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moses odhiambo
moses odhiambo

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INTRODUCTION TO MS EXCEL FOR DATA ANALYTICS

#beginners #dataengineering #datascience #learning

#What is Microsoft Excel?

Microsoft Excel is a spreadsheet application used to store, organize, clean, and analyze data. It allows users to work with data in rows and columns and perform calculations, summaries, and simple analysis without programming.

In data analytics, Excel is often the first tool beginners learn because it is visual, easy to understand, and widely used in workplaces.

##Understanding the Excel Interface

When you open Excel, you will see:

  • _Workbook _– the Excel file

  • Worksheet – individual sheets inside a workbook

  • Rows – horizontal (numbers: 1, 2, 3…)

  • Columns – vertical (letters: A, B, C…)

  • Cells – intersection of a row and column (e.g., A1)

Each cell can hold:

1.Text
2.Numbers
3.Dates
4.Formulas

###Types of Data in Excel

Excel commonly works with the following data types:

_- Text (Names, Categories, Locations)

  • Numbers (Sales, Age, Quantity)
  • Dates & Time
  • Boolean values (TRUE/FALSE)_

Understanding data types is important because formulas only work correctly when data is properly formatted.

####Basic Data Entry and Formatting

Data Entry

  • Click on a cell and type your data

  • Press Enter to move down or Tab to move right

Basic Formatting

  • Formatting helps make data easier to read:
  • Bold headers
  • Adjust column width
  • Apply number formats (currency, percentage, date)
  • Add borders to tables

N/B: Good formatting improves clarity, not analysis but clarity matters.

#####Sorting and Filtering Data

Sorting

Sorting helps organize data:

  • Ascending (A–Z, smallest to largest)
  • Descending (Z–A, largest to smallest)
  • Example: Sorting sales from highest to lowest.

Filtering

Filtering allows you to view specific records without deleting others. Example:

  • Show only sales from Nairobi/Mombasa
  • Show only products with sales above 10,000
  • Sorting and filtering are essential for exploring data quickly.

######Basic Excel Formulas for Data Analysis
Take note Formulas always start with an equals sign (=)

Common beginner formulas:

=SUM() – Adds values
=AVERAGE() – Calculates mean
=COUNT() – Counts numeric values
=MAX() – Finds the highest value
=MIN() – Finds the lowest value

Examples:

=SUM(B2:B10)
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This formulas turn raw data into useful insights...

#######Introduction to Data Cleaning in Excel

  • Before analysis, data must be clean.
  • Common data cleaning tasks:
  • Removing duplicate values
  • Fixing spelling inconsistencies
  • Handling empty cells
  • Trimming extra spaces
  • Ensuring consistent data formats
  • Clean data leads to accurate analysis

########Simple Data Analysis Using Excel

  • With clean data, Excel can be used to:
  • Calculate totals and averages
  • Compare categories
  • Identify trends
  • Answer basic questions such as:
  • Which product sold the most?
  • What is the average monthly revenue?
  • Which region performs better?
  • This is the foundation of data analytics.

#########Why Excel is Important for Data Analytics Beginners

Excel is important because:

  • It requires no coding
  • It is used in almost every industry
  • It helps understand data concepts visually
  • It prepares learners for advanced tools like SQL, Python, and Power BI

N/B: Many professional data analysts still use Excel daily.

##########Summary

  • What Excel is and how it is used in data analytics
  • How to navigate the Excel interface
  • Basic data entry, formatting, sorting, and filtering
  • Simple formulas for analysis
  • The importance of clean data
  • Excel is the starting point of a data analytics journey.

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