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Become a Data Analyst / BI Analyst
Turn raw business data into clear dashboards and actionable insights that drive real decisions.
CREATED BY
A
Asha M. [PLACEHOLDER] ★ 5.0
Tools & Automation Engineer at BigFruit Inc. | 9+ years of experience
About this Path
Perfect for graduates and career-switchers with zero analytics experience who want to land their first data or BI role. You will learn SQL from scratch, build Tableau and Power BI dashboards used in interviews, and understand how analysts communicate findings to stakeholders. Graduates leave with a portfolio of three real business case studies.
Path Overview
Beginner LevelCertificate of CompletionAbout 32 hours to completeEnglish language12+ curated videosLearn online at your own pace5 modules with resourcesGamified & interactive
Path Curriculum
SELECT, filter, sort, and aggregate
Query real sales and user tables; master GROUP BY, HAVING, and COUNT DISTINCT.
JOINs and subqueries
Combine tables from multiple sources to answer multi-step business questions confidently.
Window functions
Compute running totals, rank, and lag/lead for cohort and retention analysis.
CTEs and query optimization
Write readable, modular SQL and use EXPLAIN to spot slow table scans early.
Excel Power Query essentials
Unpivot, merge queries, and build refresh-able models without writing a line of code.
Python pandas fundamentals
Load CSVs, handle nulls, rename columns, and filter rows for analysis-ready DataFrames.
Identifying and fixing data quality issues
Detect duplicates, outliers, and schema mismatches before they corrupt your analysis.
Building reusable cleaning pipelines
Write pandas functions that clean new monthly data dumps automatically in one command.
Chart selection principles
Pick the right chart for comparisons, distributions, trends, and part-to-whole relationships.
Tableau Desktop for beginners
Connect to data, build calculated fields, and publish an interactive dashboard to Tableau Public.
Power BI end-to-end
Model data with Power Query, write basic DAX measures, and design a report with slicers.
Dashboard design best practices
Apply layout, color, and typography rules that make executives read your charts in under ten seconds.
KPI frameworks and metric trees
Decompose business goals into measurable metrics using the MECE and North Star frameworks.
Descriptive vs. diagnostic analytics
Know when to explain what happened versus why it happened, and present each clearly.
A/B test interpretation for analysts
Read experiment results, spot Simpson's paradox, and give a clear ship-or-not recommendation.
Storytelling with data
Structure an analysis as a narrative: situation, complication, resolution, and next action.
E-commerce funnel analysis project
Identify drop-off stages, quantify revenue impact, and present recommendations in Tableau.
SaaS churn and MRR dashboard
Build a Power BI report tracking churn rate, MRR growth, and cohort retention curves.
HR attrition analytics case study
Use SQL and pandas to surface the top three drivers of employee attrition in a sample dataset.
Data analyst interview question bank
Practice 30 real SQL interview questions and ten business case prompts with model answers.
What you'll learn
- ✓Write intermediate SQL queries including JOINs, window functions, CTEs, and aggregations against real datasets.
- ✓Build interactive Tableau and Power BI dashboards with calculated fields, filters, and drill-through actions.
- ✓Clean and transform messy data using Python pandas and Excel Power Query for analysis-ready tables.
- ✓Apply descriptive statistics and A/B test interpretation to support data-driven business recommendations.
- ✓Present findings to non-technical stakeholders using structured storytelling and chart selection best practices.
- ✓Complete three end-to-end analyst portfolio projects covering e-commerce, SaaS metrics, and HR analytics.