Data Literacy & Self-Service Analytics Adoption Assessment

Welcome to the Data Literacy & Self-Service Analytics Survey. This survey is designed to understand how you find, use, and analyze data in your day-to-day work. Your responses will help us identify gaps in tools, training, and support so we can better enable a data-driven culture. • Participation is voluntary and you may stop at any time. • All responses are anonymous and will be reported only in aggregate. • There are no right or wrong answers — we are interested in your honest experience. • Estimated time: 6–8 minutes. Please click Next to begin.

How would you rate your overall proficiency with data analysis and data tools?

In a typical week, approximately how much time do you spend finding, preparing, or cleaning data before you can use it?

• Less than 15 minutes
• 15–30 minutes
• 31–60 minutes
• 1–2 hours
• 2–4 hours
• More than 4 hours
• I don't do this type of work

How would you rate your current ability to create charts or visualizations from raw data?

Please rank the following barriers by how much they limit your use of data. Place the biggest barrier at the top.

1. Limited tool access or permissions
2. Unclear metric definitions
3. Tool complexity or steep learning curve
4. Data quality or freshness issues
5. Not enough time
6. Not sure where to start
7. Worried about making a mistake

How confident are you in your ability to use self-service analytics tools to answer work-related questions?

Please rank the following support options by how helpful they would be for improving your data skills and workflows. Place the most helpful at the top.

1. Live training or workshops
2. Office hours with the data team
3. How-to guides and documentation
4. Templates or prebuilt dashboards
5. Improved data catalog or search
6. Faster or more reliable data refreshes
7. Streamlined access or permissions

Based on your responses in this survey, please share any additional thoughts about your experience with data tools, data skills, or self-service analytics at our organization. (Optional)

Which best describes your primary role or function?

• Engineering
• Product Management
• Design or UX
• Marketing
• Sales
• Customer Success or Support
• Operations
• Finance
• HR or People
• IT or Security
• Other (please specify)

Thank you for completing this survey! Your responses are anonymous and will be used in aggregate to improve data tools, training, and support across the organization. If you have urgent data needs, please reach out to your data team directly.

In a typical work week, how often do you analyze or use data as part of your role?

• Several times a day
• About once per day
• A few times per week
• About once per week
• Less than once per week
• I do not regularly use data in my role

Which of the following tools have you used in the last 30 days to explore or report on data? Select all that apply.

• Spreadsheets (Excel, Google Sheets)
• BI dashboards (Tableau, Power BI, Looker)
• Product analytics (Amplitude, Mixpanel)
• SQL tools (e.g., Snowflake/BigQuery clients)
• Notebooks (Jupyter, RStudio)
• Data catalog or lineage tool
• CRM or marketing analytics
• Visualization builders (Looker Studio, Data Studio)
• Other tool (please specify)

How would you rate your current ability to write or modify a data query (e.g., SQL)?

How clear are the data governance and usage guidelines that apply to your role?

How much do you trust the accuracy of the data you typically use in your work?

We'd like to learn more about your day-to-day experience with data. Please describe a recent situation where you needed to find or analyze data to make a decision — what went well and what was frustrating?

How long have you been at the company?

• Less than 6 months
• 6–12 months
• 1–2 years
• 3–5 years
• More than 5 years

How easy is it to find the right dataset or dashboard when you need it?

How would you rate your current ability to interpret a dashboard or report and draw actionable conclusions?

Where are you primarily located?

• Americas
• EMEA
• APAC
• Multiple regions
• Prefer not to say

How easy is it to find clear, agreed-upon definitions for the key metrics you use?

Are you a people manager?

• Yes
• No
• Prefer not to say