How do you assign roles for your data architecture?

Understand Your Data Landscape: Before assigning roles, you need to have a clear understanding of the data you're dealing with, its sources, its destinations, and the processes it undergoes. Each role should have a clear definition, responsibilities, and boundaries. Data Architect: Designs the high-level structure of the data environment, ensuring that data is stored, processed, and accessed efficiently. Database Administrator (DBA): Manages and maintains the database environment. This includes performance tuning, backup and recovery, and security. Data Engineer: Focuses on building infrastructure for data generation, conversion, and storage. Data Scientist: Uses statistical, mathematical, and computational methods to analyze data.

Assigning the right data governance roles is critical for effective data management. Key roles include Data Stewards responsible for data quality and policies, Data Owners overseeing specific data domains, Data Custodians managing technical aspects, Data Governance Managers directing the program, Compliance Officers ensuring regulation adherence, Data Quality Managers focusing on data quality, Data Architects handling data structures, Business and Data Analysts analyzing and validating data, IT Administrators managing infrastructure, and Data Users relying on data for decision-making. Properly align these roles based on organization size and needs to establish a robust data governance framework aligned with data architecture.

A data governance framework will impact all data domains including the roles you assign and when to create them. It is important to identify the appropriate starting point for your organization’s data governance framework. If you start with a formal framework in a smaller organization then planning, monitoring, and enforcement may be seen as a burden and ignored all together. If you attempt an agile framework at a large organization there might not be enough guardrails setup to enforce policies, and best practices resulting in poor data asset management.

That's Right! Consider it a collaborative dance where data owners, stewards, custodians, and users all contribute in different ways to maintain the harmony of your data. Imagine that your data privacy officers and data ethics champions have joined the team to ensure that your data is reliable and compliant with ethical standards. This team works as a unit to make sure that your data journey is both effective and responsible.

I organize data governance roles into 3 categories: Contributing roles, Shaping roles, and Consumer roles. Individuals can be in multiple roles across the different categories. Contributing roles provide critical input like Business Strategies and Regulatory Requirements that will be used by people in the Shaping roles. The Shaping roles will produce the Data Governance Strategy and will include key outputs like a Business and Data Governance Roadmap. Others in the Shaping role will be critical in implementing the policies and best practices that the Consumer roles will use. The Consumer roles will leverage the data governance framework while developing data solutions that often involve multiple data domains at once.

The tools around data governance have evolved significantly over the last few years. Many will help you associate data assets with data stewards and subject-matter-experts, and even enable collaboration. Beyond the tools I will often use a RACI assignment matrix to track the data governance roles and assignments. I find it especially helpful when you assign named resources to each role. Be sure to include any steering committees in the RACI, because there will be a lot of communication and decisions from those roles.