Distribution across 38 profiles.
Middle half of Business Intelligence Analysts score between 43% and 48%.
0%
50%
100%
p10 · 40%
53% · p90
Task breakdown by work type
On-screen work88%
Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.
In-person + screen12%
Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.
Computer + action0%
Computer input, real-world output — needs someone to act on it, not just software.
Fully in-person0%
No computer required. Furthest from automation — the strongest human advantage.
Typical tasks
3 synthetic profiles for a Business Intelligence Analyst, ordered by automation exposure.
Tab between them to see how task mix drives the score difference.
TaskTimeTypeExposure
Performing exploratory data analysis (EDA) to identify patterns, anomalies, or correlations in datasets, often using statistical tools or Python/R scripts.
deep expertise
25%DD
30%
Creating dashboards and visualizations (e.g., using Tableau, Power BI, or Looker) to present key metrics and trends to stakeholders in an easy-to-understand format.
deep expertisesocial element
20%DD
20%
Collaborating with business teams (e.g., marketing, finance, operations) to understand their data needs, translate requirements into technical specifications, and deliver actionable insights.
deep expertisesocial core
15%AD
14%
Developing and maintaining automated reports or data pipelines (e.g., using Python, R, or ETL tools) to ensure stakeholders receive timely updates without manual intervention.
deep expertise
15%DD
30%
Gathering and cleaning raw data from various databases, spreadsheets, or APIs to prepare it for analysis (e.g., removing duplicates, handling missing values, standardizing formats).
14%DD
59%
Writing SQL queries to extract specific datasets from relational databases or data warehouses for reporting or deeper analysis.
6%DD
61%
Documenting data sources, methodologies, and assumptions to ensure transparency and reproducibility of analyses for other team members or auditors.
0%DD
73%
Monitoring data quality and alerting teams to inconsistencies or errors in source systems that could impact reporting or decision-making.
0%DD
54%
TaskTimeTypeExposure
Writing SQL queries to extract specific datasets from relational databases or data warehouses for reporting or deeper analysis.
17%DD
63%
Documenting data sources, methodologies, and assumptions to ensure transparency and reproducibility of analyses for other team members or auditors.
16%DD
52%
Performing exploratory data analysis (EDA) to identify patterns, anomalies, or correlations in datasets, often using statistical tools or Python/R scripts.
deep expertise
14%DD
38%
Gathering and cleaning raw data from various databases, spreadsheets, or APIs to prepare it for analysis (e.g., removing duplicates, handling missing values, standardizing formats).
13%DD
62%
Collaborating with business teams (e.g., marketing, finance, operations) to understand their data needs, translate requirements into technical specifications, and deliver actionable insights.
deep expertisesocial core
13%AD
6%
Developing and maintaining automated reports or data pipelines (e.g., using Python, R, or ETL tools) to ensure stakeholders receive timely updates without manual intervention.
9%DD
58%
Monitoring data quality and alerting teams to inconsistencies or errors in source systems that could impact reporting or decision-making.
8%DD
50%
Creating dashboards and visualizations (e.g., using Tableau, Power BI, or Looker) to present key metrics and trends to stakeholders in an easy-to-understand format.
deep expertisesocial element
7%DD
32%
TaskTimeTypeExposure
Gathering and cleaning raw data from various databases, spreadsheets, or APIs to prepare it for analysis (e.g., removing duplicates, handling missing values, standardizing formats).
31%DD
71%
Performing exploratory data analysis (EDA) to identify patterns, anomalies, or correlations in datasets, often using statistical tools or Python/R scripts.
deep expertise
18%DD
39%
Writing SQL queries to extract specific datasets from relational databases or data warehouses for reporting or deeper analysis.
12%DD
56%
Developing and maintaining automated reports or data pipelines (e.g., using Python, R, or ETL tools) to ensure stakeholders receive timely updates without manual intervention.
12%DD
60%
Creating dashboards and visualizations (e.g., using Tableau, Power BI, or Looker) to present key metrics and trends to stakeholders in an easy-to-understand format.
deep expertisesocial element
9%DD
26%
Collaborating with business teams (e.g., marketing, finance, operations) to understand their data needs, translate requirements into technical specifications, and deliver actionable insights.
deep expertisesocial element
8%AD
12%
Monitoring data quality and alerting teams to inconsistencies or errors in source systems that could impact reporting or decision-making.
5%DD
46%
Documenting data sources, methodologies, and assumptions to ensure transparency and reproducibility of analyses for other team members or auditors.
0%DD
58%
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AI tools for this role
Tools relevant to the most automatable tasks in this profession.
