Have you ever heard of Microsoft Excel and wondered why it is used by so many people in data analytics? Never mind, this guide simplifies it in the easiest manner possible.
Microsoft Excel is among the most potent and easy-to-use tools to deal with data. Most analysts tend to begin with Excel before progressing to such tools as Python, SQL, or Power BI, and they have a good reason to do so. Excel enables a person to arrange, clean, analyze, and visualize data in the same place.
Excel can be used to transform raw data into valuable information, whether you are following sales, costs, survey results, or monitoring the output of your social media presence.
*What you can do to the data using Excel:
*
- Storing and managing information.
- Automatic results calculation.
- Summarize and compare data
- The visualization of trends should be done using charts and tables.
- Swiftly identify trends and observations. What you are to learn in this article. At the end of this guide, you will be in a position to:
- Learn the meaning and purpose of Microsoft Excel and the way it can be used to support data analytics.
- Find rows, columns, and cells within a worksheet.
- Create and systematize information in an uncontaminated table format.
- Basic Excel functions to be used include SUM, AVERAGE, COUNT, and IF.
- Sort, filter, and delete duplicates with cleaning data.
- Pivot tables to summarize big data.
- Simple charts should be created to create visual trends and comparisons.
- Knowledge of the construction of Excel dashboards to use in reporting.
- Learn to work with data as a novice. Some of the terms that you will come across before getting into it are: Cell—A row and column intersection (e.g., A1) Column—Vertical cells denoting A, B, C, and so on. Row—Horizontal cells indicated by 1, 2, 3, etc. Worksheet—Single workbook within an Excel file. Workbook A Microsoft Excel file with one or more worksheets. Dataset A structured table of data, a row and a column of data. Formula—An equation that carries out a calculation (e.g., =A1+B1) Function— An inbuilt formula like SUM or AVERAGE. Range—A set of chosen cells (e.g., A1:A10). Sort—Organizing information in a given arrangement. Filter—The display of only data with a specific set of conditions. Pivot Table—It is a tool that is used to summarize large amounts of data automatically. Chart— A chart is a graphical illustration of data. Dashboard— This is a one-page display of essential insights. Data cleaning involves preparing information to make it accurate and usable.
I Introduction to Microsoft Excel.
What Is Excel?
Microsoft Excel is a Microsoft spreadsheet application. It assists users in storing data, organizing data, and computing and analyzing data based on the tables composed of rows and columns.
With Excel, you can:
Calculate with the help of formulas and functions.
Sort and filter information
Create charts and graphs
Aggregate big data in pivot tables.
In simple words, Excel converts raw data into effective information upon which decisions can be made.
Knowledge of rows, columns, and cells.
Excel spreadsheets are constructed with:
Rows—Horizontal lines (1, 2, 3…)
Columns—Vertical lines (A, B, C…)
Cells—where rows and columns meet.
Each cell can contain:
Text (names, categories)
Numbers (sales, quantities)
Dates
Formulas
Example Dataset
2 DATA FUNCTIONS
SUM—Adds values in a range
=SUM(E2:E4)
AVERAGE—Finds the mean value
=AVERAGE(E2:E4)
Application: Means scores or sales per day.
COUNT -Counts numeric values
=COUNT(E2:E4)
Use case Number of transactions.
COUNTA—Counts non-empty cells
=COUNTA(E2:E4)
Application: Number of products or customers.
IF—Applies logical conditions
=IF(C2>10,"High","Low")
Use case: Categorization of performance (high/low, pass/fail).
3. Data Cleaning in Excel
Data usually requires cleaning before analysis.
Ordinary household chores are:
Duplicates Removal Data Removal Duplicates
- Select the data (click anywhere inside your table or select the column).
- Go to the Data tab.
- Click Remove Duplicates.
- Tick the column(s) you want Excel to check.
- Click OK.
Filtering allows you to:
View only one product
Filter by a particular period of time.
Only selected records should be analyzed.
Accurate analysis is a result of clean data.
4. Pivot Tables: Potent Summaries.
Pivot tables provide an opportunity to summarize big data in seconds without complicated formulas.
You can answer such questions as
Total sales per product
Monthly sales trends
Quantity sold by category
Steps to Create a Pivot Table
Select your dataset
Click Insert → PivotTable
Choose where to place it
Drag fields to rows, columns, and values.
Example:
Rows → Product
Values → Sum of Total Sales
Everything is calculated automatically in Excel.
5. Charts in Excel
Numbers are transformed into visual charts, which are easy to comprehend.
Common Chart Types
Column Chart—Compare categories.
Line Chart—Display trends over time.
Pie Chart – Show proportions
How to Create a Chart
Select the data
Click Insert
Choose a chart type
Insights are better understood with the help of charts.
6. Dashboards in Excel
The dashboard is one page, displaying major insights.
A basic Excel dashboard can contain:
Total Sales (headline number)
Sum of price
Sum of quantity
Dashboards combine:
Pivot Tables
Charts
Slicers (filtering filters)
They assist in providing the decision-makers with a fast understanding of performance.
Conclusion
The best place to begin data analytics is Microsoft Excel. It allows you to:
Organize data efficiently
Calculate through the use of functions.
Clean and filter messy data
Respond to datasets using pivot tables.
Visualization of insights with the help of charts.
Develop report dashboards.
Being proficient in Excel provides a solid base in that an individual reaches higher tools such as Power BI, Python, or SQL.
The best of your analytics to you.
Top comments (0)