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The Data Analyst resume: every KPI, formula, and pattern

Data AnalystBusiness AnalystProduct AnalystAnalytics ConsultantSenior Data Analyst
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The 7 numbers that carry this resume

Every data analyst bullet gets stronger with one of these. The benchmark tells you what's worth claiming; the question helps you dig your real number out.

Decision influencedthe strongest analyst metric is the business outcome your analysis triggered

Name one decision that changed because of your analysis. What did it save or earn?

Revenue / cost impactany ₹/$ figure beats a percentage without a base

What was the money attached — savings found, revenue unlocked, spend reallocated?

Dashboard adoptionweekly active viewers or teams using it; adoption > existence

Who uses your dashboards, how often, and what meeting or process runs on them?

Time savedhours/week × people, from automation or self-serve

What manual reporting did you kill? How many hours a week, for how many people?

Experiment velocity/winsnumber of tests run and the win that shipped

How many experiments did you design or read out? Which one changed the product?

Query/pipeline performanceruntime cuts or refresh reliability

Did you make a slow report fast or a flaky pipeline reliable? From what to what?

Data scalerows/events/sources give context to everything above

How large were the datasets — rows, events per day, number of sources joined?

Bullet formulas

Structure first, wording second. Fill the brackets with your own numbers.

  1. Strong verb + analysis or artifact + tool + the decision/outcome it drove, with the number.
  2. Weak: "Created dashboards in Tableau." Strong: "Built the retention dashboard (Tableau + BigQuery) that surfaced a 23% drop-off at onboarding step 3; the redesign it triggered lifted D30 retention 4 points."
  3. No money numbers? Use adoption, time saved, or scale: "used weekly by 40 sellers", "killed 6 hrs/week of manual reporting", "across 200M events/day".

Verbs that read like ownership

analysis
Analyzed · Modeled · Segmented · Quantified · Diagnosed · Uncovered
influence
Informed · Persuaded · Recommended · Presented · Translated
building
Built · Automated · Pipelined · Productionized · Instrumented
experimentation
Designed · Tested · Validated · Measured · Read out
quality
Reconciled · Audited · Standardized · Documented · Cleaned
leadership
Owned · Drove · Partnered · Mentored · Established

Weak phrase → stronger pattern

created dashboardsBuilt the [domain] dashboard used weekly by [N] [roles] to run [process]

A dashboard nobody opens is a chart. Adoption is the metric of a dashboard.

analyzed dataAnalyzed [specific data] and found [finding], which drove [decision/outcome]

Analysis is the verb of the job title — the finding and the decision are the achievement.

worked with stakeholdersPartnered with [team] to [decision]; recommendation adopted, delivering [outcome]

Name the stakeholder, the recommendation, and whether it was acted on.

prepared regular reportsAutomated [cadence] reporting ([tool]), saving [N] hrs/week — then killed the report by making it self-serve

Recurring manual reporting is a cost center; automating or eliminating it is the win.

used SQL/Python[Verb] [analysis/artifact] in [tool] — [outcome]

Tools belong inside an achievement, not as one.

provided insightsIdentified [specific finding]; [what changed because of it]

"Insights" is filler until you name one and what it changed.

Keywords screens look for

SQLdashboardsPythonA/B testingETLstakeholderKPIcohort analysisforecastingdata qualityExcelreporting automationdata modeling

Use the ones that are true for you — keyword stuffing reads as noise to a human on the other side. The studio tracks your coverage live.

Before you send it

  • Every bullet ends in a number: money, hours saved, adoption, accuracy, or scale
  • One line that proves SQL depth — window functions, multi-source joins, or the event volume you queried
  • Dashboards described by who uses them and for what, never by how many you made
  • A named experiment win with the metric it moved
  • Metric definitions/data-quality work mentioned once — it signals seniority and trust
  • Portfolio link if early-career: a public analysis with real data beats certifications
  • Tools list matched to the JD's stack synonyms (Power BI vs Tableau, BigQuery vs Snowflake)

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