Data analyst (entry level, certificate route) — 3 out of 5 stars

Job 9 of 100 · Tech and IT support

Start here, step by step

  1. Learn the words first: a query is a question you ask a database in SQL, the language databases answer. A dashboard is a live summary screen — the one part of this field that leans visual, and the part you will lean away from.
  2. Get fluent in a spreadsheet first: sorting, filtering, pivot-style summaries, and formulas, all by keyboard. This is the daily tool and the cheapest skill to prove.
  3. Work through the Google Data Analytics certificate, doing every hands-on exercise with your screen reader rather than watching someone else do it.
  4. Build two portfolio projects from free public data sets — clean one messy spreadsheet and answer three real questions with SQL — and write up what you found in plain sentences.
  5. Apply toward the data-cleaning and analytics-engineering end of postings, where the work is text and tables, rather than dashboard-design roles built around visual chart styling.
  6. In interviews, demo your portfolio live with your screen reader. Showing the workflow answers the accessibility question better than any promise.

How AI can help

Use AI to explain unfamiliar SQL, suggest formulas, and draft the plain-language summary of findings you already reached. AI cannot know which number in a messy export is lying — spotting the bad data is the analyst's actual job.

Rating: 3 out of 5 stars

Strong pay and pure-text core skills, held at three stars because some business-intelligence dashboards are rough with screen readers and some postings quietly expect visual chart design — aim at the data-cleaning end and the fit is much better.

Pros and cons — the honest version

Pros

Cons