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Data Governance Inside a Big Bank: Best Practices and Project Plan


M. Allen's take on this key topic: Big banks face unprecedented challenges in managing and governing their vast amounts of data. Effective data governance is crucial for maintaining data quality, ensuring compliance with regulations, and leveraging data for informed decision-making. In this blog post, we will explore the top twenty best practices for data governance within a big bank, along with a detailed project plan or Work Breakdown Structure (WBS) to help facilitate successful implementation.



Best Practices for Data Governance in a Big Bank:


1. Establish a Data Governance Framework: Define the goals, objectives, and scope of data governance initiatives within the bank.


2. Appoint a Data Governance Team: Assemble a cross-functional team of stakeholders responsible for overseeing data governance efforts.


3. Develop Data Governance Policies: Create comprehensive policies that outline data ownership, access controls, data classification, and data retention.


4. Implement Data Stewardship: Assign data stewards responsible for data quality, metadata management, and resolving data-related issues.


5. Conduct Data Inventory: Perform a thorough inventory of all data assets, including databases, applications, and data sources.


6. Define Data Standards: Establish consistent data standards, naming conventions, and data definitions across the organization.


7. Ensure Data Quality: Implement data quality controls, data validation processes, and data cleansing techniques to maintain accurate and reliable data.


8. Enforce Data Security and Privacy Measures: Implement robust security protocols, access controls, encryption, and privacy policies to protect sensitive data.


9. Establish Data Classification: Categorize data based on its sensitivity, criticality, and regulatory requirements to determine appropriate handling and protection measures.


10. Implement Data Lifecycle Management: Define the stages of data lifecycle, including data creation, storage, archival, and disposal.


11. Enable Data Lineage and Traceability: Establish mechanisms to track data lineage, understand data origins, transformations, and ensure auditability.


12. Perform Data Risk Assessments: Conduct regular risk assessments to identify potential vulnerabilities and mitigate data-related risks.


13. Foster Data Governance Awareness and Training: Provide comprehensive training programs to educate employees about data governance principles, policies, and best practices.


14. Establish Data Governance Metrics: Define key performance indicators (KPIs) to measure the effectiveness of data governance initiatives.


15. Enable Data Governance Tools: Invest in robust data governance software solutions to automate and streamline data governance processes.


16. Ensure Regulatory Compliance: Stay up-to-date with applicable data protection and privacy regulations and ensure compliance within the organization.


17. Foster Collaboration and Communication: Encourage cross-functional collaboration to facilitate effective data governance, and establish clear channels of communication.


18. Conduct Regular Data Audits: Perform periodic data audits to assess data quality, compliance, and adherence to data governance policies.


19. Continuously Improve Data Governance: Regularly review and refine data governance processes to adapt to changing business needs and emerging technologies.


20. Foster a Data Governance Culture: Instill a culture of data governance and accountability throughout the organization by fostering data-driven decision-making and transparency.


Data Governance Project Plan (Work Breakdown Structure - WBS):


1. Project Initiation

- Define project objectives and scope

- Formulate project team and roles

- Develop project charter


2. Data Governance Assessment

- Conduct a comprehensive assessment of existing data governance practices

- Identify gaps and areas for improvement

- Define project deliverables and success criteria


3. Data Governance Framework Development

- Define data governance goals, objectives, and guiding principles

- Establish governance structure and roles

- Create data governance policies and procedures


4. Data Governance Implementation

- Develop data stewardship program and assign roles

- Implement data quality controls and data validation processes

- Establish data security and privacy measures


5. Data Governance Communication and Training

- Develop training programs for employees on data governance practices

- Create communication plans to raise awareness and foster engagement


6. Data Governance Monitoring and Reporting

- Define key performance indicators (KPIs) for data governance

- Implement monitoring mechanisms and reporting processes

- Conduct regular audits to assess compliance and effectiveness


7. Continuous Improvement and Optimization

- Evaluate the effectiveness of data governance initiatives

- Identify areas for improvement and implement necessary changes

- Continuously optimize data governance processes and policies


Implementing effective data governance within a big bank is a complex but essential endeavor. By following the top twenty best practices outlined in this blog post and adhering to the project plan, banks can establish a robust data governance framework, ensure data quality and security, and leverage data as a strategic asset. Data governance is not a one-time effort but an ongoing process that requires continuous monitoring, improvement, and adaptation to ever-evolving data landscapes.


Budget and Resource Allocation for Data Governance Program: Allocating and managing financial resources is crucial for the successful implementation and sustainability of a data governance program within a big bank. Here's a breakdown of how you could budget and allocate $3 million per year for overseeing the program, along with key roles and the required experience: 1. Data Governance Program Manager (Full-time, $200,000 per year): - Responsible for overall program management, coordination, and strategic planning. - Experience: Proven track record in managing complex data governance initiatives, strong leadership skills, and understanding of regulatory requirements. 2. Data Governance Analysts (2 Full-time, $150,000 per year each): - Support the program manager in data governance activities, data analysis, policy development, and implementation. - Experience: Strong analytical abilities, knowledge of data governance frameworks and best practices, and proficiency in data management tools. 3. Data Stewards (6 Part-time, $100,000 per year each): - Serve as subject matter experts in specific data domains, ensuring data quality, metadata management, and resolving data-related issues. - Experience: Deep understanding of data domains, data management experience, and ability to collaborate with various stakeholders. 4. Data Privacy and Security Specialist (Full-time, $180,000 per year): - Responsible for ensuring data privacy and security measures are in place, assessing risks, and implementing appropriate controls. - Experience: Expertise in data privacy and security regulations, knowledge of encryption techniques, and experience in managing data breaches. 5. Data Governance Tool Implementation and Maintenance (One-time cost of $500,000 in the first year, with annual maintenance costs of $150,000): - Investment in robust data governance software solutions to automate and streamline data governance processes. - Experience: Expertise in data governance tools, data integration, and data management technologies. 6. Training and Communication (Annual cost of $200,000): - Conduct comprehensive training programs for employees on data governance principles, policies, and best practices. - Develop communication plans to raise awareness and foster engagement throughout the organization. 7. External Audit and Compliance Support (Annual cost of $200,000): - Engage external audit firms to conduct regular data audits, assess compliance, and provide expertise in regulatory requirements. - Experience: Strong understanding of data governance principles, regulatory compliance, and experience in conducting audits. 8. Continuous Improvement and Optimization (Annual cost of $200,000): - Allocate funds for process optimization, technology upgrades, and adapting data governance practices to evolving business needs. It's important to note that the above figures are approximate and can vary depending on the specific requirements and size of the big bank. Regular financial reviews and adjustments should be conducted to ensure the effective utilization of the allocated budget. By budgeting and allocating resources strategically, the big bank can ensure that it has the necessary expertise, tools, and support to oversee the data governance program effectively, protecting valuable data assets and promoting a culture of data-driven decision-making.


Matt Slonaker Founder & CEO of M. Allen (E)mslonaker@mattallendevelopment.com (W) www.mattallendevelopment.com

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