Cleap up your data (Techniques and tips)

What is Data Cleaning ?
The process of amending or removing data in a
Data Set/ Data Base that is incorrect, incomplete,
improperly formatted, or duplicated.

Before Data Cleaning :
1. Have a Backup to play freely with your Dataset.
2. Understand your Dataset.
3. Specify your Problems.
4. Vision before tools.
5. Set your Priorities.

Main Problems :
1. Duplicates.
- Places.
- Removing.

Main Problems :
2. Missing Data :
- Number.
- Places.
- Filling : Choose the right Decision First.

Main Problems :
3. Spelling Errors :
How to check and fix them ?

Main Problems :
4. Text to Columns :
- How to divide one cell into two ?

Main Problems :
5. Columns to Text :
How to combine two cells in one ?

Main Problems :
6. Part of the Cell to Columns :
- Mid Function.
- Flash Fill.

Main Problems :
7. Replacing Shortcuts / Unification of Variables :
- Why ?
- How ?

Main Problems :
8. Lower / Upper / Proper Case :
- Lower Function.
- Upper Function.
- Proper Function.
- Flash Fill.

Main Problems :
9. Some Data In the Wrong Place.

Main Problems :
10. Day / Month / Year :
- Day Function.
- Month Function.
- Year Function.
- Text Function.

Main Problems :
11. Invisible Spaces :
- Why ?
- How ?

Main Problems :
12. Format of the Cell :
- Is Number Function.
- Is Text Function.

Main Problems :
13. Unwanted Punctuation or Duplicated Parts of
Text :
- Right Function.
- Left Function.
- Replace Function.
- Substitute Function.
- Multi Substitute Function.

My Contact :
 Mobile : 01017008287
01155523721
 Mail : ahmed.essam.mohamed1@gmail.com
 Linkedin : www.linkedin.com/in/ahmed-essam-mohamed/

Cleap up your data (Techniques and tips)

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