Fintech database: from 10,000 transactions to SQL queries
M1 group project: model and build a database from 10,000 financial transactions, then query it in SQL to read purchasing behavior.
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Context
A database course in the MITIC master's, in a group of four: start from a file of 10,000 financial transactions and turn it into a database that can be queried to understand customers' purchasing behavior.
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What I did
I worked on the modeling, from the conceptual model to the logical model, with integrity constraints and normalization, then on the SQL implementation and the analysis queries. The group also wrote a teaching document that explains the method step by step.
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What came out of it
A working database holding the 10,000 transactions, advanced queries that bring out purchasing profiles, and a reusable design guide. The full document can be downloaded below.