SQL Project: Analysis of Paintings and Museums

The primary goal of this project is to analyze data related to paintings, artists, museums, and various other related attributes to derive meaningful insights and answer specific queries using SQL. This project involves querying data from multiple tables related to paintings and museums to answer business-related questions. The analysis covers data retrieval, manipulation, and cleaning using SQL queries. The project uses multiple tables stored in a database named Paintings. The tables include such items as museum, artist, museum_hours, canvas_size, image_link, product_size, subject, work. The project involves the use of various SQL techniques including:

SELECT statements for data retrieval.

JOIN operations to combine data from multiple tables.

Subqueries for nested queries.

Aggregation functions such as COUNT, SUM, and AVG.

Data cleaning techniques such as removing duplicates.

Conditional statements for filtering data.

Ordering results using ORDER BY.

Grouping results using GROUP BY.

The analysis of the paintings database revealed important insights about the distribution and pricing of artworks. The queries identified museums without paintings, artworks with pricing anomalies, and artists whose works are internationally displayed. This information can help museum management make informed decisions about their collections.

Through this project, I deepened my understanding of database structures and relationships, honed my SQL query skills, and emphasized the importance of data validation and integrity. I enhanced my analytical abilities by interpreting query results to provide insights into artwork distribution, pricing, and display. Additionally, I recognized the value of data-driven decision-making for museum management, improved my problem-solving skills by addressing specific queries, and gained experience in effectively documenting and communicating project findings.