Kash Mehdi, Customer Success Manager
- Implement the Operating Model
- Identify data domains
- Identify critical data elements within domains
We are going to review the four best Data Governance practices when launching a Data Governance program. The first step is to focus on the operating model. This is a key element of your Data Governance journey, so in this phase you’re going to define roles, responsibilities. The next step in this process is identification of data domains. This will involve managing key information assets through the Collibra Platform, where you define domains, glossaries, dictionaries, data catalog, the business processes around managing customer information. The third point is identifying the critical data elements within your domains. The fourth and final step is defining control measurements. Now that you defined structure, domains, identified what’s really critical, it takes us to this control measurement, which includes some key activities.
Lowell Fryman, Customer Success Practice Principal
- Understand the measurable value of initiating a Data Governance program
- Develop use cases with defined business value propositions
- Outline the activities in developing a business case
This course provides an introduction to the principles and practices of Data Governance. We will review the business relevance of data governance and how to establish the business value proposition, use cases, and business cases. Data Governance leadership should focus on identifying specific business value statements that will drive the establishment and roadmap for the Data Governance program. Consider the desired outcomes, potential improvements, business value, and financial returns. The major business value propositions are addressed in use cases from the perspectives of stakeholders and executives. Define the use cases and business case to state the intended outcomes and associated financial considerations. These practices will guide you towards developing and implementing your Data Governance program!
Matt Tager, Account Executive
- Understand Data Governance strategy
- Create Data Governance councils and roles
- Use the RACI Matrix to assign roles
This course will take you through the foundation of creating roles and responsibilities within your Data Governance program. We will discuss forming your Data Governance council and key members to include. We will review the roles and collaboration of the Data and Technical Stewards, ensuring business users have access to the data they need to fulfill their job responsibilities. Finally, we will review using the RACI Matrix to map roles and responsibilities to team members.
Jonelle Miller, Account Executive
- Understanding data-driven organizations
- Defining Data Governance
- Operating the Collibra Platform
This course will allow you to understand what it means to be a data-driven organization. Being data-driven influences the culture, the decision-making processes, operations, and the people in an organization. Adopting a data governance model and implementing new processes will result in business-driven systems designed for business users. This culminates in everyone in your organization is able to find, understand and trust the data. Finally, there will be a brief demonstration of the applications within the Collibra Platform.
Stijn Christiaens, Chief Technology Officer
- Demonstrate the value of data
- Assign roles based on organizational structure
- Apply metrics for process improvements
Why are you a Data Citizen? In this course, we will discuss the value of data as a strategic asset. We will review how data can be applied for greater analysis and insights, leading to productive changes in your business or organization. Data Governance enables your team to set up processes to find the data they need, to know who produced it and when it was last updated. The data can then be used for reporting needs, allowing you to confidently draw conclusions and avoid any data brawls leading to conflicting reports and analysis. Capture metrics to apply analytics and continuously improve your processes, thereby getting more and more value at an organization level out of your data.