Data Analysis
About Course
Data Analysis involves using tools like Excel, SQL Server, and Power BI to collect, process, and derive meaningful insights from data. The course focuses on scenario-based projects across three different domains to help students understand real-time business problems. With hands-on training and guided project work, learners will gain practical experience in tools and techniques used in modern data analytics. The course also emphasizes placement assistance, resume building, and interview skills development to ensure job readiness.
Course Objectives
Pre-requisties
The Course can be learned by any IT or non-IT individual having basic knowledge of:
- Basic computer Skills.
- Understanding of Data and Spreadsheet Concepts.
Duration
Duration: 3 Months
Class Timing: 90 Minutes per Day
Includes: Access to recorded sessions
What You'll Learn
- Gain strong foundational knowledge in Excel, SQL Server, and Power BI
Analyze datasets and interpret results to support decision-making
Apply tools to build dashboards, reports, and visuals
Work on scenario-based real-world projects from 3 different business domains
Prepare for jobs in analytics and data-driven roles
Who Can Join
Any student or graduate looking to build a career in data analysis or reporting
Any BE/BTech/BSc/BCA/MTech/MCA/M.Sc./M.Com/B.Com students
Working professionals seeking to upskill in data analytics
Anyone interested in transitioning into analytics or business intelligence roles
Training Curriculum
Spreadsheet navigation and data entry
Basic formulas and functions (SUM, AVERAGE, etc.)
Formatting and data validation
Sorting, filtering, and conditional formatting
Pivot tables and charts
Advanced formulas (IF, VLOOKUP, INDEX/MATCH)
What-If analysis and data tools
Excel dashboards
Introduction to relational databases
SQL syntax: SELECT, WHERE, JOIN, GROUP BY
Creating and managing tables
Writing queries for data retrieval and manipulation
Power BI overview and navigation
Connecting to datasets
Creating reports and visualizations
Designing interactive dashboards
Retail or Sales Analysis
Creating performance reports and KPIs
Generating dashboards based on real-world datasets
HR or Employee Data Analysis
Workforce trends and attrition analysis
Use of Power BI to visualize hiring insights
Finance or Budget Tracking
Visualizing revenue and expense trends
Data storytelling through dashboards
Creating a data-focused resume
Common interview questions in data analytics
Mock interview sessions
Tips for portfolio and project presentation