Exploratory Data Analysis Using Excel


Exponential data growth and data-driven decision-making are driving organizations towards data analysis. Data analysis is the science of analyzing raw data to draw meaningful business insights.

Excel has been around in the industry since the early 1980s and is widely used today. Not just calculations, but Excel is a very powerful data analysis tool with several notable additions by Microsoft. It is easy to be productive with Excel because of its simplicity.


This course will help anyone interested in deriving valuable insights from data and using them to improve business decision-making. Excel is an affordable self-service Business Intelligence tool for EVERYONE. This is not an MS Excel course, and we will study only the basic Excel functions needed for data analysis. Macros and VB scripts are not part of the scope. This course will be ideal for:

  • Professionals who work in IT or any core industries like finance, sales, supply chain, CRM, etc.
  • Professionals who want to learn business analytics but have no prior knowledge of analytics, statistics.
  • Professionals who want to begin their journey in Data Science, Business Analytics, or Data Visualization.
  • Fresh graduates who must demonstrate their proficiency in data analysis skills upon entering the workforce.

  •   Microstrategy report states that 94% of enterprises say data is essential to business growth.
  •   According to Glassdoor, the average salary for a Data Analyst with Microsoft Excel skills is $73,824 per year in the United States.
  •   Data and AI show the highest growth rate at 41% per year as per the World Economic Forum’s “Jobs of Tomorrow.”

Course Objectives

This course will help you develop employable data analysis skills, making it apt for professionals looking to enter the field of analytics without getting into coding. Experts use Excel for advanced analytics, and now you can too! The key learnings are:

  • Understand data analysis and how businesses use it.
  • Learn how to clean collected data and prepare data for analysis.
  • Different techniques of exploratory data analysis and visualization.
  • Analyze data using PivotTables and PivotCharts.
  • Creating interactive dashboards.
  • Merging Data from different sources.
  • Advanced-Data Analysis
  • Work on real-life case studies and projects to derive data-driven insights.


Course Learn from an Industry Expert

This course is designed by industry experts with ten years of IT experience in analytics.

Course Video Lectures

These sessions will give you the flexibility to plan your learning journey based on your schedule.

Course Case-Studies

Get more practice with case studies specially designed to put all your learning into practice.

Course Real-life Project

Apply your learning in a real-life project for the sales performance of Mega Mart, a leading supermarket chain. Find more details in the section below.

Course Module-wise Practice Questions

Learning theory and not putting it into practice is not a good way of learning. You will get a range of practice questions for each module to reinforce the concepts that you learn.

EDA Course Features

Video Lectures

Module-wise Practice Questions

Real-life Case Studies

Course Project

Course Proficiency Certificate

1-year TechEdge Portal Access

Skills Covered

  •   Data Analysis
  •   Microsoft Excel
  •   Pivot Tables
  •   Project Planning
  •   Exploratory Data Analysis
  •   Power Query
  •   Data Cleansing
  •   Data Visualization
  •   Data Cleaning


Source: https://netflixtechblog.com/artwork-personalization-c589f074ad76

Netflix Content Descriptive Analysis

  • Netflix is the world's leading streaming entertainment service with 204 million paid memberships in over 190 countries, enjoying TV series, documentaries, and feature films across a wide variety of genres and languages.
  • This descriptive analysis case study for Netflix focuses on discovering popular content on Netflix, top countries actively preparing content, movie and TV show trends, average movie duration, and other business insights.


Superstore Low Profits Diagnostic Analysis

  • As part of the finance team of the Super Store, you noticed that there were some profit problems for some inventory categories.
  • You decide to investigate which sub-category has profit problems, where the problems are happening, for which products, and the reason.
  • This diagnostic analysis aims to find the root cause for low profits in sub-categories.


Mega Mart Sales Performance Analysis

  • The management wants to look at the key metrics: sales, profit, and profit ratio and the proportion of sales across cities. They also want to analyze the top sold products to promote further and increase sales.
  • In this capstone project, you will analyze key metrics, derive insights to formulate the sales strategy, and build an interactive dashboard for Mega Mart.

Course Syllabus

Course Module
Module 1: Overview of Data Analysis
Data-driven Management in Organizations
What is Data?
Need for Data Analysis
Data Analysis Process & Examples
Introduction to Excel, Pros, and Cons
Using Excel for Data Analysis
Module 2: Collect and Prepare Data
Data Collection for Analysis
Importing Data into Excel
Data Types
Data Types in Excel & Formatting
Data Preparation before Analysis
Excel Tables
Filtering Data
Sorting Data
Analytical Functions
Module 3: Data Analysis & Visualization
Creating Cross-Tabulated Reports using:
  • Excel Formulae
  • Dynamic Arrays
  • Pivot Tables
Comparison Analysis using Bar Charts
Trend Analysis and Predictions using Line Charts
Distribution/Frequency Analysis using Histograms
Correlation Analysis using Scatter Plots
Part-to-whole Analysis using Area Charts
Creating Final Interactive Dashboard
Module 4: Data Merging
Need for Data Merging
Using the VLOOKUP() Function
Using Power Query
Module 5: Advanced Data Analysis
Data Analysis using the Analysis ToolPak:
  • Histogram
  • Rank & Percentile
  • Descriptive Statistic
  • Correlation
  • T-Test


Every course participant will receive a course completion certification from Techcanvass. The course certification:

  • Proves that you have gained considerable knowledge on performing EDA with Excel.
  • It is a significant step forward towards your career growth.
  • Certifies your course completion.
  • Provides an opportunity to go ahead and share your achievement on LinkedIn, Facebook, etc., add it to your resume, tell your friends!


Priya Telang

Priya Telang

Priya Telang is a senior data analyst. She is an influential, result-oriented, and self-motivated leader with excellent analytical and critical skills. She has a diversified professional experience of 10 years in IT, the public sector, and curriculum development. Her journey started with Business Intelligence and analytics in Accenture with prominent clients in retail, finance, media & telecommunication, followed by a fellowship with Teach for India and curriculum development. She is passionate about using data analysis and machine learning to solve problems. She is a certified IIBA Business Data Analyst and certified Tableau Desktop Specialist.

Exploratory Data Analysis Using Excel Training Fees

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Exploratory Data Analysis Using Excel

₹ 2,673 ₹2,970 ( 10% OFF )
GST extra
Self-paced Course
  •     Self-paced Course
  •     Course Certification
  •     End of Chapter Quizzes
  •     Real-life Project
  •     Email Support from the Expert

Frequently Asked Questions (FAQ)

Is knowledge of excel basics a prerequisite?

Basic knowledge of Excel is not necessary but helpful. Even if you are new to Excel, this course covers the basic Excel concepts. So, learning Excel will not be difficult.

What is exploratory data analysis?

Exploratory data analysis (EDA) is performed before the actual data analysis, and it helps to understand the nature of the data set. It is used to check if the data is making sense in the context of the business problem, look at the data summary, identify data quality issues, identify outliers, find data patterns, and much more.

How is Excel used for data analysis?

In the simplest terms, Excel organizes raw data into a readable format to draw insights. You can even add calculations and summary statistics, customize fields, merge or segment, and visualize data. This will help to explore data, draw patterns, understand correlations, and much more.

What types of analysis can you do with Excel?

Data Analysis helps you evaluate business data by inspecting, cleaning, transforming, and modeling for effective business decision-making. You can do a comparison, trend, part-to-whole, correlation, distribution analysis, and much more.

Which built-in features of Microsoft Excel can be used for analysis?

Features like pivot tables, power pivot, data analysis Toolpak, and the What-if analysis can be used for analysis.

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