Transformation Flows
I led the initial concept definition and UX design of Transformation Flows: defining user journeys, prototyping in UI5/Figma, testing with Data Modelers, and collaborating with PM & Engineering, before handing off the project to another designer to carry forward to completion.
Jan 2, 2023
CLIENT
SAP
CLIENT
SAP
CLIENT
SAP
Role
Designer
Role
Designer
Role
Designer
Service
UX Design
Service
UX Design
Service
UX Design
Work Details
Work Details
Work Details
Context
Transformation Flows are part of SAP Datasphere’s Data Builder, enabling Data Modelers to load data from one or more sources, apply SQL-based or graphical transformations, and output the results into target tables. This feature fills a key gap between simple data loading and advanced modeling.
Problem Statement
Before this feature, Data Modelers lacked a straightforward way to transform data as it moved between sources and targets. Workarounds required external tools or overloading other flow types, creating inefficiencies and governance risks.
My Role
I initiated the UX design for Transformation Flows, focusing on the concept definition and early design exploration. My responsibilities included:
Researching user needs and defining initial user journeys.
Creating early prototypes in Figma and UI5 aligned with the Data Builder canvas.
Exploring multiple design directions and identifying dead ends.
Collaborating with Product Management and Engineering to scope feasible solutions.
Conducting moderated usability sessions to validate the mental model.
After setting the foundational design direction, I transitioned the project to another designer, providing a full handover of concepts, flows, and design rationale to ensure continuity.
Context
Transformation Flows are part of SAP Datasphere’s Data Builder, enabling Data Modelers to load data from one or more sources, apply SQL-based or graphical transformations, and output the results into target tables. This feature fills a key gap between simple data loading and advanced modeling.
Problem Statement
Before this feature, Data Modelers lacked a straightforward way to transform data as it moved between sources and targets. Workarounds required external tools or overloading other flow types, creating inefficiencies and governance risks.
My Role
I initiated the UX design for Transformation Flows, focusing on the concept definition and early design exploration. My responsibilities included:
Researching user needs and defining initial user journeys.
Creating early prototypes in Figma and UI5 aligned with the Data Builder canvas.
Exploring multiple design directions and identifying dead ends.
Collaborating with Product Management and Engineering to scope feasible solutions.
Conducting moderated usability sessions to validate the mental model.
After setting the foundational design direction, I transitioned the project to another designer, providing a full handover of concepts, flows, and design rationale to ensure continuity.
Context
Transformation Flows are part of SAP Datasphere’s Data Builder, enabling Data Modelers to load data from one or more sources, apply SQL-based or graphical transformations, and output the results into target tables. This feature fills a key gap between simple data loading and advanced modeling.
Problem Statement
Before this feature, Data Modelers lacked a straightforward way to transform data as it moved between sources and targets. Workarounds required external tools or overloading other flow types, creating inefficiencies and governance risks.
My Role
I initiated the UX design for Transformation Flows, focusing on the concept definition and early design exploration. My responsibilities included:
Researching user needs and defining initial user journeys.
Creating early prototypes in Figma and UI5 aligned with the Data Builder canvas.
Exploring multiple design directions and identifying dead ends.
Collaborating with Product Management and Engineering to scope feasible solutions.
Conducting moderated usability sessions to validate the mental model.
After setting the foundational design direction, I transitioned the project to another designer, providing a full handover of concepts, flows, and design rationale to ensure continuity.
Design Solution
Design Solution
Design Solution
Design Process
Exploration: Compared extending Data Flows vs. introducing a new flow type.
Pivot: Determined that embedding transformations into existing flows created confusion, so we defined Transformation Flows as a distinct category.
Finalized Concept (handover point): Established consistency with other Data Builder flows while introducing transformation-specific capabilities.
Challenges & Resolutions
Challenge: Avoiding overlap with Data Flows and Replication Flows.
Resolution: Scoped Transformation Flows around modeling and delta logic, keeping boundaries clear.
Impact
Though I handed over before the final implementation, the foundation I designed enabled the team to deliver a feature that:
Covers the most common data modeling requirements.
Allows SQL-based transformations directly within Datasphere.
Supports delta tables and integrates with existing flow canvases.
Know more:
SAP Datasphere - https://www.sap.com/products/data-cloud/datasphere.html
Design Process
Exploration: Compared extending Data Flows vs. introducing a new flow type.
Pivot: Determined that embedding transformations into existing flows created confusion, so we defined Transformation Flows as a distinct category.
Finalized Concept (handover point): Established consistency with other Data Builder flows while introducing transformation-specific capabilities.
Challenges & Resolutions
Challenge: Avoiding overlap with Data Flows and Replication Flows.
Resolution: Scoped Transformation Flows around modeling and delta logic, keeping boundaries clear.
Impact
Though I handed over before the final implementation, the foundation I designed enabled the team to deliver a feature that:
Covers the most common data modeling requirements.
Allows SQL-based transformations directly within Datasphere.
Supports delta tables and integrates with existing flow canvases.
Know more:
SAP Datasphere - https://www.sap.com/products/data-cloud/datasphere.html
Design Process
Exploration: Compared extending Data Flows vs. introducing a new flow type.
Pivot: Determined that embedding transformations into existing flows created confusion, so we defined Transformation Flows as a distinct category.
Finalized Concept (handover point): Established consistency with other Data Builder flows while introducing transformation-specific capabilities.
Challenges & Resolutions
Challenge: Avoiding overlap with Data Flows and Replication Flows.
Resolution: Scoped Transformation Flows around modeling and delta logic, keeping boundaries clear.
Impact
Though I handed over before the final implementation, the foundation I designed enabled the team to deliver a feature that:
Covers the most common data modeling requirements.
Allows SQL-based transformations directly within Datasphere.
Supports delta tables and integrates with existing flow canvases.
Know more:
SAP Datasphere - https://www.sap.com/products/data-cloud/datasphere.html
