PROJECT NAME

Data Analytics PaaS

SKILLS
Research + Design
STAKEHOLDERS
Intel Corporation

Challenge

I joined the Trusted Analytics Platform team to help enhance the user experience, which involved defining users, conducting usability testing, and improving UI design, user documentation, GitHub repositories, and product demonstrations.

User Interviews

I initiated interviews with subject matter experts within our team and recruited both internal and external data scientists to understand their work contexts, motivations, and expertise levels. These insights were consolidated into user definitions to guide our team.

Users were divided into 3 main segments: Experimentation, Solutions, and Innovation.
Defining the Users: Experimentation Segment
Defining the Users: Solutions Segment
Defining the Users: Innovation Segment

Scraping the Internet for Data

I worked with data scientists to analyze job postings alongside user interviews, aiming to identify popular data science tools and prioritize platform features, considering the possibility that experienced users prefer Command Line Interface (CLI) over Graphical User Interface (GUI) tools.

Methodology
Experience Level Determined by Data Scrape
Job Postings by Degree Type
Goal of Data Scrape
Experience Level and Occurrence of Tools
Terminology by Data Science Level
Languages by Data Science Level
Frameworks by Data Science Level
Tolls with UIs by Data Science Level
Tools with CLI by Data Science Level
Data Scrape Conclusions

User Testing

Using Data Scientist User Definitions derived from the interviews and data scraping, I conducted comprehensive user testing on the current interface, evaluating it through various tasks both qualitatively and quantitatively.

Results

The user definitions guided new feature development, and the data scrape led to prioritizing the expansion of Python-based features to reach a wider audience. Insights from usability test sessions led to significant improvements in the web UI.

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