Data Analytics Course — Duration-wise Syllabus

2030 Outlook — Data Analytics

Career Risk (2030): Low–Medium

Low–Medium

career risk

Where it's headed

Demand remains strong because businesses need insights from data. AI will automate some reporting tasks, but analysts who understand business problems, build dashboards and tell stories with data will remain valuable.

Demand today

Consistently high demand for SQL, Excel, Power BI, Tableau, Python and statistics — the core toolkit behind every analytics team.

Our recommendation

Go beyond building reports. Focus on connecting data to business decisions — that's the part AI won't replace.

SQL Excel Power BI Tableau Python Statistics Data Storytelling

Duration-wise curriculum

10 Weeks syllabus, module by module.

Click a module to expand it. Every module ends with a hands-on exercise so the tool stack sticks, not just the theory.

Advanced formulas: XLOOKUP, INDEX-MATCH, array formulas
PivotTables and PivotCharts for fast analysis
Data cleaning techniques inside Excel
Building dashboard-style Excel reports

SELECT, JOINs, GROUP BY and aggregate functions
Window functions for ranking and running totals
Writing queries to answer real business questions
Query optimization basics for large tables

Descriptive statistics: mean, median, variance, distributions
Correlation vs causation
Hypothesis testing fundamentals
Applying statistics to real business datasets

Data modeling and relationships in Power BI
DAX formulas for calculated measures
Building interactive dashboards and reports
Publishing and sharing Power BI workspaces

Connecting data sources and building visualizations
Calculated fields and parameters
Dashboard design principles for clarity
Publishing to Tableau Public/Server

Python fundamentals for analysts
Data manipulation with Pandas
Visualization with Matplotlib/Seaborn
Exploratory data analysis (EDA) workflow

Structuring an analysis around a business question
Storytelling with data: framing, narrative, visuals
Capstone project: end-to-end analysis and dashboard
Portfolio review and mock interviews

Who should join

Freshers and career-switchers targeting analyst roles
Excel-heavy professionals who want to add SQL, BI tools and Python
Business/operations professionals who want to work with data directly
Anyone who wants to move from reporting to real decision-support

Prerequisites

Basic comfort with Excel and spreadsheets
No prior SQL, BI tool or programming experience required
Genuine interest in business problems, not just tools

Career outcomes

Roles this program prepares you for.

Analysts who pair tool skill with business judgment are the ones AI augments, not replaces.

ROLE 01

Data Analyst

Turn raw business data into reports and dashboards decision-makers actually use.

ROLE 02

BI Developer

Own Power BI/Tableau dashboard development for a team or department.

ROLE 03

Business/Product Analyst

Translate business questions into data-backed recommendations.

Data Analytics