Attention all professionals and businesses!
Are you tired of struggling to stay on top of governance and risk management in the ever-evolving world of data governance? Look no further than our Governance And Risk Management in Data Governance Knowledge Base!
Our dataset includes 1547 prioritized requirements, solutions, benefits, results, and case studies for Governance And Risk Management in Data Governance.
With this comprehensive knowledge base at your fingertips, you′ll have the most important questions to ask in order to get results by urgency and scope.
But what sets our product apart from competitors and alternatives? Our Governance And Risk Management in Data Governance dataset is designed specifically for professionals like you and is a more affordable option compared to similar products.
You′ll have everything you need to effectively manage your governance and risk through easy-to-use solutions and real-life examples.
Not only that, but our dataset also provides a detailed and in-depth overview of the product′s specifications, making it user-friendly and accessible for even the most novice users.
Plus, our product offers unique benefits that semi-related products just can′t match.
You don′t have to rely on expensive and complicated products any longer.
With our Governance And Risk Management in Data Governance Knowledge Base, you have a DIY and cost-effective solution that puts you in control.
Trust us, we′ve done the research for you and our dataset has proven to be a valuable asset for businesses of all sizes.
So why wait? Take the first step towards better data governance today with our Governance And Risk Management in Data Governance Knowledge Base.
Say goodbye to confusion and hello to effective risk management.
Unlock the potential of your data and give your business a competitive edge.
Order now and see the transformative results for yourself!
What data governance exists in your organization, and what requirements do you need to meet throughout the data management lifecycle?
Governance And Risk Management
Governance and risk management involves identifying and implementing policies and procedures to effectively manage data within an organization, including data governance measures and compliance with data management requirements.
1. Implement a Data Governance Framework - This will provide guidelines and policies for managing data, ensuring consistency and compliance.
2. Establish a Data Governance Committee - Bring together stakeholders from across the organization to oversee data governance efforts and make key decisions.
3. Conduct Data Risk Assessments - Regularly assess potential risks to data and create strategies to mitigate or eliminate them.
4. Develop Data Management Processes - Clearly define processes for data collection, storage, access, and usage to ensure consistency and security.
5. Train Employees on Data Governance - Educate employees on best practices and policies for handling data to reduce human error and ensure compliance.
6. Use Data Quality Tools - Invest in software tools to monitor data quality and identify areas for improvement.
7. Implement Data Privacy Measures - Implement measures such as data encryption and access controls to protect sensitive data.
8. Conduct Audits - Regularly audit data governance processes and systems to ensure compliance and identify areas for improvement.
9. Monitor and Measure Data Governance - Set performance indicators and regularly measure and report on the effectiveness of data governance efforts.
10. Continuously Improve Data Governance - Regularly review and update data governance policies and processes to adapt to changing requirements and technologies.
CONTROL QUESTION: What data governance exists in the organization, and what requirements do you need to meet throughout the data management lifecycle?
Big Hairy Audacious Goal (BHAG) for 10 years from now:
In 10 years, the organization will have a comprehensive and progressive governance and risk management system in place that is continuously evolving to meet the ever-changing data landscape. This system will be rooted in the principles of transparency, accountability, and inclusivity, with a focus on responsible data stewardship and protection.
Through a robust data governance framework, all data assets will be identified, classified, and governed according to their level of sensitivity and importance. The organization will have clear policies, procedures, and standards in place for data access, handling, sharing, and retention. These guidelines will be regularly reviewed and adapted to comply with new regulatory requirements and best practices.
The organization will also have an established data management lifecycle, consisting of well-defined processes for data collection, storage, processing, analysis, and disposal. These processes will be supported by cutting-edge technologies and tools, promoting efficiency and effectiveness in managing data.
To achieve this BHAG, the organization will engage in continuous training and education programs for all employees to instill a strong culture of data governance and risk management. Regular audits and assessments will also be conducted to monitor compliance and identify areas for improvement.
Furthermore, the organization will collaborate with other industry leaders and experts to stay abreast of emerging technologies and practices in data governance and risk management. This will ensure that the organization remains at the forefront of data protection and sets the standard for responsible data management in the industry.
Ultimately, my goal is for the organization to be recognized as a leader in data governance and risk management, setting the benchmark for other organizations to follow. This will not only enhance the trust and confidence of our stakeholders but also ensure the long-term sustainability and success of the organization.
"This dataset has been a game-changer for my business! The prioritized recommendations are spot-on, and I`ve seen a significant improvement in my conversion rates since I started using them."
Synopsis:
This case study focuses on the data governance and risk management practices of a medium-sized retail company, XYZ Corporation. The company has been in the retail business for over 20 years and has expanded its operations globally. With a large customer base and vast amounts of data being generated every day, the company realized the need for a comprehensive data governance framework to ensure the accuracy, integrity, and security of its data. The lack of data governance was hindering the company′s ability to make informed decisions and comply with regulatory requirements. Thus, they hired a consulting firm, ABC Consulting, to assist them in implementing a data governance program.
Consulting Methodology:
ABC Consulting follows a structured methodology for data governance implementation, which includes five phases - Assessment, Planning, Implementation, Monitoring, and Improvement. In the assessment phase, the team conducted interviews and workshops with key stakeholders to understand the existing data management practices, identify gaps, and define the scope of data governance. This phase also involved assessing the company′s IT infrastructure, data storage systems, and data processes. The planning phase involved creating a data governance roadmap, defining roles and responsibilities, and selecting appropriate tools and technologies. In the implementation phase, the data governance framework was established, and policies and procedures were developed. The monitoring phase involved regular audits and reviews of the data governance program′s effectiveness, and the improvement phase focused on continuously enhancing and optimizing the data governance processes.
Deliverables:
The deliverables of this data governance consulting engagement included a data governance policy document, data standards and guidelines, a data inventory, a data governance committee charter, and a data governance roadmap. The policy document outlined the principles, goals, and responsibilities of data governance, while the data standards and guidelines provided a set of rules and procedures for managing data across the organization. The data inventory included a detailed list of all the company′s data assets, along with their ownership and usage. The data governance committee charter defined the roles and responsibilities of the data governance committee members, whose primary focus was to oversee and enforce data governance activities. Lastly, the data governance roadmap provided a clear plan for implementing and sustaining the data governance framework in the organization.
Implementation Challenges:
One of the biggest challenges faced during the implementation of the data governance program was getting buy-in from all stakeholders. The project team had to convince the leadership team and other business units of the importance and benefits of data governance. Another challenge was aligning data governance with existing processes and systems, without disrupting the day-to-day operations of the business. Moreover, there was a lack of awareness and understanding of data governance among employees, which made it challenging to enforce data governance policies and procedures.
KPIs:
The success of the data governance program was measured using key performance indicators (KPIs) such as data quality, data availability, data accuracy and integrity, IT system uptime, and user adoption rate. These KPIs were tracked regularly and compared against the set targets to evaluate the effectiveness of the data governance program.
Management Considerations:
Data governance is an ongoing process that requires continuous monitoring and improvement. Therefore, XYZ Corporation has established a data governance committee to oversee and manage the data governance program. The committee meets quarterly to review the progress of data governance initiatives and address any issues or concerns. Additionally, the company has also invested in training and development programs to educate employees about the importance of data governance and to ensure compliance with data governance policies and procedures.
Citations:
The consulting methodology followed by ABC Consulting is based on industry best practices and recommendations from several consulting whitepapers. One such paper, Best Practices for Data Governance by Gartner, highlights the five essential phases of data governance implementation, which aligns with ABC Consulting′s methodology (Gartner, 2018).
Academic business journals, such as The Role of Data Governance in Business Performance: A Conceptual Model and Research Propositions by Yilma et al. (2018), have emphasized the importance of data governance in improving business performance and decision-making. This study also highlights the need for establishing a data governance committee to oversee and manage data governance activities effectively.
According to the Global Data Governance Market Report 2020-2025 by ResearchAndMarkets.com, there has been a significant increase in the adoption of data governance solutions among organizations due to the increasing volume and complexity of data. This report also emphasizes the importance of having a well-defined data governance policy and roadmap in place to ensure successful implementation (ResearchAndMarkets.com, 2020).
Conclusion:
In conclusion, the implementation of a robust data governance program has enabled XYZ Corporation to effectively manage and utilize its vast amount of data. With the help of ABC Consulting, the company was able to establish a comprehensive data governance framework, which has improved data quality, accuracy, and availability. The data governance program has also helped the organization comply with data protection regulations and make more informed business decisions. The involvement and support of all stakeholders have been crucial in the success of this program, and the company continues to monitor and refine its data governance practices to ensure data remains a valuable asset to the organization.
Are you tired of struggling to stay on top of governance and risk management in the ever-evolving world of data governance? Look no further than our Governance And Risk Management in Data Governance Knowledge Base!
Our dataset includes 1547 prioritized requirements, solutions, benefits, results, and case studies for Governance And Risk Management in Data Governance.
With this comprehensive knowledge base at your fingertips, you′ll have the most important questions to ask in order to get results by urgency and scope.
But what sets our product apart from competitors and alternatives? Our Governance And Risk Management in Data Governance dataset is designed specifically for professionals like you and is a more affordable option compared to similar products.
You′ll have everything you need to effectively manage your governance and risk through easy-to-use solutions and real-life examples.
Not only that, but our dataset also provides a detailed and in-depth overview of the product′s specifications, making it user-friendly and accessible for even the most novice users.
Plus, our product offers unique benefits that semi-related products just can′t match.
You don′t have to rely on expensive and complicated products any longer.
With our Governance And Risk Management in Data Governance Knowledge Base, you have a DIY and cost-effective solution that puts you in control.
Trust us, we′ve done the research for you and our dataset has proven to be a valuable asset for businesses of all sizes.
So why wait? Take the first step towards better data governance today with our Governance And Risk Management in Data Governance Knowledge Base.
Say goodbye to confusion and hello to effective risk management.
Unlock the potential of your data and give your business a competitive edge.
Order now and see the transformative results for yourself!
Discover Insights, Make Informed Decisions, and Stay Ahead of the Curve:
Key Features:
Comprehensive set of 1547 prioritized Governance And Risk Management requirements. - Extensive coverage of 236 Governance And Risk Management topic scopes.
- In-depth analysis of 236 Governance And Risk Management step-by-step solutions, benefits, BHAGs.
- Detailed examination of 236 Governance And Risk Management 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
Governance And Risk Management Assessment Dataset - Utilization, Solutions, Advantages, BHAG (Big Hairy Audacious Goal):
Governance And Risk Management
Governance and risk management involves identifying and implementing policies and procedures to effectively manage data within an organization, including data governance measures and compliance with data management requirements.
1. Implement a Data Governance Framework - This will provide guidelines and policies for managing data, ensuring consistency and compliance.
2. Establish a Data Governance Committee - Bring together stakeholders from across the organization to oversee data governance efforts and make key decisions.
3. Conduct Data Risk Assessments - Regularly assess potential risks to data and create strategies to mitigate or eliminate them.
4. Develop Data Management Processes - Clearly define processes for data collection, storage, access, and usage to ensure consistency and security.
5. Train Employees on Data Governance - Educate employees on best practices and policies for handling data to reduce human error and ensure compliance.
6. Use Data Quality Tools - Invest in software tools to monitor data quality and identify areas for improvement.
7. Implement Data Privacy Measures - Implement measures such as data encryption and access controls to protect sensitive data.
8. Conduct Audits - Regularly audit data governance processes and systems to ensure compliance and identify areas for improvement.
9. Monitor and Measure Data Governance - Set performance indicators and regularly measure and report on the effectiveness of data governance efforts.
10. Continuously Improve Data Governance - Regularly review and update data governance policies and processes to adapt to changing requirements and technologies.
CONTROL QUESTION: What data governance exists in the organization, and what requirements do you need to meet throughout the data management lifecycle?
Big Hairy Audacious Goal (BHAG) for 10 years from now:
In 10 years, the organization will have a comprehensive and progressive governance and risk management system in place that is continuously evolving to meet the ever-changing data landscape. This system will be rooted in the principles of transparency, accountability, and inclusivity, with a focus on responsible data stewardship and protection.
Through a robust data governance framework, all data assets will be identified, classified, and governed according to their level of sensitivity and importance. The organization will have clear policies, procedures, and standards in place for data access, handling, sharing, and retention. These guidelines will be regularly reviewed and adapted to comply with new regulatory requirements and best practices.
The organization will also have an established data management lifecycle, consisting of well-defined processes for data collection, storage, processing, analysis, and disposal. These processes will be supported by cutting-edge technologies and tools, promoting efficiency and effectiveness in managing data.
To achieve this BHAG, the organization will engage in continuous training and education programs for all employees to instill a strong culture of data governance and risk management. Regular audits and assessments will also be conducted to monitor compliance and identify areas for improvement.
Furthermore, the organization will collaborate with other industry leaders and experts to stay abreast of emerging technologies and practices in data governance and risk management. This will ensure that the organization remains at the forefront of data protection and sets the standard for responsible data management in the industry.
Ultimately, my goal is for the organization to be recognized as a leader in data governance and risk management, setting the benchmark for other organizations to follow. This will not only enhance the trust and confidence of our stakeholders but also ensure the long-term sustainability and success of the organization.
Customer Testimonials:
"This dataset has been a game-changer for my business! The prioritized recommendations are spot-on, and I`ve seen a significant improvement in my conversion rates since I started using them."
"As a data scientist, I rely on high-quality datasets, and this one certainly delivers. The variables are well-defined, making it easy to integrate into my projects."
"This dataset was the perfect training ground for my recommendation engine. The high-quality data and clear prioritization helped me achieve exceptional accuracy and user satisfaction."
Governance And Risk Management Case Study/Use Case example - How to use:
Synopsis:
This case study focuses on the data governance and risk management practices of a medium-sized retail company, XYZ Corporation. The company has been in the retail business for over 20 years and has expanded its operations globally. With a large customer base and vast amounts of data being generated every day, the company realized the need for a comprehensive data governance framework to ensure the accuracy, integrity, and security of its data. The lack of data governance was hindering the company′s ability to make informed decisions and comply with regulatory requirements. Thus, they hired a consulting firm, ABC Consulting, to assist them in implementing a data governance program.
Consulting Methodology:
ABC Consulting follows a structured methodology for data governance implementation, which includes five phases - Assessment, Planning, Implementation, Monitoring, and Improvement. In the assessment phase, the team conducted interviews and workshops with key stakeholders to understand the existing data management practices, identify gaps, and define the scope of data governance. This phase also involved assessing the company′s IT infrastructure, data storage systems, and data processes. The planning phase involved creating a data governance roadmap, defining roles and responsibilities, and selecting appropriate tools and technologies. In the implementation phase, the data governance framework was established, and policies and procedures were developed. The monitoring phase involved regular audits and reviews of the data governance program′s effectiveness, and the improvement phase focused on continuously enhancing and optimizing the data governance processes.
Deliverables:
The deliverables of this data governance consulting engagement included a data governance policy document, data standards and guidelines, a data inventory, a data governance committee charter, and a data governance roadmap. The policy document outlined the principles, goals, and responsibilities of data governance, while the data standards and guidelines provided a set of rules and procedures for managing data across the organization. The data inventory included a detailed list of all the company′s data assets, along with their ownership and usage. The data governance committee charter defined the roles and responsibilities of the data governance committee members, whose primary focus was to oversee and enforce data governance activities. Lastly, the data governance roadmap provided a clear plan for implementing and sustaining the data governance framework in the organization.
Implementation Challenges:
One of the biggest challenges faced during the implementation of the data governance program was getting buy-in from all stakeholders. The project team had to convince the leadership team and other business units of the importance and benefits of data governance. Another challenge was aligning data governance with existing processes and systems, without disrupting the day-to-day operations of the business. Moreover, there was a lack of awareness and understanding of data governance among employees, which made it challenging to enforce data governance policies and procedures.
KPIs:
The success of the data governance program was measured using key performance indicators (KPIs) such as data quality, data availability, data accuracy and integrity, IT system uptime, and user adoption rate. These KPIs were tracked regularly and compared against the set targets to evaluate the effectiveness of the data governance program.
Management Considerations:
Data governance is an ongoing process that requires continuous monitoring and improvement. Therefore, XYZ Corporation has established a data governance committee to oversee and manage the data governance program. The committee meets quarterly to review the progress of data governance initiatives and address any issues or concerns. Additionally, the company has also invested in training and development programs to educate employees about the importance of data governance and to ensure compliance with data governance policies and procedures.
Citations:
The consulting methodology followed by ABC Consulting is based on industry best practices and recommendations from several consulting whitepapers. One such paper, Best Practices for Data Governance by Gartner, highlights the five essential phases of data governance implementation, which aligns with ABC Consulting′s methodology (Gartner, 2018).
Academic business journals, such as The Role of Data Governance in Business Performance: A Conceptual Model and Research Propositions by Yilma et al. (2018), have emphasized the importance of data governance in improving business performance and decision-making. This study also highlights the need for establishing a data governance committee to oversee and manage data governance activities effectively.
According to the Global Data Governance Market Report 2020-2025 by ResearchAndMarkets.com, there has been a significant increase in the adoption of data governance solutions among organizations due to the increasing volume and complexity of data. This report also emphasizes the importance of having a well-defined data governance policy and roadmap in place to ensure successful implementation (ResearchAndMarkets.com, 2020).
Conclusion:
In conclusion, the implementation of a robust data governance program has enabled XYZ Corporation to effectively manage and utilize its vast amount of data. With the help of ABC Consulting, the company was able to establish a comprehensive data governance framework, which has improved data quality, accuracy, and availability. The data governance program has also helped the organization comply with data protection regulations and make more informed business decisions. The involvement and support of all stakeholders have been crucial in the success of this program, and the company continues to monitor and refine its data governance practices to ensure data remains a valuable asset to the organization.
Security and Trust:
- Secure checkout with SSL encryption Visa, Mastercard, Apple Pay, Google Pay, Stripe, Paypal
- Money-back guarantee for 30 days
- Our team is available 24/7 to assist you - support@theartofservice.com
About the Authors: Unleashing Excellence: The Mastery of Service Accredited by the Scientific Community
Immerse yourself in the pinnacle of operational wisdom through The Art of Service`s Excellence, now distinguished with esteemed accreditation from the scientific community. With an impressive 1000+ citations, The Art of Service stands as a beacon of reliability and authority in the field.Our dedication to excellence is highlighted by meticulous scrutiny and validation from the scientific community, evidenced by the 1000+ citations spanning various disciplines. Each citation attests to the profound impact and scholarly recognition of The Art of Service`s contributions.
Embark on a journey of unparalleled expertise, fortified by a wealth of research and acknowledgment from scholars globally. Join the community that not only recognizes but endorses the brilliance encapsulated in The Art of Service`s Excellence. Enhance your understanding, strategy, and implementation with a resource acknowledged and embraced by the scientific community.
Embrace excellence. Embrace The Art of Service.
Your trust in us aligns you with prestigious company; boasting over 1000 academic citations, our work ranks in the top 1% of the most cited globally. Explore our scholarly contributions at: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=blokdyk
About The Art of Service:
Our clients seek confidence in making risk management and compliance decisions based on accurate data. However, navigating compliance can be complex, and sometimes, the unknowns are even more challenging.
We empathize with the frustrations of senior executives and business owners after decades in the industry. That`s why The Art of Service has developed Self-Assessment and implementation tools, trusted by over 100,000 professionals worldwide, empowering you to take control of your compliance assessments. With over 1000 academic citations, our work stands in the top 1% of the most cited globally, reflecting our commitment to helping businesses thrive.
Founders:
Gerard Blokdyk
LinkedIn: https://www.linkedin.com/in/gerardblokdijk/
Ivanka Menken
LinkedIn: https://www.linkedin.com/in/ivankamenken/
