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data_cleaning

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An SQL data cleaning project

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# data_cleaning
A repository of SQL data cleaning projects.

## Introduction
This is a repo for small projects that can be used to practice data cleansing using SQL, Excel or any other method.  This small project was inspired by a post made by [Sushanta Khara](https://www.linkedin.com/posts/ksushant_data-cleaning-and-preparation-with-sql-activity-6970218566356791296-tXvN?utm_source=share&utm_medium=member_desktop) on LinkedIn.

### Project List:
- [Club Member Information](https://github.com/iweld/data_cleaning/tree/main/club_member_info)

## Problem Statement

In Data Analysis, the analyst must ensure that the data is 'clean' before doing any analysis.  'Dirty' data can lead to unreliable, inaccurate and/or misleading results.  Garbage in = garbage out.

These are the some steps that can be taken to properly prepare your dataset for analysis.

- Check for duplicate entries and remove them.
- Remove extra spaces and/or other invalid characters.
- Separate or combine values as needed.
- Ensure that certain values (age, dates...) are within certain range.
- Check for outliers.
- Correct incorrect spelling or inputted data.
- Adding new and relevant rows or columns to the new dataset.
- Check for null or empty values.

Using the criteria above, create a new SQL table with the properly formatted data.

## Datasets used

This repository contains different projects/datasets to give the user many opportunities to practice:
- Basic select statements (select, where, group by, having).
- Aggregate functions (count, sum, min, max, avg)
- Joins (inner, outer, left, right)
- CTE's, temp tables and views
- string & date manipulation functions.
- Window functions (rank, lead, lag, row_number, ntile...)

data_cleaning

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