Platform Personas

A ‘persona’ refers to a predefined user profile that groups together specific roles, permissions, and platform capabilities. Personas help simplify user management by assigning a set of responsibilities, tools, and access levels to users based on what they need to do on the platform.

Harbr has three primary platform personas that your Organization can map its own user personas against. They include:

Platform Operators

• Accelerate data access across your ecosystem by championing flexibility, governance, self-service, and collaboration.

• Share a vision for the platform and motivate team members to adopt it.

• Define organization types and set privacy between them.

• Invite users and teams to the platform and assigning user roles.

• Visibility over user activity.

This persona may describe users within your Organization who manage the platform and administer configurations.

Data Producers

• Define, maintain, and promote discoverable, usable, high-quality data products. They ensure products are legally compliant, flexible and secure. 

• Connect data from sources using connectors.

• Create, manage, and share assets.

• Combine assets to create products with specific value propositions.

• Apply visibility to data products.

• Support and collaborate with consumers in Spaces to help them derive value from data products.

This persona may describe users within your Organization who supply and manage datasets on platform.

Data Consumers

• Access, evaluate, and customize data, develop models, and generate insights. 

• Browse for data products to use in visualizations or SQL labs.

• Bring people, tools, and data together in secure, on-demand cloud environments.

• Query assets via SQL or AI-assisted questions.

• Consume and freely distribute data products off-platform.

This persona may describe users within your Organization who work as analysts, engineers or anyone looking to utilize data for insights.

Remember: A singular user may behave as multiple personas on your platform, switching ‘hats’ based on how they intend to interact with the data and tools.