Business intelligence
Data Analyst
Turning messy spreadsheets into decisions.
Typical pay
$60k-$120k
How you get in
Degree or self-taught SQL, Excel and BI tools
Outlook
Growing
Lots of openings
24/100Openings come up often relative to the size of this field, and the field is growing.
JobPOVs index, calculated from U.S. Bureau of Labor Statistics Employment Projections 2025-2035 for Data scientists. It measures how many openings arise each year relative to the size of the field — not how many people apply. BLS does not publish a saturation figure.
Analysts pull, clean and interpret data to answer business questions. Heavy on SQL and communication, lighter on math than people assume.
A day in the life
9:00a – 4:30p · 7 hours 30 min
- 9:00aCheck dashboards for anomalies
- 10:00aA stakeholder asks why signups dipped
- 11:00aWrite SQL, sanity-check the join
- 1:00pBuild the chart, write the takeaway
- 3:00pPresent findings, get three new questions
- 4:30pAutomate the report
How to get in
Degree plus SQL
Duration
4 years
Cost
$40,000-$150,000+
Credential
Bachelor's in anything quantitative
- Finish a degree with real statistics coursework — economics, math, business analytics
- Learn SQL properly, then Excel to a genuinely advanced level
- Build a portfolio analyzing public datasets end to end
- Apply to analyst roles or convert from an internship
Self-taught
Duration
3-9 months
Cost
$0-$3,000
Credential
None — your portfolio is the credential
- Learn SQL first — it is most of the job
- Add a BI tool (Tableau or Power BI) and enough Python to clean data
- Publish three analyses that answer a real question, not a tutorial
- Apply to junior analyst and reporting roles
Transfer from inside a company
Duration
1-2 years
Cost
$0
Credential
None — internal track record
- Work in operations, support, finance or marketing
- Become the person on your team who builds the reports
- Automate something visible enough that leadership notices
- Move into the open analyst role with domain knowledge others lack
What people love
- · Entry path into tech without deep coding
- · Visible impact on decisions
- · Remote friendly
What wears people down
- · Lots of ad-hoc requests
- · Data is always messier than promised
- · Can be undervalued