GETTING STARTED WITH EXCEL FOR DATA ANALYTICS: FROM BASICS TO DATA CLEANING

EXCEL OVERVIEW

• What is Excel? These is a spreadsheet tool for organizing, analyzing, calculating, and visualizing data. Wiledy used for personal and professional data management.

EXCEL INTERFACE

• This is an Excel workbook that usually subdivided into work sheets

1. Ribbon: Toolbar with commands(Home, insert, data..)
2. Quick Access Toolbar: save, undo, redo.
3. Formula Bar: displays cell content
4. Rows, columns, cells.

Data validation

• The restrictions on the type of data user can input into a cell. (Dropdown lists, Numbers , ranges, date limits, text length)

THE DATA CLEANING

• Data cleaning is the process where you prepare raw datasets so they are accurate, consistent, and ready for analysis. This is a very crucial set because one gets to correct small errors , duplicates which may lead to misleading results in the formulas. Clean data ensures reliability and save time when performing deeper analysis.

Raw uncleaned data

Cleaned data

DATA CLEANING TECHNIQUES

• Removing duplicates: Prevents inflated results in analysis.
• Mombasa
• Mombasa

Standardizing text this ensures consistency

• NAIROBI
• NairoBi

checking dates: corrects inconsistent format and invalid entries, fixing words format:

• use PROPER() to standardize capitalization in names.

DATA FORMARTTING & CLEANING

Number Formatting

• this changes how numbers display without altering their actual value Conditional formatting
• This highlights cells automatically based on trends or criteria

CONCLUTION

In conclusion data cleaning in excel is more the a technical step, it is the foundation of reliable analysis. This is a effective data cleaning turns Excel from a simple spreadsheet tool into a powerful engine for analytics.