This comprehensive Data Analyst training program is designed to equip students with practical skills in data analysis, data visualization, and business intelligence. The course covers Microsoft Excel, SQL, and Power BI, focusing on real-world datasets and industry projects to prepare students for data analyst roles.

Duration: 4 Weeks

Level: Beginner to Intermediate

Tools Covered: Excel, SQL, Power BI

Outcome: Hands-on experience with real-world analytics projects and dashboards

What Students Will Learn

Week 1: Excel for Data Analysis

In the first week, students will learn how to work with data using Microsoft Excel. The focus will be on data cleaning, formulas, and building analytical reports.

Topics Covered:

• Introduction to Data Analytics and Excel

• Understanding datasets and data types

• Data cleaning techniques (Remove duplicates, Text to Columns, Find & Replace)

• Essential Excel formulas:

• SUM

• COUNT / COUNTA

• AVERAGE

• MIN / MAX

• IF function

• Lookup functions:

• VLOOKUP

• HLOOKUP

• XLOOKUP

• INDEX and MATCH

• Conditional calculations:

• SUMIFS

• COUNTIFS

• AVERAGEIFS

• Pivot Tables and Pivot Charts

• Data visualization using charts

• Creating interactive Excel dashboards

Project: Build a Sales Analysis Dashboard in Excel.

Week 2: SQL for Data Analysis

This week focuses on querying databases and extracting insights using SQL.

Topics Covered:

• Introduction to databases and relational data

• Understanding tables, rows, columns, primary keys, and foreign keys

• Writing basic SQL queries:

  • SELECT

  • WHERE

  • ORDER BY

  • LIMIT

• Filtering data using:

  • AND / OR

  • IN

  • BETWEEN

  • LIKE

• Aggregation functions:

  • COUNT

  • SUM

  • AVG

  • MIN / MAX

• GROUP BY and HAVING clauses

• SQL Joins:

  • INNER JOIN

  • LEFT JOIN

  • RIGHT JOIN

• Advanced queries:

  • Subqueries

  • Multiple joins

• Window functions:

  • ROW_NUMBER

  • RANK

  • PARTITION BY

Project: Analyze sales and customer data using SQL queries

Week 3: Power BI for Data Visualization

Students will learn how to transform raw data into interactive dashboards using Power BI.

Topics Covered:

• Introduction to Power BI

• Connecting to data sources

• Data transformation using Power Query

• Data modeling concepts

• Creating relationships between tables

• Introduction to DAX (Data Analysis Expressions)

• Creating calculated columns and measures

• Important DAX functions:

  • SUM

  • COUNT

  • CALCULATE

  • FILTER

  • DIVIDE

•  

• Data visualization techniques

• Creating charts, tables, and KPI cards

• Interactive dashboard design using slicers and filters

• Publishing reports to Power BI Service

Project: Create a Marketing or Sales Dashboard using Power BI.

Week 4: Real-World Analytics Projects

The final week focuses on applying the learned tools to real-world business scenarios.

Topics Covered:

• Marketing analytics:

• Lead analysis

• Conversion rate analysis

• Campaign performance metrics

• Sales analytics:

• Revenue analysis

• Product performance

• Regional performance insights

• Excel-based reporting and automation

• SQL-based business queries and case studies

• Dashboard storytelling and presenting insights

Capstone Project:

Students will complete a full analytics project involving:

• Data cleaning

• Data analysis

• SQL querying

• Power BI dashboard creation

Skills You Will Learn

• Data Cleaning and Preparation

• Data Analysis Techniques

• SQL Query Writing

• Dashboard Design

• Business Insights and Reporting

• Data Visualization

 Students will progress through the course by starting with basic data handling techniques and advancing to complex data visualizations and analytics projects. The outcomes include the ability to clean data, perform SQL queries, and create dashboards that effectively communicate insights.

Teaching Method & Learning Approach

This course will be delivered in a online mode, The teaching style is practice-oriented, focusing on real-world applications of data analysis concepts. Interactive sessions will encourage student engagement through practical exercises, collaborative projects, and discussions.

Why Learn From This Tutor

Nikhil Veerwani provides clear teaching and structured guidance throughout the course. His approach emphasizes student support, ensuring that learners can ask questions and receive feedback on their progress. This supportive environment is essential for building confidence and understanding complex topics.

Location Context

For those attending offline sessions, this course is located in Bangalore, making it easily accessible for local learners. The convenience of being in a vibrant city with numerous resources enhances the learning experience.

Benefits & Learning Outcomes

Students will gain a solid understanding of data analysis concepts, which is crucial for career advancement. They will build confidence in their skills and improve their ability to analyze and visualize data effectively. By the end of the course, learners will be well-prepared for data analyst roles or further studies in advanced analytics.