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Data Analytics Learning Hub

Turn messy data into decisions with Excel, SQL, Python and clear charts. 6 lessons, a Skill Check and guided projects — free.

Start with lesson 1 Take the Skill Check

Free tutorials
Practice tests
Projects

Lessons: 6
Reading time: 66 min
Skill Check: 12 questions
Projects: 2

About this skill

Every company now collects more data than it can read: sales, app clicks, support tickets, attendance, delivery times. A data analyst turns that pile into answers a manager can act on — which product is losing money, why customers leave, where the delays happen. This track teaches the full workflow the way analysts actually do it: asking a sharp question, cleaning the data, analysing it in Excel, SQL and pandas, and presenting what you found in a way that changes a decision.

Who it is for: Students from any branch (including commerce and non-CS engineering), freshers targeting data analyst, business analyst or MIS roles, and working professionals who live in Excel and want to go further.

After this track you will be able to

Turn a vague business problem into clear, answerable questions
Clean real-world data: missing values, duplicates and inconsistent formats
Analyse data with Excel pivot tables, lookups and formulas
Write SQL with GROUP BY, JOINs and window functions
Explore and summarise data with Python pandas
Choose the right chart and present insights that lead to action

Not sure where to start? Take the Data Analytics Skill Check 12 questions · about 10 minutes · instant level and a score for every topic Start

Learning path

Lessons, in order

Each lesson takes about 10 minutes and ends with a small task. 0 of 6 completed.

1
Thinking Like an AnalystThe analyst workflow, asking good questions and cleaning data you can trust.
- What Does a Data Analyst Do? The Analytics Workflow ExplainedA data analyst turns questions into answers a manager can act on. See a real day of work, the six-step analytics workflow, the four types of analysis and the skills recruiters actually test. Beginner 9 min
- Data Cleaning for Beginners: Fix Missing Values, Duplicates and Messy FormatsAnalysts say cleaning takes half their time — and they are not exaggerating. Learn the common problems in real data, how to fix each one in Excel and pandas, and a checklist you can use on every dataset. Beginner 10 min
2
Excel & SQL for AnalysisPivot tables, lookups, GROUP BY, JOINs and window functions on real business data.
- Excel for Data Analysis: Pivot Tables, XLOOKUP and Formulas That MatterYou do not need 400 Excel functions. You need about a dozen, used well. Learn tables, SUMIFS and COUNTIFS, XLOOKUP, pivot tables and conditional formatting with one realistic sales dataset. Beginner 11 min
- SQL for Data Analysis: GROUP BY, JOINs and Window FunctionsThe SQL that analyst interviews actually test: filtering, aggregation, HAVING, joins, CASE and window functions — all on one realistic e-commerce schema, with the mistakes that cost candidates the round. Intermediate 13 min
3
Python, Charts & Storytellingpandas for analysis, then charts and dashboards that make people act.
- Python pandas for Data Analysis: Load, Explore, Group and Mergepandas is Excel and SQL inside Python — with no row limit and every step saved as code. Learn the 15 operations that cover most analysis work, using a real-world style orders dataset. Intermediate 13 min
- Data Visualisation and Storytelling: Charts and Dashboards That Drive DecisionsA correct analysis that nobody understands changes nothing. Learn how to pick the right chart, design a clean dashboard in Power BI, Tableau or Looker Studio, and present findings so people act on them. Beginner 10 min

Build

Data Analytics projects

Finish the lessons, then prove the skill with a project you can show.

Data Analytics project Sales Performance Dashboard with Insights Clean a real sales dataset, analyse it with pivot tables or SQL, and build a one-page dashboard with KPIs, trends and three written recommendations. Data cleaningPivot tables / SQLDashboard design Beginner ~6 hours Data Analytics project Placement Data Analysis with SQL and pandas Analyse a placement dataset with SQL and Python to answer what really drives offers — CGPA, branch, internships or skills — and present it as a short report. SQL GROUP BY & window functionspandasCharts Intermediate ~5 hours

FAQ

Data Analytics: common questions

Can I become a data analyst without a computer science degree?

Yes — it is one of the most open roles in tech. Many analysts come from commerce, mechanical, electronics or science backgrounds. Recruiters care about three things: SQL, Excel and a portfolio that shows you can find a real insight. This track covers all three.

Excel, SQL or Python — which should I learn first?

Excel first (you can be useful in a week), SQL second (it is asked in almost every analyst interview), then Python pandas for bigger or messier data. The lessons follow exactly that order.

Do I need Power BI or Tableau?

You need one dashboard tool, and it does not matter much which. The principles in the visualisation lesson — right chart, clear titles, one message per chart — apply to Power BI, Tableau and Looker Studio. Pick the one used by companies you are applying to.

How much statistics do I need?

For a fresher analyst role: averages, median, percentages, distributions and the idea of correlation vs causation. We explain each one when it comes up, with examples, not formulas first.