Maven Space Challenge- Data Cleaning & Exploration
By dividing the addresses into a more usable format and cleaning the null prices, I utilized SQL to clean the dataset. On the data set, I also performed data exploration.
Discover moreA database can be created, modified, and deleted using the programming language SQL. SQL is also used to store and retrieve data from databases. Numerous firms favor SQL because of its many advantages.
I've made the decision to develop SQL projects using data analytics challenges from websites like LinkedIn and 8weekssqlchallenge, among others. Each SQL challenge includes a unique database and problem statement that are based on business objectives.
By dividing the addresses into a more usable format and cleaning the null prices, I utilized SQL to clean the dataset. On the data set, I also performed data exploration.
Discover moreI performed data exploration on the dataset and was able to analyze the correlation between dataset features (variables), maximizing the insights into a data set in the end.
Discover moreAs instructed by Alex-The-Analyst, I used Azure Data Studio to carry out the data cleaning process on a Nashville Housing dataset. Skills used involved Joins, Substrings, Charindex, Parse, Partition, CTE, amongst others.
Discover moreAn exploratory data analysis to help understand the dataset Thanks to this study, I was able to identify trends and linkages in the dataset. It helped me decide how to change the dataset in the most efficient way as well.
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