Version: 2.0-rc

Data Architect

Role overview

note

Your mission: You define how data is structured, processed, and managed across the Platform. Your goal is to establish standards, integrate data, and ensure that data can be consistently used and reused.

Why your role is vital: You are the "Architect". You create the foundation that enables all data-related work. Without your structures, standards, and integrations, Datasets cannot be created, processed, or reused.

Defining your scope: You work across the Platform on Datapools, Data structures, Data sources, Pipelines, and APIs. You define standards and enable others to create, manage, and use data-related elements.

Your core responsibilities

Define standards and guidelines: You define Data structures, metadata standards, and reusable patterns across the tenant.
Manage data architecture: You create and maintain Data structures, Data sources, and pipelines across the Platform.
Organize data domains: Structure related Datasets using Datapools and define shared governance where appropriate
Enable data processing: You ensure data can be ingested, transformed, stored, and provided consistently.
Support the organization: You work across domains and support other Roles in building and using data-related elements.

Outside your scope

It is not your responsibility to release Datasets or govern access policies.

If you are responsible for reviewing and releasing Datasets, the Data Owner or Data Gatekeeper role is likely the right role for you.

Understanding the Authorisation Logic

To work effectively with data-related elements, you need the correct permissions.

The access logic: Access is always the result of a User being assigned to a Group, and that Group being assigned a Role at a specific Scope.

Scopes: Roles apply either at Platform level, on a Datapool, or on a specific data-related element such as a Dataset, Data source, or Data structure.

To create and manage data-related elements, your Group typically needs a Data Role with create Permissions at Platform scope.

→ Deep Dive Authorisation

Typical tasks

Your work in CIVITAS/CORE focuses on designing and managing data-related elements across the Platform:

Design Data structures: Create and version Data structures based on defined standards
Register Data sources: Connect systems and ensure data is ingested correctly
Organize Datasets using Datapools: Provide an additional scope for access management
Build pipelines and configure APIs: Define how data is ingested, transformed, and prepared for use
Prepare Datasets for further use: Ensure Datasets are complete and ready for review by Data Owner or Data Gatekeeper

Your first steps

To start working as a Data Architect in CIVITAS/CORE:

Check that your Group has a Data Role with create Permissions at Platform scope
Explore existing Data structures and Data sources in the Platform
Create your first Data structure
Create your first Data source and link it to the Data structure
Create your first Dataset and assign it to a Datapool (recommended)
Build your first Pipeline
Configure APIs and manage access permissions

Recommendation

Whenever possible, manage access at Datapool level. Use Dataset-specific permissions only when individual Datasets require different access rules.

Best practices & avoiding mistakes

Work with reusable Data structures: Design Data structures so they can be reused across multiple Datasets
Keep pipelines clear and maintainable: Avoid overly complex pipeline logic. Keep transformations understandable
Separate responsibilities: Focus on building and preparing data. Data Stewards handle the detailed configuration of Datasets, while Data Owners and Gatekeepers are responsible for release decisions
Use Datapools to organize related Datasets: This simplifies access management and Data source availability
Ensure proper access setup: Make sure your Group has the required platform-wide Data Role to create data-related elements
Enable Data Stewards through access: Assign Data Roles to Groups on the relevant Datasets, Data sources, and Data structures so Data Stewards can work on them.

Common pitfall: Missing access on connected elements

When working with pipelines, make sure access is assigned across all involved data-related elements.

If a Dataset uses a Data source or Data structure, the required Group + Role assignment must exist on each of them. When using Datapools, remember that permission inheritance does not automatically grant access to referenced Data sources or Data structures.

Otherwise, your collaborators may not be able to select Data sources or Data structures and configure or run pipelines.

Your permissions

Permissions / Data-related elements	READ	CREATE	UPDATE	DELETE
Dataset	🟢	🟢	🟢	🟢
↳ Payload
Data source	🟢	🟢	🟢	🟢
Data structure	🟢	🟢	🟢	🟢
Datapool	🟢	🟢	🟢	🟢

Key terms to know

To work effectively as a Data Architect, review these terms in our Glossary:

Data structure: Defines the schema and structure of data
Data source: Represents the origin of data.
Dataset: A structured collection of data prepared for use
Pipeline: Defines how data is loaded, transformed, and stored
Data Role: A Role that grants access to data-related elements
Scope: Defines where a Role applies, either on Platform level or on a specific data-related element
Datapool: Organizes related Datasets and provides an additional scope for access management and Data source availability

Deep Dives

→ Authorisation

→ Design Data structures

→ Connect external Data

→ Persist, transform & provide Data

Role overview​

Your core responsibilities​

Outside your scope​

Typical tasks​

Your first steps​

Best practices & avoiding mistakes​

Your permissions​

Key terms to know​

Deep Dives​