Analyzing Music Sales Data: SQL PROJECT

 

Project Overview

The project revolves around a comprehensive music sales dataset containing information about customers, invoices, tracks, and artists. Through a series of SQL queries, we aim to extract valuable insights to inform business decisions within the music industry.

Senior Most Employee by Job Title

We begin our analysis by identifying the senior-most employee based on job title. By querying the dataset, we can pinpoint the employee holding the highest-ranking position within the company.

Countries with the Most Invoices

Understanding sales distribution across different countries is crucial for targeted marketing and expansion strategies. By querying the dataset, we can identify the countries generating the highest number of invoices, indicating regions of strong market presence.

Top Values of Total Invoice

Next, we analyze the top three values of total invoices to gain insights into the magnitude of sales transactions. This information can aid in understanding revenue distribution and identifying high-value customers.

City with the Best Customers

To reward loyal customers and boost engagement, we identify the city with the highest sum of invoice totals. This city will be the prime location for hosting a promotional music festival, attracting both existing and potential customers.

Best Customer Identification

Recognizing and appreciating top-spending customers is essential for fostering customer loyalty. By querying the dataset, we pinpoint the individual who has spent the most money, earning them the title of the best customer.

Moderate-Level Queries

In addition to basic insights, the project includes moderate-level queries that offer deeper analysis:

  • Rock Music Listeners: We identify customers who prefer rock music by querying their email, first name, last name, and preferred genre, ordered alphabetically.

  • Top Rock Bands: Inviting popular artists to events can enhance their fan engagement. We identify the top 10 rock bands based on the total number of tracks they've written.

  • Longest Tracks: We list tracks with a duration longer than the average song length, providing valuable insights into listener preferences and consumption habits.

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