Data Analyst Master Class by Using Power BI, SQL and MS Excel

In this course, learners will gain hands-on experience in MS Excel for data cleaning, data transformation, and basic statistical analysis, and Power BI for interactive dashboards, reports, and real-time data visualization. Alongside analytical skills, students will be introduced to key cyber security principles such as data privacy, access control, threat identification, and secure data handling practices.

Duration

2 Weeks

Skill Level

Moderate

Starts From:

15/05/2026

Category

Science And Technology

Overview

The course “Data Analyst by Using Power BI, SQL and MS Excel” is designed to provide learners with practical skills in data analysis, visualization, and cyber security awareness using industry-relevant tools. This program integrates the fundamentals of data analytics with essential concepts of cyber security, enabling students to analyze data securely and make informed, data-driven decisions.

 

In this course, learners will gain hands-on experience in MS Excel for data cleaning, data transformation, and basic statistical analysis, and Power BI for interactive dashboards, reports, and real-time data visualization. Alongside analytical skills, students will be introduced to key cyber security principles such as data privacy, access control, threat identification, and secure data handling practices.


Our Trainers

Prachi Patodi

16+ years experience. Started career in TCS and currently working as Managing Director of DataFlair Company. Have trained thousands of students from more than 90 countries in data analyst domain.

Modules

Module 1: Introduction to Data Analytics (3 Hours)

Topics:

  • Introduction to Data Analytics
  • Role of a Data Analyst
  • Types of Data (Structured, Semi-structured, Unstructured)
  • Data Analytics Lifecycle
  • Tools used in Data Analytics
  • Real-world applications (Business, Finance, Healthcare, Cyber Security)

Outcome:
Students understand the end-to-end analytics process and industry relevance.


Module 2: MS Excel for Data Analysis (9 Hours)

(Week 1 – Day 2 to Day 4)

Topics:

  • Excel Interface and Data Types
  • Data Cleaning Techniques
  • Sorting, Filtering, Conditional Formatting
  • Excel Functions:
    • SUM, AVERAGE, COUNT
    • IF, VLOOKUP/XLOOKUP
    • COUNTIF, SUMIF
  • Pivot Tables & Pivot Charts
  • Basic Statistical Analysis
  • Data Visualization using Charts

Hands-on:

  • Sales dataset analysis
  • Student performance analysis

Outcome:
Students can clean, transform, and analyze data using Excel.


Module 3: SQL for Data Analysis (9 Hours)

(Week 1 – Day 5 to Week 2 – Day 2)

Topics:

  • Introduction to Databases
  • RDBMS Concepts
  • SQL Basics:
    • SELECT, INSERT, UPDATE, DELETE
  • Filtering:
    • WHERE, LIKE, BETWEEN, IN
  • Sorting & Grouping:
    • ORDER BY, GROUP BY, HAVING
  • Joins:
    • INNER JOIN, LEFT JOIN
  • Aggregate Functions:
    • COUNT, SUM, AVG, MIN, MAX
  • Subqueries

Hands-on:

  • Employee database
  • Customer sales database

Outcome:
Students can query, filter, and analyze data using SQL.


Module 4: Power BI for Data Visualization (7 Hours)

(Week 2 – Day 3 to Day 4)

Topics:

  • Introduction to Power BI
  • Connecting Excel & SQL data
  • Power Query (Data Transformation)
  • Data Modeling
  • DAX Basics
  • Creating Reports & Dashboards
  • Interactive Visualizations:
    • Bar chart, Pie chart, KPI, Slicers
  • Publishing Reports

Hands-on:

  • Sales dashboard
  • HR analytics dashboard

Outcome:
Students can build professional dashboards using Power BI.


Module 5: Mini Project & Case Study (2 Hours)

(Week 2 – Day 5)

Activities:

  • Real-world dataset
  • End-to-end analysis:
    • Excel → SQL → Power BI
  • Dashboard presentation
  • Interpretation of insights

Sample Projects:

  • E-commerce sales analysis
  • Student result analytics
  • Cyber incident dataset analysis

Outcome:
Students apply all tools in a real project.


Outcomes

Apply MS Excel techniques for data collection, cleaning, preprocessing, and basic statistical analysis.

Use Power BI tools to design interactive dashboards and visual reports for effective data interpretation.

Analyze real-world datasets to extract insights and support data-driven decision making.

Demonstrate understanding of cyber security fundamentals including threats, vulnerabilities, and risk concepts in data environments.

Implement secure data handling practices such as data privacy, access control, and protection of sensitive information.

Integrate data analytics with cyber security perspectives to identify risks and improve system security.

Develop and present analytical reports and dashboards for business and security case studies.

Apply analytical and security skills in mini projects and real-world problem scenarios.


Contact

Name: PROF. VINEET GUPTA

Mobile No: 7000038733


Course Image

This Premium course is included in plans

1000/-

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