The Chinook Data Analysis Project is an ongoing, comprehensive data exploration and analysis initiative designed to extract valuable business insights from the Chinook music store database. This project is currently under construction, but it already showcases a diverse range of analytical techniques and tools, highlighting my proficiency in data management, analysis, and visualization.
At the core of this project is the Chinook Database, which I’ve accessed and queried using PostgreSQL. Through advanced SQL queries, I’ve addressed various business questions, such as identifying top-selling tracks, understanding customer purchasing behavior, and evaluating sales performance across different regions. These queries form the foundation for deeper analyses and set the stage for extracting actionable insights.
To further enhance this exploration, I’ve employed Python and its powerful libraries, including Pandas, Matplotlib, and Seaborn. These tools enable me to clean, manipulate, and visualize the data, offering a clear view of trends, patterns, and anomalies. Whether it’s generating time series analyses, customer segmentation, or sales forecasting, these libraries have been instrumental in transforming raw data into meaningful visuals and insights.
Additionally, I’ve integrated Google Spreadsheets into the project (can be found at Chinook.zip folder) to demonstrate practical, hands-on skills with everyday business tools. By leveraging functions like VLOOKUP, creating Pivot Tables, Conditionals, Queries & Macros, I’ve answered key business questions and showcased how to seamlessly integrate multiple datasets, such as linking customer information with invoice details. This approach not only underlines my technical capabilities but also illustrates how data analysis can directly inform business decisions in a user-friendly, accessible format. All actions performed using advanced spreadsheet functions are meticulously highlighted in different colours such as: Vlookup in Blue, Pivot Tables in Green, Conditionals in Yellow and Queries in Red colour. This color-coding allows for easy identification and tracking of these operations, providing clear visibility into the application of these techniques throughout the project.
As the project progresses, I plan to create compelling visual narratives using Tableau. These Tableau Stories and Dashboards will present the findings in an engaging and interactive manner, allowing stakeholders to explore the data and insights dynamically. The use of Tableau will cap off the project, turning data into stories that drive business understanding and decision-making.