Advanced Dashboarding - Sales to Marketing Data Analysis on Theoretical Data Generated with AI and Python, Analyzed in SQL, and Visualized in Power BI

This was an exciting project that encompassed true data exploration and correlation through several different software tools. After looking through inadequate data on free data sources, I decided to make my own! I used AI to create two small data sets for Sales and Marketing of a heavy machinery manufacturing company. Then I took the data design to Python to generate over 5,000 rows of it spanning over 10 years of company operation with the use of the Python Faker Library. Next, I analyzed and aggregated the data sets together using a multiple key join in SQL and visualized the results in a company brand custom theme in Power BI. This was an extensive journey into the capability of collaborative technologies.

First take a look at the Python code used to generate the data executed in Jupyter Notebook.

Next, take a look at the Multi Key Join and Data Aggregation SQL code used to summarize and segment the data accordingly to prepare it for visualization.

Now you can view the dashboard visualization results! This interactive dashboard lets you manipulate the Sales and Marketing Data for State, Region, Sales Channel, Marketing Channel, and Product all over a 10 year time frame. This grants you the ability to realize which marketing channels are most successful in specific areas of operation that yield the greatest return on investment in relation to the marketing return on investment ratio. Dynamic forecasting is also included that will update based on the amount of prior years you would like to be factored in the for forecast function, along with an auto updating AI Quick Summary.