Database Analyst

Database Analyst trains newcomers and these 20 real tasks outline the concrete coaching and checks you’ll perform. Tasks cover first-week priorities, simple demonstrations, and common rookie errors. Each one shows where we found it, and comes with an AI prompt you can copy and use straight away.

20evidenced tasks
20ready prompts
7tools of the trade
15-2041.00O*NET-SOC code
29,030hold this job (US, BLS 2025)
$105,650median pay/yr (US)
Open Database Analyst in the interactive atlas →

What it pays

Government survey numbers — not estimates, not ads.

Half of all Statisticians in the U.S. earn more than $105,650 a year — the middle 80% land between $64,000 and $174,050. About 29,030 people in the U.S. do this work. Figures are for the U.S. occupation group “Statisticians”. (U.S. Bureau of Labor Statistics survey, published 2025.) In India, Professionals earn about ₹38,298 a month on average — around ₹4.6 lakh a year (government PLFS survey via ILOSTAT, occupation-family figure).
$105,650typical pay / year
29,030people in this work
$174,050+top 10% earn
₹4.6 lakha year in India (family avg)
Think you get this job?Six quick questions on how it really works — with a hint and the reason behind every answer.
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The work, task by task

These are the real jobs-to-be-done, not a wish list. Each task shows where we found it, and the prompt underneath is written for that exact task.

Analysing4

Apply statistical methods to data

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Run exploratory analysis on last quarter’s transaction logs to estimate seasonality and variance: clean the…
Run exploratory analysis on last quarter’s transaction logs to estimate seasonality and variance: clean the raw tables, compute summary statistics by region and product, fit a baseline regression, and deliver a one-page memo with charts to the head of analytics by Friday.
The tools that do the workIBM SPSS StatisticsMicrosoft ExcelESCOjob descriptionsO*NETWikipedia

Analyze data to identify trends

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Analyze six months of sales data to identify emerging trends: join sales and customer tables, compute rolling…
Analyze six months of sales data to identify emerging trends: join sales and customer tables, compute rolling averages and growth rates, highlight three product categories with accelerating demand, and present the findings to commercial by Tuesday morning.
The tools that do the workApache Sparkjob descriptionsO*NETWikipedia

Produce statistical reports and visualizations

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Produce weekly statistical reports for product engagement: calculate cohort retention, median session length,…
Produce weekly statistical reports for product engagement: calculate cohort retention, median session length, and conversion funnels for May 2026, create three visualizations (retention curve, funnel chart, session density) and export a one-page PDF summary for the product manager by Thursday 3pm.
The tools that do the workMicrosoft Exceljob descriptionsO*NETWikipedia

Develop and apply statistical principles

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Design and run statistical tests to compare feature A and feature B on retention: define hypotheses, compute…
Design and run statistical tests to compare feature A and feature B on retention: define hypotheses, compute sample sizes, run A/B significance tests with confidence intervals, and produce a methods note and results table for the experimental review by Friday EOD.
The tools that do the workIBM SPSS Statisticsjob descriptionsO*NET
Learning2

Collect data

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Pull raw transaction and user event tables for Q2 2026, join on user_id, filter out test accounts and…
Pull raw transaction and user event tables for Q2 2026, join on user_id, filter out test accounts and negative amounts, then deliver a single cleaned CSV with data dictionary and row counts by source by Friday noon for the analytics team.
The tools that do the workApache SparkESCOjob descriptionsWikipedia

Collect and organize data for analysis

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Gather customer support logs, purchase records, and app telemetry for March–May 2026, standardise timestamps,…
Gather customer support logs, purchase records, and app telemetry for March–May 2026, standardise timestamps, dedupe by user_id and event_id, tag missing fields, and output a normalized dataset with source provenance for the data science team on Monday morning.
The tools that do the workMicrosoft Accessjob descriptionsO*NETWikipedia
The daily work14

Identify statistical patterns

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Run exploratory statistical scans on the customer_events table for the last two years, flag recurring weekly…
Run exploratory statistical scans on the customer_events table for the last two years, flag recurring weekly and monthly patterns, quantify effect sizes and confidence intervals for each pattern, and deliver a ranked list of actionable anomalies with SQL snippets and sample rows.
The tools that do the workApache SparkESCOsee the evidence ↗

Gather data

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Assemble transaction, customer profile, and device logs from the past 24 months, deduplicate and normalise…
Assemble transaction, customer profile, and device logs from the past 24 months, deduplicate and normalise keys, validate schema and completeness, and hand over a single cleaned table ready for analysis with row counts and data-quality issues documented.
The tools that do the workAmazon RedshiftESCOsee the evidence ↗

Assess reliability of source information

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Assess the reliability of the quarterly sales source by profiling its origin, timestamp patterns,…
Assess the reliability of the quarterly sales source by profiling its origin, timestamp patterns, missing-value rates, and any schema changes over the past two years, flagging records with conflicting IDs for manual review by Friday.
The tools that do the workIBM DB2job descriptionsO*NET

Evaluate and describe data utility

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Evaluate the utility of the customer dataset for churn modelling: report field completeness, predictive…
Evaluate the utility of the customer dataset for churn modelling: report field completeness, predictive signal per feature, correlation with churn, and recommended transformation or enrichment before handoff to analytics by Wednesday.
The tools that do the workMicrosoft Exceljob descriptionsWikipedia

Use software like R, Python, SAS, SQL

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Prepare the cleaned extract of order and customer tables, include sample code showing how to join, aggregate…
Prepare the cleaned extract of order and customer tables, include sample code showing how to join, aggregate and export the dataset for analysis in R or Python, and attach a validation checklist demonstrating row-level counts match the source.
The tools that do the workApache Sparkjob descriptionsWikipedia

Build models and perform hypothesis testing

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Build the sales forecasting model and run hypothesis tests on price sensitivity: specify assumptions, fit…
Build the sales forecasting model and run hypothesis tests on price sensitivity: specify assumptions, fit candidate models with diagnostics, report p-values and effect sizes, and recommend whether to accept the price elasticity hypothesis.
The tools that do the workIBM SPSS Statisticsjob descriptions

Liaise with management to define data needs

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Meet with Sarah in Product and Jonah in Finance, confirm the KPIs they need, draft a prioritized list of…
Meet with Sarah in Product and Jonah in Finance, confirm the KPIs they need, draft a prioritized list of tables and refresh cadence, then circulate the summary and ask for sign-off by next Tuesday.
The tools that do the workMicrosoft Officejob descriptions

Create charts

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Create a set of charts showing monthly revenue by region, customer cohort retention curves, and top SKU…
Create a set of charts showing monthly revenue by region, customer cohort retention curves, and top SKU contribution, export them as printable PNGs and attach a one-page captioned summary for the commercial review on Monday.
The tools that do the workMicrosoft ExcelESCO

Process data

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Cleanse the sales and transaction tables for January through June, deduplicate by invoice and customer ID,…
Cleanse the sales and transaction tables for January through June, deduplicate by invoice and customer ID, normalise date and currency fields, then produce a validated, exportable dataset ready for aggregations and joins by Friday noon.
The tools that do the workApache SparkESCOsee the evidence ↗

Think analytically

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Review the customer churn indicators, run correlation checks between tenure, support tickets and monthly…
Review the customer churn indicators, run correlation checks between tenure, support tickets and monthly spend, flag unexpected relationships and write a one-page interpretation of likely drivers for the product manager.
The tools that do the workIBM SPSS StatisticsESCOsee the evidence ↗

Perform data analysis

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Calculate weekly active user counts, cohort retention at 7, 30 and 90 days, and produce a table of spend per…
Calculate weekly active user counts, cohort retention at 7, 30 and 90 days, and produce a table of spend per active user by cohort with confidence intervals for the analytics team meeting Tuesday.
The tools that do the workMicrosoft ExcelESCOsee the evidence ↗

Apply statistical analysis techniques

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Run hypothesis tests comparing average order value across the three pricing tiers, adjust for unequal…
Run hypothesis tests comparing average order value across the three pricing tiers, adjust for unequal variances, report p-values, effect sizes and a plain-English conclusion for the pricing lead.
The tools that do the workIBM SPSS StatisticsESCOsee the evidence ↗

Apply scientific methods

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Design an A/B experiment to test the new checkout flow: specify randomisation unit, sample size for 80…
Design an A/B experiment to test the new checkout flow: specify randomisation unit, sample size for 80 percent power, primary metric, data collection plan and stopping rules, then save the protocol for review.
The tools that do the workApache SparkIBM SPSS StatisticsESCOsee the evidence ↗

Write work-related reports

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Draft the monthly data quality report: summarise missingness, trend of key metric drift, incidents closed,…
Draft the monthly data quality report: summarise missingness, trend of key metric drift, incidents closed, and three recommended fixes with estimated impact and owner, then circulate to ops and product.
The tools that do the workMicrosoft OfficeMicrosoft ExcelESCOsee the evidence ↗

Says who?

These are the pages we read to build this. Open any of them and check us.

The logs, files & records this job keeps

Shared with other careers — the same record means something different in each.

Related careers

Same family of work — each with its own tasks and prompts.

The LLOS Work Atlas is the world's largest evidenced task library — a map of human work, with a ready prompt behind every task. 1,774 careers · every task named by the sources that witnessed it — O*NET, ESCO, real job descriptions, Wikipedia — and the deepest tasks by several at once. And it is honest about limits: where AI cannot help, the map says so.

The rest of the map

Same library, five ways in.

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Built on public evidence: O*NET®, ESCO, Wikipedia, U.S. Bureau of Labor Statistics, ILOSTAT. All sources & licenses