Data Cleaning And Exploration With SQL
Data cleaning and exploration with SQL typically involves using SQL commands to filter, sort, and manipulate data in a relational database. This process can include tasks such as removing duplicate rows, correcting data errors, and filling in missing values. Exploration involves using SQL queries to gain insights into the data, such as identifying patterns, trends, and relationships between different columns and tables. Common SQL commands used for data cleaning and exploration include SELECT, WHERE, GROUP BY, JOIN etc. In this section of my portfolio website,I carried out analysis on two different dataset with the use of Miscrosft SQL Server.
In this project,I performed EDA on COVID-19.Exploring data on COVID-19 using Microsoft SQL Server involves using SQL commands to filter, sort, and manipulate data in a relational database. This process include tasks such as joining multiple data sources, filtering data based on certain criteria, and calculating various statistics.After the data exploration process, I was able to gain insights into the spread of COVID-19, such as identifying hotspots, understanding the impact of certain policies, and tracking the progress of the pandemic over time.
In this project,I cleaned the Nashville housing Dataset and prepared it for visualization. Cleaning data in the Nashville Housing dataset using Microsoft SQL Server would involve using SQL commands to filter, sort, and manipulate the data in the database. This process can include tasks such as removing duplicate rows, correcting data errors, and filling in missing values.