MS Excel for Data Analytics: A Beginner-Friendly Introduction

Howdy! Ever heard of Microsoft Excel? Ever wondered what its use is? Worry not, let me simplify it for you. Microsoft Excel is one of the most poowerful and beginner-friendly tools for data analytics. Before people move to advanced tools like Python or SQL, they often start with Excel, and for good reason. It helps you organize data, clean it, analyze it, and visualize it all in one place. How cool is that?

Whether you are tracking sales, survey responses, expenses, or social media performance, Excel can turn your raw numbers (data) into meaningful insights.

What You Will Learn from This Article

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

• Understand what Microsoft Excel is and how it is used in data analytics
• Identify rows, columns, and cells in a worksheet
• Enter and organize data in table format
• Use basic Excel functions like SUM, AVERAGE, COUNT, and IF
• Clean data by sorting, filtering, and removing duplicates
• Create Pivot Tables to summarize large amounts of data
• Build simple charts to visualize trends and comparisons
• Understand how Excel can be used to create basic dashboards for reporting
• Gain a strong foundation to start working with data confidently, even as a beginner.

Excel Terms You Will Encounter (Excel & Data Analytics)

Here are simple explanations of key terms used in this article:

1. Cell - A single box in Excel where a row and column meet (example: A1).
2. Column - A vertical group of cells labeled with letters (A, B, C…).
3. Row - A horizontal group of cells labeled with numbers (1, 2, 3…).
4. Worksheet - One page inside an Excel file where you enter and analyze data.
5. Workbook - An Excel file that contains one or more worksheets.
6. Dataset - A collection of related data arranged in rows and columns.
7. Formula - An equation used in Excel to perform calculations (example: =A1+B1).
8. Function - A built-in formula in Excel that performs a specific task (example: SUM, AVERAGE).
9. Range - A group of selected cells (example: A1:A10).
10. Filter - A tool used to display only the data that meets certain conditions.
11. Sort - Arranging data in a specific order (A–Z, smallest to largest, etc.).
12. Pivot Table - A tool that summarizes and analyzes large datasets by grouping and calculating data automatically.
13. Chart - A visual representation of data, such as a bar chart or line graph.
14. Dashboard - A single page that shows key data insights using charts, numbers, and summaries.
15. Data Cleaning - The process of fixing or organizing data so it is accurate and ready for analysis.

All right, let’s get into understanding MS Excel.

1. Introduction to Excel

Definition

Microsoft Excel is a spreadsheet software developed by Microsoft that helps people store, organize, calculate, and analyze data using tables made of rows and columns.
It allows users to:

• Perform calculations with formulas and functions
• Sort and filter information
• Create charts and graphs
• Summarize data using tools like Pivot Tables

Simply put, Excel turns raw numbers into useful information that helps with decision-making.

Excel is a spreadsheet program made up of:

• Rows – horizontal lines (1, 2, 3…)
• Columns – vertical lines (A, B, C…)
• Cells – where rows and columns meet (like A1, B2)

Each cell can contain:

1. Text (Names, Categories)
2. Numbers (Sales, Scores)
3. Dates (1/1/2026, 02-11-2026)
4. Formulas (calculations), among many others.

Example Dataset

Let’s say we have this simple sales dataset:

Date	Product	Quantity	Price	Total Sales
1/1/2026	Pen	10	15	150
1/2/2026	Book	5	70	350
2/3/2026	Pencil	7	25	175
1/4/2026	Rubber	3	10	30

_NOTE: In this table, the Total Sales column is calculated by multiplying Quantity × Price.

This kind of table is the starting point for data analysis.

2. Excel Functions (Basic Calculations)

Functions are built-in formulas that help you perform calculations easily.

1. SUM – Add Numbers

Adds a range of numbers.

=SUM(C2:C5)

This adds all values from cell C2 to C5.

Use case: Total sales, total expenses, total quantity sold.

AVERAGE – Find the Mean

Calculates the average of numbers.

=AVERAGE(D2:D5)

Use case: Average score, average daily sales.

COUNT – Count Numbers

Counts how many cells contain numbers.

=COUNT(A2:A5)

Use case: Number of transactions recorded.

COUNTA – Count Non-Empty Cells

Counts cells that are not empty (text or numbers).

=COUNTA(B2:B5)

Use case: Number of customers or products listed.

IF – Logical Function

Performs a test and returns different results depending on the outcome.

=IF(C2>10, "High", "Low")

This checks if the value in C2 is greater than 10.
** Use case** Categorizing sales as High/Low, Pass/Fail.

3. Data Cleaning in Excel

Before analysis, data often needs cleaning.
Common cleaning tasks:

• Removing duplicates Data -> Remove Duplicates
• Sorting data Data -> Sort A to Z
• Filtering data Data -> Filter

Filtering lets you view only certain data, like:

• Only sales for “Pen.”
• Only records from January

4. Pivot Tables (Powerful Data Summaries)

Pivot Tables help you summarize large data quickly without complex formulas.

You can answer questions like:

• Total sales per product
• Sales per month
• Quantity sold by category

Steps to create a Pivot Table:

1. Select your data
2. Go to Insert -> PivotTable
3. Choose where to place it
4. Drag fields into Rows, Columns, and Values

Example:

• Rows -> Product
• Values -> Sum of Total Sales

Excel will automatically calculate total sales for each product.

5. Charts in Excel

Charts help turn numbers into visuals that are easier to understand.

Common chart types:

• Column Chart – Compares categories
• Line Chart – Shows trends over time
• Pie Chart – Shows proportions

How to insert a chart:

1. Select your data
2. Click Insert
3. Choose a chart type

Example: Sales by product displayed as a column chart.

6. Dashboards in Excel

A dashboard is a single page that shows key insights using charts, numbers, and summaries.

A simple Excel dashboard might include:

• Total Sales (big number)
• Sales by Product (chart)
• Sales by Month (line chart)
• Top Product (text or card)

Dashboards help decision-makers understand performance quickly.

Tools used in dashboards:

1. Pivot Tables
2. Charts
3. Slicers (interactive filters)

Conclusion

Excel is a powerful starting tool for data analytics because it helps you:

• Organize data in tables
• Perform calculations using functions
• Clean and filter messy data
• Summarize information with Pivot Tables
• Visualize trends using charts
• Build dashboards for reporting

Mastering Excel gives you a strong foundation before moving into advanced analytics tools like Power BI, Python, or SQL.

ALL THE BEST IN YOUR ANALYTICS JOURNEY!