Introduction.
Microsoft Excel is a popular spreadsheet tool by Microsoft that helps users store, organize, analyze, and display data using rows and columns. You don’t need programming skills to start analyzing data with Excel. With simple features like tables, formulas, sorting, and charts, Excel helps you understand data and make decisions based on it.
This article introduces how MS Excel can be used for basic data analytics, using simple explanations and practical examples.
What is Data Analytics.
The process of examining raw data to uncover hidden patterns, trends, and insights, which are then used to make informed, data-driven decisions. It involves collecting, cleaning, and organizing data to transform it into actionable information for solving problems or forecasting future trends.
what find in excel.
Rows (horizontal – labeled with numbers)
Columns (vertical – labeled with letters)
Cells (where rows and columns meet, e.g., A1)
Each cell can store text, numbers, or formulas.
Example of a dataset:
Turning Data into a Table
Tables ensure ease in analysis.
Steps to follow;
- Select your data
- Press Ctrl + T
- Click OK
Benefits of tables:
-Automatic filters
-Better formatting
-Easier analysis
Data sorting.
This is the process of arranging rows of data in a specific, meaningful order. Example: Sort scores from highest to lowest to see top performers.
Steps to follow;
1.Click anywhere in the Score column
2.Go to Data → Sort Z to A
Data Filtering.
Filtering helps you view specific data only.
Example: View only students who scored above 70.
Steps:
1.Click the filter arrow in the Score column
2.Choose Number Filters → Greater Than
3.Enter 70
FORMULAS and FUNCTIONS.
Formulas allow Excel to calculate values automatically.
Arithmetic/Basics:
=A1+B1, =A1-B1, =A1*B1, =A1/B1 (Basic operators)
=SUM(A1:A10): Adds a range of cells.
=AVERAGE(A1:A10): Calculates the mean of a range.
=PRODUCT(A1:A10): Multiplies cells.
=COUNT(A1:A10): Counts cells containing numbers.
=ROUND(A1, 2): Rounds a number to a specific digit.
Logical & Conditional:
=IF(condition, value_if_true, value_if_false): Checks a condition.
=SUMIF(range, criteria, [sum_range]): Sums cells based on a condition.
=COUNTIF(range, criteria): Counts cells based on a condition.
Lookup & Reference:
=VLOOKUP(lookup_value, table_array, col_index_num, [range_lookup]): Finds data in a table.
Conditional formatting.
This highlights important data visually.
Example: Highlight scores below 70 in red.
Steps:
- Select the Score column
- Go to Home → Conditional Formatting
- Choose Highlight Cell Rules → Less Than
- Enter 70
Use of Pivot Table
A Pivot Table is used to summarize and analyze large amounts of data quickly. It helps you see patterns, totals and averages without writing formulas.
Steps in creating a pivot table;
1.Select your data
2.Go to Insert → PivotTable
3.Click OK
Excel creates a new sheet with Pivot Table fields.
Example Use Case;
Using the student scores data, a Pivot Table can:
- Show average score per subject
- Show total scores per subject
- Count how many students took each subject
How to do it:
1.Drag Subject to Rows
2.Drag Score to Values
3.Choose Average or Sum
Importance of pivot tables.
- No formulas needed
- Fast data summarization
- Easy to update
- Ideal for reports and analysis
Creating Charts.
Charts help you visualize data, making it easier to understand trends.
Example: Column Chart for Scores.
Steps:
1.Select the data
2.Go to Insert → Column Chart
3.Choose a chart style
Why Excel Is Good for Beginners in Data Analytics:
- Easy to learn
- No coding required
- Widely used in schools and workplaces
- Great for small datasets
- Strong visualization tools
Conclusion.
Microsoft Excel is a powerful and beginner-friendly tool for data analytics. With basic features like tables, formulas, sorting, filtering, and charts, you can analyze data and gain useful insights without technical complexity. If you are starting your journey in data analytics, Excel is a perfect place to begin.
Good luck in your journey of analytics.
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