Using SQL to take a deeper look into our subscribers churn rate during Jan, Feb, Mar of 2017.
Here we take a look into healthcare cost for individuals with different metrics including if they have children, their age, BMI, and if they are a smoker.
Taking a deeper look into the conversion rates with the number of pageviews, checkouts, & purchases of a sample data set using SQL.
The superstore data visualization sample shows sales data for a fictional chain of retail superstores across multiple locations. The data is presented in the form of interactive charts and graphs, which allow the user to explore various aspects of the sales data, such as sales by region, product category, and time period.
The Python code script performs ETL tasks for a data analyst job by extracting data from a source file, transforming it by creating new columns and filtering it by date range, aggregating it by month, and loading it into a database.
The student loan data visualization sample shows student loan debt trends and statistics for a fictional college over several years. The data is presented in the form of interactive charts and graphs, which allow the user to explore various aspects of the student loan data.
Starting with a clear objective is an essential step in the data analysis process. By recognizing the business problem that I'm trying to solve and setting well-defined goals, it’ll be way easier to decide on the data that's necessary.
I gather all necessary and pertinent data to have a complete, 360-degree view of the problem to answer questions & avoid scope creep. The data is then cleaned by processing and formatting it in a consistent and accurate manner that allows for easy analysis and interpretation.
I analyze by using mathematical and statistical methods to identify patterns and trends. Once the results of the analysis have been found, I create visualizations to express findings in a clear and concise way.
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