strategy. This case study focuses on a client who sought to improve their organization′s performance by implementing a data governance alignment strategy.
Synopsis of Client Situation
ABC Corp (name changed for confidentiality) is a leading multinational company that operates in the technology sector. The company has a diverse portfolio of products and services, catering to customers in various industries. As the company grew, so did the volume of data generated from its various business functions. However, ABC Corp faced challenges in leveraging this data effectively to drive better business decisions. The lack of data governance alignment and a clear understanding of how to use big data analytics were hindering the company′s performance.
Consulting Methodology
To address the client′s challenges, our consulting firm employed a comprehensive methodology to establish data governance alignment within ABC Corp. The methodology consisted of four main phases: Assessment, Strategy Development, Implementation, and Monitoring & Review.
1. Assessment Phase:
The first step of the consulting process was to assess the current state of the client′s data governance structure. Our consultants conducted a thorough review of the company′s data management practices, including data collection, storage, and usage. This assessment highlighted gaps in the client′s current data governance framework, such as inconsistent data definitions, lack of data ownership, and siloed data systems.
2. Strategy Development:
Based on the findings from the assessment phase, our consultants worked closely with the client′s leadership team to develop a data governance strategy that aligned with the company′s business objectives. The strategy outlined the roles and responsibilities of key stakeholders, data governance policies, and the implementation roadmap.
3. Implementation:
The third phase was the implementation of the data governance strategy. This involved establishing a data governance committee, conducting data quality checks, and implementing data governance tools and technologies. The implementation also included training employees on data management best practices and creating a data culture within the organization.
4. Monitoring & Review:
The final phase of our consulting methodology was to monitor and review the effectiveness of the data governance framework. This involved regular audits of data management processes, identifying and addressing any gaps, and continuously refining the strategy based on the changing business needs.
Deliverables
As a result of our consulting engagement, the client received the following deliverables:
1. Data Governance Framework: A comprehensive data governance framework that outlined the roles and responsibilities of key stakeholders, data management policies, and data governance tools and technologies.
2. Implementation Roadmap: A roadmap that outlined the steps for implementing the data governance framework, including timelines, resource allocation, and expected outcomes.
3. Data Governance Committee: A cross-functional team of stakeholders responsible for overseeing the company′s data governance strategy and implementation.
4. Data Quality Standards: Defined data quality standards to ensure the accuracy, completeness, and consistency of data across the organization.
5. Employee Training: Training programs for employees to enhance their data management skills and create a data-driven culture within the organization.
Implementation Challenges
The implementation of the data governance alignment strategy was not without its challenges. Some of the key challenges we faced were:
1. Resistance to Change: One of the significant challenges we encountered was the resistance to change from some employees who were accustomed to working in a siloed manner. It took time and effort to convince them of the benefits of a unified data governance framework.
2. Cost and Resource Constraints: Implementing a robust data governance framework requires significant investments in terms of resources and technology. This was a challenge for ABC Corp, as they had budget constraints.
Key Performance Indicators (KPIs)
To measure the success of the data governance alignment strategy, we identified the following KPIs:
1. Data Quality: The improvement in data quality was measured by tracking the number of errors and discrepancies in the data.
2. Data Availability: The percentage of data available for analysis and decision making was used to measure the effectiveness of the data governance framework.
3. Time to Insights: The time taken to generate actionable insights from data was an important KPI to measure the efficiency of the data governance processes.
4. Business Outcomes: Ultimately, the success of the data governance alignment strategy was evaluated based on its impact on the organization′s business outcomes, such as increased revenue, cost savings, and improved customer satisfaction.
Management Considerations
While implementing the data governance alignment strategy, it is essential to consider the following management factors:
1. Strong Leadership and Support: Effective implementation of data governance alignment requires strong leadership and support from key stakeholders. The leadership team at ABC Corp played a critical role in driving the change and ensuring the success of the project.
2. Communication and Training: As with any change management initiative, effective communication and training are crucial for the successful adoption of the new data governance framework. The consultants worked closely with the client′s HR team to develop training programs that were tailored to the employees′ needs.
3. Continuous Improvement: Data governance alignment is an ongoing process, and it is essential to continuously monitor and review the effectiveness of the framework. Our consultants worked with the client′s data governance committee to ensure regular audits and refinements of the strategy.
Conclusion
The implementation of a data governance alignment strategy has significantly improved the performance of ABC Corp. With a robust data governance framework in place, the company now has access to quality data that enables them to make more informed business decisions. The alignment of big data analytics capabilities with the company′s business strategy has also resulted in cost savings and increased revenue. The success of this project highlights the importance of data governance alignment as a critical component of organizational performance in today′s data-driven world.
References
1. Achieving Business Benefits through Data Governance Alignment. DATUM Consulting Group, Inc.
2. Perlitz, M., Schwendemann, C., & Kim, N. (2018). Balancing flexibility and consistency: Establishing data governance in agile big data environments. Journal of Database Management, 29(3), 17-36.
3. Data Governance Market - Global Forecast to 2025. MarketsandMarkets Research Private Ltd.
Are you tired of spending endless hours trying to align your data governance strategy with your business goals and priorities? Look no further, because our Data Governance Alignment in Data Governance Knowledge Base is here to streamline the process and deliver results like never before.
Our dataset contains 1547 prioritized requirements, solutions, benefits, and real-life case studies/use cases that will guide you in asking the most important questions to align your data governance efforts with urgency and scope.
This comprehensive knowledge base is designed to cater to all your data governance needs, ensuring that your efforts yield the desired results efficiently and effectively.
But why choose our Data Governance Alignment in Data Governance Knowledge Base over competitors and alternative solutions? Firstly, it is tailor-made for professionals like you who understand the critical role of data governance in driving business success.
Secondly, our product is DIY and affordable, which means you can save on expensive consultancy fees while still achieving the same level of expertise and knowledge.
With an overview of product details and specifications, you can easily navigate through the dataset and align your data governance strategy according to your unique business needs.
Our product type also sets us apart from semi-related products, as our focus on data governance alignment makes us a clear leader in this specialized field.
But what are the benefits of using our Data Governance Alignment in Data Governance Knowledge Base? For starters, you can expect to see a significant improvement in your data governance practices, leading to better data quality and compliance.
This translates into improved decision-making, enhanced operational efficiency, and increased customer trust.
Don′t just take our word for it – our extensive research on data governance alignment and satisfied customers speak volumes about the effectiveness of our product.
Whether you are a small business or a large corporation, our Data Governance Alignment in Data Governance Knowledge Base is suitable for all businesses looking to unlock the full potential of their data.
And the best part? It comes at a reasonable cost with low maintenance and upkeep requirements.
Of course, every product has its pros and cons.
But with our Data Governance Alignment in Data Governance Knowledge Base, the pros far outweigh any potential cons.
Our detailed description of what our product does will allow you to make an informed decision and understand how it aligns your data governance efforts with your urgent business needs.
Say goodbye to data governance headaches and hello to a streamlined and effective approach with our Data Governance Alignment in Data Governance Knowledge Base.
Try it now and see the difference it can make for your business.
Discover Insights, Make Informed Decisions, and Stay Ahead of the Curve:
Key Features:
Comprehensive set of 1547 prioritized Data Governance Alignment requirements. - Extensive coverage of 236 Data Governance Alignment topic scopes.
- In-depth analysis of 236 Data Governance Alignment step-by-step solutions, benefits, BHAGs.
- Detailed examination of 236 Data Governance Alignment case studies and use cases.
- Digital download upon purchase.
- Enjoy lifetime document updates included with your purchase.
- Benefit from a fully editable and customizable Excel format.
- Trusted and utilized by over 10,000 organizations.
- Covering: Data Governance Data Owners, Data Governance Implementation, Access Recertification, MDM Processes, Compliance Management, Data Governance Change Management, Data Governance Audits, Global Supply Chain Governance, Governance risk data, IT Systems, MDM Framework, Personal Data, Infrastructure Maintenance, Data Inventory, Secure Data Processing, Data Governance Metrics, Linking Policies, ERP Project Management, Economic Trends, Data Migration, Data Governance Maturity Model, Taxation Practices, Data Processing Agreements, Data Compliance, Source Code, File System, Regulatory Governance, Data Profiling, Data Governance Continuity, Data Stewardship Framework, Customer-Centric Focus, Legal Framework, Information Requirements, Data Governance Plan, Decision Support, Data Governance Risks, Data Governance Evaluation, IT Staffing, AI Governance, Data Governance Data Sovereignty, Data Governance Data Retention Policies, Security Measures, Process Automation, Data Validation, Data Governance Data Governance Strategy, Digital Twins, Data Governance Data Analytics Risks, Data Governance Data Protection Controls, Data Governance Models, Data Governance Data Breach Risks, Data Ethics, Data Governance Transformation, Data Consistency, Data Lifecycle, Data Governance Data Governance Implementation Plan, Finance Department, Data Ownership, Electronic Checks, Data Governance Best Practices, Data Governance Data Users, Data Integrity, Data Legislation, Data Governance Disaster Recovery, Data Standards, Data Governance Controls, Data Governance Data Portability, Crowdsourced Data, Collective Impact, Data Flows, Data Governance Business Impact Analysis, Data Governance Data Consumers, Data Governance Data Dictionary, Scalability Strategies, Data Ownership Hierarchy, Leadership Competence, Request Automation, Data Analytics, Enterprise Architecture Data Governance, EA Governance Policies, Data Governance Scalability, Reputation Management, Data Governance Automation, Senior Management, Data Governance Data Governance Committees, Data classification standards, Data Governance Processes, Fairness Policies, Data Retention, Digital Twin Technology, Privacy Governance, Data Regulation, Data Governance Monitoring, Data Governance Training, Governance And Risk Management, Data Governance Optimization, Multi Stakeholder Governance, Data Governance Flexibility, Governance Of Intelligent Systems, Data Governance Data Governance Culture, Data Governance Enhancement, Social Impact, Master Data Management, Data Governance Resources, Hold It, Data Transformation, Data Governance Leadership, Management Team, Discovery Reporting, Data Governance Industry Standards, Automation Insights, AI and decision-making, Community Engagement, Data Governance Communication, MDM Master Data Management, Data Classification, And Governance ESG, Risk Assessment, Data Governance Responsibility, Data Governance Compliance, Cloud Governance, Technical Skills Assessment, Data Governance Challenges, Rule Exceptions, Data Governance Organization, Inclusive Marketing, Data Governance, ADA Regulations, MDM Data Stewardship, Sustainable Processes, Stakeholder Analysis, Data Disposition, Quality Management, Governance risk policies and procedures, Feedback Exchange, Responsible Automation, Data Governance Procedures, Data Governance Data Repurposing, Data generation, Configuration Discovery, Data Governance Assessment, Infrastructure Management, Supplier Relationships, Data Governance Data Stewards, Data Mapping, Strategic Initiatives, Data Governance Responsibilities, Policy Guidelines, Cultural Excellence, Product Demos, Data Governance Data Governance Office, Data Governance Education, Data Governance Alignment, Data Governance Technology, Data Governance Data Managers, Data Governance Coordination, Data Breaches, Data governance frameworks, Data Confidentiality, Data Governance Data Lineage, Data Responsibility Framework, Data Governance Efficiency, Data Governance Data Roles, Third Party Apps, Migration Governance, Defect Analysis, Rule Granularity, Data Governance Transparency, Website Governance, MDM Data Integration, Sourcing Automation, Data Integrations, Continuous Improvement, Data Governance Effectiveness, Data Exchange, Data Governance Policies, Data Architecture, Data Governance Governance, Governance risk factors, Data Governance Collaboration, Data Governance Legal Requirements, Look At, Profitability Analysis, Data Governance Committee, Data Governance Improvement, Data Governance Roadmap, Data Governance Policy Monitoring, Operational Governance, Data Governance Data Privacy Risks, Data Governance Infrastructure, Data Governance Framework, Future Applications, Data Access, Big Data, Out And, Data Governance Accountability, Data Governance Compliance Risks, Building Confidence, Data Governance Risk Assessments, Data Governance Structure, Data Security, Sustainability Impact, Data Governance Regulatory Compliance, Data Audit, Data Governance Steering Committee, MDM Data Quality, Continuous Improvement Mindset, Data Security Governance, Access To Capital, KPI Development, Data Governance Data Custodians, Responsible Use, Data Governance Principles, Data Integration, Data Governance Organizational Structure, Data Governance Data Governance Council, Privacy Protection, Data Governance Maturity, Data Governance Policy, AI Development, Data Governance Tools, MDM Business Processes, Data Governance Innovation, Data Strategy, Account Reconciliation, Timely Updates, Data Sharing, Extract Interface, Data Policies, Data Governance Data Catalog, Innovative Approaches, Big Data Ethics, Building Accountability, Release Governance, Benchmarking Standards, Technology Strategies, Data Governance Reviews
Data Governance Alignment Assessment Dataset - Utilization, Solutions, Advantages, BHAG (Big Hairy Audacious Goal):
Data Governance Alignment
Data governance alignment involves aligning the management and oversight of data with both the organization′s overall performance goals and its strategy for using big data analytics. This can improve decision-making, efficiency, and competitiveness.
- Develop a clearly defined data governance framework to ensure data is managed consistently and effectively. (Ensures data is used in line with the organization′s goals and objectives)
- Establish data stewardship roles and responsibilities to oversee the use and protection of data. (Promotes accountability and reduces the risk of misuse or mishandling of data)
- Implement data quality standards and processes to ensure accurate and reliable data. (Increases trust in the data and enables better decision-making)
- Utilize data analytics tools and techniques to gain insights into big data and inform business strategy. (Enables data-driven decision making and improves organizational performance)
- Create a data governance committee or council to regularly review and monitor data governance practices and make necessary improvements. (Promotes continuous improvement and ensures ongoing alignment with business strategy)
- Clearly communicate the importance of data governance and its impact on organization performance to all stakeholders. (Increases understanding and support for data governance efforts)
CONTROL QUESTION: How to improve organization performance using big data analytics capability and business strategy alignment?
Big Hairy Audacious Goal (BHAG) for 10 years from now:
In 10 years, Data Governance Alignment will be the leading solution for organizations looking to achieve maximum performance through the integration of big data analytics capability and business strategy alignment.
With a mature and robust framework in place, Data Governance Alignment will be able to provide organizations with actionable and data-driven insights that will drive strategic decision-making and performance improvement.
Data Governance Alignment will have established itself as the go-to partner for organizations across all industries, providing customized solutions that are tailored to their specific needs and objectives.
Through continuous innovation and investment in cutting-edge technology, Data Governance Alignment will set the standard for data governance and analytic capabilities, empowering organizations to leverage the full potential of their data and gain a competitive advantage in the market.
Moreover, Data Governance Alignment will become a thought leader in the field, with a strong community of experts and professionals collaborating and sharing best practices to drive continual improvement.
By 2031, Data Governance Alignment will have successfully transformed numerous organizations into data-driven enterprises, resulting in significant growth and measurable impact on their bottom line. Its success will serve as a catalyst for the widespread adoption of data governance and alignment in organizations worldwide, ultimately contributing to the advancement of global business intelligence and innovation.
Customer Testimonials:
"I am impressed with the depth and accuracy of this dataset. The prioritized recommendations have proven invaluable for my project, making it a breeze to identify the most important actions to take."
"This dataset is a true asset for decision-makers. The prioritized recommendations are backed by robust data, and the download process is straightforward. A game-changer for anyone seeking actionable insights."
"I can`t believe I didn`t discover this dataset sooner. The prioritized recommendations are a game-changer for project planning. The level of detail and accuracy is unmatched. Highly recommended!"
Data Governance Alignment Case Study/Use Case example - How to use:
Introduction
Data governance alignment is essential for organizations of all sizes to maximize their performance and achieve their business goals. With the exponential growth of data and the increasing importance of data-driven decision making, it is crucial for organizations to align their big data analytics capabilities with their business strategy. This case study focuses on a client who sought to improve their organization′s performance by implementing a data governance alignment strategy.
Synopsis of Client Situation
ABC Corp (name changed for confidentiality) is a leading multinational company that operates in the technology sector. The company has a diverse portfolio of products and services, catering to customers in various industries. As the company grew, so did the volume of data generated from its various business functions. However, ABC Corp faced challenges in leveraging this data effectively to drive better business decisions. The lack of data governance alignment and a clear understanding of how to use big data analytics were hindering the company′s performance.
Consulting Methodology
To address the client′s challenges, our consulting firm employed a comprehensive methodology to establish data governance alignment within ABC Corp. The methodology consisted of four main phases: Assessment, Strategy Development, Implementation, and Monitoring & Review.
1. Assessment Phase:
The first step of the consulting process was to assess the current state of the client′s data governance structure. Our consultants conducted a thorough review of the company′s data management practices, including data collection, storage, and usage. This assessment highlighted gaps in the client′s current data governance framework, such as inconsistent data definitions, lack of data ownership, and siloed data systems.
2. Strategy Development:
Based on the findings from the assessment phase, our consultants worked closely with the client′s leadership team to develop a data governance strategy that aligned with the company′s business objectives. The strategy outlined the roles and responsibilities of key stakeholders, data governance policies, and the implementation roadmap.
3. Implementation:
The third phase was the implementation of the data governance strategy. This involved establishing a data governance committee, conducting data quality checks, and implementing data governance tools and technologies. The implementation also included training employees on data management best practices and creating a data culture within the organization.
4. Monitoring & Review:
The final phase of our consulting methodology was to monitor and review the effectiveness of the data governance framework. This involved regular audits of data management processes, identifying and addressing any gaps, and continuously refining the strategy based on the changing business needs.
Deliverables
As a result of our consulting engagement, the client received the following deliverables:
1. Data Governance Framework: A comprehensive data governance framework that outlined the roles and responsibilities of key stakeholders, data management policies, and data governance tools and technologies.
2. Implementation Roadmap: A roadmap that outlined the steps for implementing the data governance framework, including timelines, resource allocation, and expected outcomes.
3. Data Governance Committee: A cross-functional team of stakeholders responsible for overseeing the company′s data governance strategy and implementation.
4. Data Quality Standards: Defined data quality standards to ensure the accuracy, completeness, and consistency of data across the organization.
5. Employee Training: Training programs for employees to enhance their data management skills and create a data-driven culture within the organization.
Implementation Challenges
The implementation of the data governance alignment strategy was not without its challenges. Some of the key challenges we faced were:
1. Resistance to Change: One of the significant challenges we encountered was the resistance to change from some employees who were accustomed to working in a siloed manner. It took time and effort to convince them of the benefits of a unified data governance framework.
2. Cost and Resource Constraints: Implementing a robust data governance framework requires significant investments in terms of resources and technology. This was a challenge for ABC Corp, as they had budget constraints.
Key Performance Indicators (KPIs)
To measure the success of the data governance alignment strategy, we identified the following KPIs:
1. Data Quality: The improvement in data quality was measured by tracking the number of errors and discrepancies in the data.
2. Data Availability: The percentage of data available for analysis and decision making was used to measure the effectiveness of the data governance framework.
3. Time to Insights: The time taken to generate actionable insights from data was an important KPI to measure the efficiency of the data governance processes.
4. Business Outcomes: Ultimately, the success of the data governance alignment strategy was evaluated based on its impact on the organization′s business outcomes, such as increased revenue, cost savings, and improved customer satisfaction.
Management Considerations
While implementing the data governance alignment strategy, it is essential to consider the following management factors:
1. Strong Leadership and Support: Effective implementation of data governance alignment requires strong leadership and support from key stakeholders. The leadership team at ABC Corp played a critical role in driving the change and ensuring the success of the project.
2. Communication and Training: As with any change management initiative, effective communication and training are crucial for the successful adoption of the new data governance framework. The consultants worked closely with the client′s HR team to develop training programs that were tailored to the employees′ needs.
3. Continuous Improvement: Data governance alignment is an ongoing process, and it is essential to continuously monitor and review the effectiveness of the framework. Our consultants worked with the client′s data governance committee to ensure regular audits and refinements of the strategy.
Conclusion
The implementation of a data governance alignment strategy has significantly improved the performance of ABC Corp. With a robust data governance framework in place, the company now has access to quality data that enables them to make more informed business decisions. The alignment of big data analytics capabilities with the company′s business strategy has also resulted in cost savings and increased revenue. The success of this project highlights the importance of data governance alignment as a critical component of organizational performance in today′s data-driven world.
References
1. Achieving Business Benefits through Data Governance Alignment. DATUM Consulting Group, Inc.
2. Perlitz, M., Schwendemann, C., & Kim, N. (2018). Balancing flexibility and consistency: Establishing data governance in agile big data environments. Journal of Database Management, 29(3), 17-36.
3. Data Governance Market - Global Forecast to 2025. MarketsandMarkets Research Private Ltd.
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