Data Analyst

Standardize nulls, dates, and text values using PostgreSQL functions.

Write validation queries that detect duplicate keys and invalid field values.

Deduplicate records deterministically with ROW_NUMBER.

Calculate conversion rates across the stages of a business funnel.

Build a cohort retention table from event-level data.

Calculate growth rates and segment contributions to explain a change in a headline metric.

Use EXPLAIN to identify a likely performance bottleneck in an analytical query.

Reconcile query outputs against control totals before reporting results.

Distinguish sampling variation from meaningful change in a business metric.

Construct and interpret a confidence interval for a mean or proportion.

Formulate null and alternative hypotheses for a business question.

Interpret a p-value without confusing statistical significance with business importance.

Select an appropriate test for comparisons of means, proportions, or categorical variables.

Evaluate an A/B test using uncertainty, effect size, and practical significance.

Identify common sources of selection bias, confounding, and misleading correlation.

Interpret the coefficients and core diagnostics of a linear regression model.

Aggregate and reshape analytical datasets with pandas groupby and pivot operations.

Merge pandas DataFrames while validating join cardinality and row-count changes.

Create analysis-ready features with vectorized pandas operations.

Profile distributions and segment-level patterns in an exploratory analysis.

Identify outliers and justify whether to retain, cap, transform, or exclude them.

Create presentation-ready comparison and time-series charts with Matplotlib and Seaborn.

Run and interpret a hypothesis test in Python.

Structure a reproducible notebook that separates preparation, analysis, findings, and limitations.

Choose correctly between a Power BI calculated column and a DAX measure.

Create explicit DAX measures for totals, ratios, and distinct counts.

Predict how row context and filter context affect a DAX expression.

Use CALCULATE with filter modifiers to produce context-sensitive metrics.

Use iterator functions such as SUMX and AVERAGEX for row-wise business logic.

Create a valid date table and apply DAX time-intelligence functions.

Build actual-versus-target and period-over-period variance measures.

Validate DAX results at total, segment, and filtered levels.

Translate an ambiguous stakeholder request into a decision-focused analytical question.

Define a KPI by specifying its formula, grain, time window, and edge cases.

Build a driver tree to investigate the root causes of a metric change.

Select a chart type that matches a comparison, trend, distribution, relationship, or composition question.

Arrange a Power BI dashboard using visual hierarchy and a clear reading path.

Configure filters, tooltips, and drill-through interactions without obscuring the main message.

Write takeaway titles and annotations that state the meaning of a visualization.

Present a recommendation while distinguishing evidence, assumptions, limitations, and next steps.

Evaluate existing portfolio projects against a role-relevance and evidence-quality rubric.

Rewrite a project brief around a business decision, target audience, and measurable success criteria.

Organize a project repository so that its data, SQL, notebooks, dashboard assets, and documentation are reproducible.

Add a concise data dictionary and documented quality checks to a portfolio project.

Align metric definitions and reported values across SQL, Python, and Power BI outputs.

Write a portfolio README that explains the problem, method, findings, impact, and limitations.

Deliver a three-minute walkthrough of a project using a problem-action-insight-recommendation structure.

Extract the required skills, business responsibilities, and screening keywords from an analyst job description.

Map each important job requirement to specific evidence from work experience or portfolio projects.

Rewrite résumé bullets to quantify the scale, action, analytical method, and business result of MIS work.

Tailor an existing résumé and portfolio selection to a data analyst, BI analyst, or business data analyst vacancy.

Build a targeted application tracker with priorities, follow-up dates, and conversion metrics.

Solve a timed SQL interview problem and verify the result with edge cases.

Explain a Power BI data model and DAX measure clearly during a technical interview.

Answer a business analytics case by stating assumptions, selecting metrics, structuring the analysis, and recommending next steps.