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Data Modeling with PostgreSQL Schema

Executing basic CRUD commands is standard practice when building a system. A well-designed system is highly agnostic, and its concepts can be transferred between different lower-level products. Some of the most popular RDBMS include PostgreSQL, OracleSQL, and MySQL. But where does the data originate? How frequently does it change? How many files are there, and how often do we receive new ones? Could IoT 🛰 devices be a factor?

To the infinity and beyond… - Buzz Lightyear 1995

The application below provides directory paths where the client-side system stores data files for a music application product. I analyzed the data, built its entities, and established the fundamental links between them. The analytics team is keen to understand which songs users are listening to.

cur.execute("DROP DATABASE IF EXISTS ...")

This project was completed under the Data Engineer Udacity Nanodegree link

tech: PostgreSQL, Python, Pandas


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