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Day 20 of the Data Analyst Bootcamp by @Alex_TheAnalyst !
Data cleaning is an important step in the data analytics process.
It involves identifying and correcting inaccuracies, inconsistencies, and errors in the data to ensure reliable decision-making.
#Dataanalytics #SQL
Data cleaning is an important step in the data analytics process.
It involves identifying and correcting inaccuracies, inconsistencies, and errors in the data to ensure reliable decision-making.
#Dataanalytics #SQL
Today, I completed an SQL data cleaning project using the Nashville housing dataset.
This dataset was a bit messy, with multiple duplicate entries, blank cells, and incorrect data types.
This dataset was a bit messy, with multiple duplicate entries, blank cells, and incorrect data types.
I used these queries to fix the data:
1⃣ CONVERT and ALTER TABLE to change data formats
2⃣ JOIN to populate missing values
3⃣ SUBSTRING and PARSENAME to separate columns
1⃣ CONVERT and ALTER TABLE to change data formats
2⃣ JOIN to populate missing values
3⃣ SUBSTRING and PARSENAME to separate columns
4⃣ CASE statement to change values
5⃣ CTE to remove duplicates
6⃣ DROP TABLE to delete unused columns
Check out this link for more details:
github.com/Jeanstevany
5⃣ CTE to remove duplicates
6⃣ DROP TABLE to delete unused columns
Check out this link for more details:
github.com/Jeanstevany
If you are interested in data analytics, follow me for updates:
🔔 @jeanstevany
🔔 @jeanstevany
https://twitter.com/jeanstevany/status/1650518750502830085?s=20
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