Technology
Data Analyst
Based on 42 assessments · 4 from real users
38%
Moderate risk
Average realistic automation risk across all Data Analyst profiles in the dataset.
Score spread
Distribution across 42 profiles.
Middle half of Data Analysts score between 34% and 41%.
0%
50%
100%
Task breakdown by work type
Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.
Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.
Computer input, real-world output — needs someone to act on it, not just software.
No computer required. Furthest from automation — the strongest human advantage.
Typical tasks
3 synthetic profiles for a Data Analyst, ordered by automation exposure.
Tab between them to see how task mix drives the score difference.
Performing statistical analysis or predictive modeling (e.g., regression, clustering) to identify trends, patterns, or forecast future outcomes
deep expertise
25%
DD
40%
Creating visualizations (e.g., charts, dashboards) using tools like Tableau, Power BI, or Python libraries to present data insights to stakeholders
deep expertise
social element
20%
DD
28%
Writing reports or summaries explaining data findings, insights, and recommendations for business decisions in clear, non-technical language
deep expertise
social core
18%
DD
13%
Collecting and cleaning raw data from various sources (e.g., databases, spreadsheets, APIs) to ensure accuracy and consistency before analysis
17%
AD
24%
Collaborating with teams (e.g., marketing, operations) to understand their data needs and translate business questions into analytical tasks
deep expertise
social core
12%
AD
16%
Monitoring data quality and automating repetitive data workflows (e.g., ETL pipelines) to improve efficiency and reduce manual errors
deep expertise
5%
DD
31%
Writing SQL queries to extract specific datasets from relational databases for reporting or further analysis
1%
DD
63%
Performing statistical analysis or predictive modeling (e.g., regression, clustering) to identify trends, patterns, or forecast future outcomes
deep expertise
social element
29%
DD
29%
Writing reports or summaries explaining data findings, insights, and recommendations for business decisions in clear, non-technical language
deep expertise
social core
24%
DD
22%
Monitoring data quality and automating repetitive data workflows (e.g., ETL pipelines) to improve efficiency and reduce manual errors
14%
DD
63%
Writing SQL queries to extract specific datasets from relational databases for reporting or further analysis
14%
DD
58%
Collecting and cleaning raw data from various sources (e.g., databases, spreadsheets, APIs) to ensure accuracy and consistency before analysis
6%
AD
24%
Creating visualizations (e.g., charts, dashboards) using tools like Tableau, Power BI, or Python libraries to present data insights to stakeholders
5%
DD
51%
Collaborating with teams (e.g., marketing, operations) to understand their data needs and translate business questions into analytical tasks
deep expertise
social core
4%
AD
10%
Performing statistical analysis or predictive modeling (e.g., regression, clustering) to identify trends, patterns, or forecast future outcomes
31%
DD
53%
Collecting and cleaning raw data from various sources (e.g., databases, spreadsheets, APIs) to ensure accuracy and consistency before analysis
18%
AD
31%
Writing reports or summaries explaining data findings, insights, and recommendations for business decisions in clear, non-technical language
deep expertise
social core
16%
DD
18%
Writing SQL queries to extract specific datasets from relational databases for reporting or further analysis
13%
DD
95%
Creating visualizations (e.g., charts, dashboards) using tools like Tableau, Power BI, or Python libraries to present data insights to stakeholders
9%
DD
47%
Collaborating with teams (e.g., marketing, operations) to understand their data needs and translate business questions into analytical tasks
deep expertise
social core
8%
AD
12%
Monitoring data quality and automating repetitive data workflows (e.g., ETL pipelines) to improve efficiency and reduce manual errors
3%
DD
69%
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