Deutsche Telekom

Product Design

Chief Data Office Portal

Overview

Deutsche Telekom’s Innovation Laboratories aimed to transform how data was shared and utilized across its national companies. The goal was to create a centralized hub for the Chief Data Office, enabling seamless information exchange, functionality sharing, and fostering a data-driven community.

We designed a comprehensive enterprise portal that enables data scientists and business leaders to:

Seamlessly access and share datasets across national companies.
Gain clarity on data quality, completion status, and relevance.
Collaborate on data science projects with improved efficiency.
Provide business managers with a high-level view of data-driven initiatives and revenue opportunities.

Key Contributions:

UX/UI Design for Enterprise SaaS – Created a streamlined and intuitive interface for technical and business users.
User Research & Testing – Conducted in-depth research to understand how data scientists interact with datasets.
Data Visualization & Analytics Integration – Designed dashboards that provide clear insights into project progress.
Collaboration & Knowledge Sharing – Developed features that foster teamwork and cross-department communication.

We designed a comprehensive enterprise portal that enables data scientists and business leaders to:

Seamlessly access and share datasets across national companies.
Gain clarity on data quality, completion status, and relevance.
Collaborate on data science projects with improved efficiency.
Provide business managers with a high-level view of data-driven initiatives and revenue opportunities.

Key Contributions:

UX/UI Design for Enterprise SaaS – Created a streamlined and intuitive interface for technical and business users.
User Research & Testing – Conducted in-depth research to understand how data scientists interact with datasets.
Data Visualization & Analytics Integration – Designed dashboards that provide clear insights into project progress.
Collaboration & Knowledge Sharing – Developed features that foster teamwork and cross-department communication.

We designed a comprehensive enterprise portal that enables data scientists and business leaders to:

Seamlessly access and share datasets across national companies.
Gain clarity on data quality, completion status, and relevance.
Collaborate on data science projects with improved efficiency.
Provide business managers with a high-level view of data-driven initiatives and revenue opportunities.

Key Contributions:

UX/UI Design for Enterprise SaaS – Created a streamlined and intuitive interface for technical and business users.
User Research & Testing – Conducted in-depth research to understand how data scientists interact with datasets.
Data Visualization & Analytics Integration – Designed dashboards that provide clear insights into project progress.
Collaboration & Knowledge Sharing – Developed features that foster teamwork and cross-department communication.

We designed a comprehensive enterprise portal that enables data scientists and business leaders to:

Seamlessly access and share datasets across national companies.
Gain clarity on data quality, completion status, and relevance.
Collaborate on data science projects with improved efficiency.
Provide business managers with a high-level view of data-driven initiatives and revenue opportunities.

Key Contributions:

UX/UI Design for Enterprise SaaS – Created a streamlined and intuitive interface for technical and business users.
User Research & Testing – Conducted in-depth research to understand how data scientists interact with datasets.
Data Visualization & Analytics Integration – Designed dashboards that provide clear insights into project progress.
Collaboration & Knowledge Sharing – Developed features that foster teamwork and cross-department communication.

Client

Deutsche Telekom AG

Industry

Telecommunications

Website

www.telekom.com

Markus Schmidt, Head of Data Strategy, Innovate Telekom

Tanya’s expertise in UX research and design transformed how Deutsche Telekom’s data teams collaborate. Her solution streamlined data sharing and empowered both scientists and business managers with valuable insights.

Problem Statement

Deutsche Telekom’s data science teams faced significant challenges in finding, sharing, and validating datasets across national branches.

There was no standardized system for storing and categorizing datasets.
Data quality and completeness were unclear, leading to delays in decision-making.
Communication with local IT departments was inefficient, making it difficult to verify data reliability.

Without a centralized platform, data scientists were losing valuable time navigating complexity instead of focusing on research and innovation.

Deutsche Telekom’s data science teams faced significant challenges in finding, sharing, and validating datasets across national branches.

There was no standardized system for storing and categorizing datasets.
Data quality and completeness were unclear, leading to delays in decision-making.
Communication with local IT departments was inefficient, making it difficult to verify data reliability.

Without a centralized platform, data scientists were losing valuable time navigating complexity instead of focusing on research and innovation.

Deutsche Telekom’s data science teams faced significant challenges in finding, sharing, and validating datasets across national branches.

There was no standardized system for storing and categorizing datasets.
Data quality and completeness were unclear, leading to delays in decision-making.
Communication with local IT departments was inefficient, making it difficult to verify data reliability.

Without a centralized platform, data scientists were losing valuable time navigating complexity instead of focusing on research and innovation.

Deutsche Telekom’s data science teams faced significant challenges in finding, sharing, and validating datasets across national branches.

There was no standardized system for storing and categorizing datasets.
Data quality and completeness were unclear, leading to delays in decision-making.
Communication with local IT departments was inefficient, making it difficult to verify data reliability.

Without a centralized platform, data scientists were losing valuable time navigating complexity instead of focusing on research and innovation.

Process & Methodology

We adopted a research-driven and iterative design process to develop an enterprise-grade solution:

Discovery & Research

Conducted stakeholder interviews with data scientists, business managers, and IT teams.
Mapped out user workflows and pain points to define key requirements.
Benchmarked existing solutions to identify industry best practices.

Experience Design & Prototyping

Created wireframes and prototypes to visualize key workflows.
Designed intuitive dashboards and data visualization components for both data teams and business leaders.
Focused on usability and reducing cognitive load for technical users.

User Testing & Iteration

Ran usability testing sessions to refine the platform’s functionality.
Implemented feedback to optimize the data-sharing and collaboration experience.
Ensured seamless integration with Deutsche Telekom’s existing data infrastructure.

We adopted a research-driven and iterative design process to develop an enterprise-grade solution:

Discovery & Research

Conducted stakeholder interviews with data scientists, business managers, and IT teams.
Mapped out user workflows and pain points to define key requirements.
Benchmarked existing solutions to identify industry best practices.

Experience Design & Prototyping

Created wireframes and prototypes to visualize key workflows.
Designed intuitive dashboards and data visualization components for both data teams and business leaders.
Focused on usability and reducing cognitive load for technical users.

User Testing & Iteration

Ran usability testing sessions to refine the platform’s functionality.
Implemented feedback to optimize the data-sharing and collaboration experience.
Ensured seamless integration with Deutsche Telekom’s existing data infrastructure.

We adopted a research-driven and iterative design process to develop an enterprise-grade solution:

Discovery & Research

Conducted stakeholder interviews with data scientists, business managers, and IT teams.
Mapped out user workflows and pain points to define key requirements.
Benchmarked existing solutions to identify industry best practices.

Experience Design & Prototyping

Created wireframes and prototypes to visualize key workflows.
Designed intuitive dashboards and data visualization components for both data teams and business leaders.
Focused on usability and reducing cognitive load for technical users.

User Testing & Iteration

Ran usability testing sessions to refine the platform’s functionality.
Implemented feedback to optimize the data-sharing and collaboration experience.
Ensured seamless integration with Deutsche Telekom’s existing data infrastructure.

We adopted a research-driven and iterative design process to develop an enterprise-grade solution:

Discovery & Research

Conducted stakeholder interviews with data scientists, business managers, and IT teams.
Mapped out user workflows and pain points to define key requirements.
Benchmarked existing solutions to identify industry best practices.

Experience Design & Prototyping

Created wireframes and prototypes to visualize key workflows.
Designed intuitive dashboards and data visualization components for both data teams and business leaders.
Focused on usability and reducing cognitive load for technical users.

User Testing & Iteration

Ran usability testing sessions to refine the platform’s functionality.
Implemented feedback to optimize the data-sharing and collaboration experience.
Ensured seamless integration with Deutsche Telekom’s existing data infrastructure.

Results

Our solution transformed data management and collaboration within Deutsche Telekom:

✅ Faster Data Discovery – Scientists can now locate and access datasets without friction.

✅ Improved Collaboration – Teams across different national companies share knowledge effortlessly.

✅ Streamlined Business Insights – Business managers gain real-time visibility into data-driven initiatives and potential revenue impacts.

✅ Scalable & Future-Proof – The hub was designed to evolve with Deutsche Telekom’s growing data needs.

With a centralized, user-friendly data portal, Deutsche Telekom’s teams can now focus on innovation rather than administration, accelerating the development of cutting-edge data science solutions.