Understand CC query use cases

[meganhicks]

User Story:

As a VRO platform researcher, I need to gain a comprehensive understanding of the CC team's typical use cases for querying data so that we can better align our designs with their needs.

Acceptance Criteria:

• Reach out to Yurena and Tyler
• Review the research notes before meeting with CC so we do not ask them the same questions
• Develop questions we will ask to meet our goals:
  • Identify Common Queries: Document the common types of queries the CC team frequently makes when interacting with the data.
  • Understand Query Importance: Define why these queries are important to the CC team and how they impact their workflows.
  • Data Set Details: Provide details on the size of the datasets being queried, performance expectations, and the formats in which the data is stored.
  • Detail any challenges they experience
  • Detail what impact they think this data will have on them.
• Get VRO team input on additional questions
• Synthesize and present findings and insights to the VRO Team - Demo for Sprint Review

Resources

• Conditions Team Conversation Guide and Notes (10/31)
• VRO & Conditions Team Collaboration
• Streamlit MVP Mural

For reference:

• Data Visibility MVP 2024 Product Brief
• Data Visibility Research Interviews: CC Team Notes
• Data Visbility Mural board

[bianca-rivera]

Update:
I met with Yurena this morning to get an understanding of how defined the use cases and methodology for analysis of contentions are, and she shared the team has been creating a detailed brief and plan on the analysis they want to conduct.

These docs will be shared with the VRO team in the next partner team meeting on 10/31, so this ticket will rollover into Sprint 4.

[meganhicks]

Bianca please use the risks section in the Product Brief to ensure all of our questions are addressed to the best of our ability. https://docs.google.com/document/d/1QSF_6lIBnX1kQ41CbYJ4BLJJ_rLEIB9ZDwy-FSli_Do/edit?tab=t.0

[meganhicks]

Hey Tyler,
I met with Yurena today to discuss our progress on Streamlit and requested that we set aside time for the sprint starting 11/19/24 to collaborate more on the features and capabilities you want within Streamlit, specifically around the data. I know
@bianca Rivera Alvelo
is conducting research with you this sprint, and Yurena mentioned you have a team meeting tomorrow to discuss your needs.
Yurena emphasized how important it is to have a download feature and, last week, she mentioned the importance of being able to filter by claims on VA.gov. When I asked her today about prioritization, we agreed that filtering by VA.gov claims should come first thing VRO works on, as it would help minimize data sets.
As you work with the CC Team and Bianca on your use cases, please help us think through the following:
How would you like to filter the data? For example, are some topics like "contention classified" more important than others, and is all the metadata necessary?
What’s the average size of your data sets, and what are your performance expectations? How long do queries take currently?
Besides filtering by VA.gov, do you have any data cleansing or preprocessing needs?
What format is most valuable for downloads?
When it comes to visualizing the data, do you have a preferred method (e.g., heat map, bar chart)?
No need to respond directly—I know Bianca will capture this—but I wanted to share what I started asking Yurena today during our Product Manager meeting.