Become a Job-Ready Data Analyst in 12–16 Weeks

The Data Analytics Course at Future X Academy is designed to transform beginners into skilled data analysts who can work confidently with real-world datasets, tools, and business problems.
You’ll learn Excel, SQL, Power BI, Python, statistics, dashboards, and reporting — everything required to crack interviews and deliver insights that drive business decisions.

Course Objectives

By the end of this course, you will be able to:

  • Clean, organize, manipulate, and analyze raw data
  • Build dashboards and reports used in real companies
  • Write SQL queries to extract data from databases
  • Use Python libraries for advanced data analysis
  • Present insights using visual storytelling
  • Solve business case studies like an analyst
  • Apply for roles such as Data Analyst, Business Analyst, Reporting Analyst, and MIS Executive

Tools You Will Learn

Matplotlib
Pandas & NumPy1
power-bi-icon1
power-query1
advanced-excel1
Jupyter Notebook1
python1
sql-database-logo1

100% practical & job-oriented training

Real projects + capstone project

Industry-expert trainers

Why Choose Future X Academy?

Placement assistance

Interview preparation & resume building

Affordable fees with EMI options

Complete Course Curriculum

Module 1

Introduction to Data Analytics

  • What is Data Analytics?
  •  Types of Analytics: Descriptive, Diagnostic, Predictive, Prescriptive
  •  Life cycle of Data Analytics
  • Understanding data types & data sources
  • How companies use data for decision-making
  • Introduction to real datasets
Module 2

Advanced Excel for Data Analytics

Excel Skills Covered:
  • Data cleaning & formatting
  • Lookup functions: VLOOKUP, HLOOKUP, XLOOKUP
  • Logical functions: IF, AND, OR
  • Pivot tables & pivot charts
  • Text functions
  • Date & time functions
  • Conditional formatting
  • Data validation
  • What-If Analysis (Goal Seek, Scenario Manager)
  • Power Query basics for automation
Outcome: Perform complete data analysis using Excel like a corporate analyst.

Module 3

SQL for Data Extraction & Database Management

Concepts Covered:
  • Introduction to databases
  • SQL basics: SELECT, WHERE, ORDER BY, GROUP BY
  • Joins: INNER, LEFT, RIGHT, FULL
  • Subqueries
  • Window functions
  • CTE (Common Table Expressions)
  • Aggregations
  • Database design
  • Importing and exporting data
Outcome: Write SQL queries to extract and manipulate data from large databases—exactly what companies expect.
Module 4

Powe BI for Data Visualization

Topics Included:
  • Power BI interface & workspace
  • Connecting to datasets
  • Data modeling
  • Data cleaning with Power Query
  • Measures & Calculated Columns (DAX)
  • Creating dashboards
  • Charts: Bar, Line, Pie, Waterfall, Donut, Maps
  •  Publishing dashboards
  • Sharing reports in real environment
Outcome: Create professional dashboards and present insights to stakeholders confidently.

Module 5

Python for Data Analysis

Python Concepts:

  • Python basics & environment setup
  • Working with Jupyter Notebook
  • Data types & operators
  • Loops & functions
  • Importing libraries

Libraries Covered:

  • Pandas (data cleaning, merging, grouping, analysis)
  • NumPy (numerical operations)
  • Matplotlib & Seaborn (data visualization)

Outcome: Use Python to handle large datasets and generate advanced insights.

Module 6

Statistics & Business Insights

Statistics for Analytics:
  • Mean, Median, Mode
  • Standard deviation & variance
  • Probability basics
  • Correlation & covariance
  • Hypothesis testing
  • Regression analysis (simple & multiple)
Business Interpretation Skills:
  • Identifying patterns
  • Finding root causes
  • Recommending solutions
  • Storytelling with data
Outcome: Analyze data not just technically—but strategically for business decisions.

Module 7

Dashboard Building & Reporting

    • Combining Excel, SQL, Power BI & Python outputs
    • Visual storytelling techniques
    • Monthly & weekly business reporting
    • Creating business dashboards:
      • Sales dashboard
      • Marketing dashboard
      • HR dashboard
      • Financial dashboard
    • KPI identification
    • Presenting insights in interviews
Module 8

Case Studies & Real-World Projects

Hands-on projects include:
  • Sales trend analysis
  • Customer segmentation
  • Market basket analysis
  • Employee performance dashboard
  • Inventory demand forecasting
  • Social media analytics
Final Capstone Project: Build a complete business analytics dashboard using Excel + SQL + Power BI + Python and present insights like an industry analyst.

Career Opportunities After the Course

  • Data Analyst
  • Business Analyst
  • Reporting Analyst
  • MIS Analyst
  • Junior Data Scientist
  • Operations Analyst
  • Marketing / Sales Analyst
  • Freelancer in analytics

Certifications Provided