Databases need to be structured properly to enable efficient and effective querying and analysis of data. Build normalized, consistent, and performant relational data models. Use SQL Database Definition Language (DDL) to create the data schemas designed in Postgres and apply SQL Database Manipulation Language (DML) to migrate data from a denormalized schema to a normalized one. Understand the tradeoffs between relational databases and their non-relational counterparts, and justify which one is best for different scenarios. With a radical shift of paradigms, learn about MongoDB and Redis to get an understanding of the differences in behaviors and requirements for non-relational databases.
Overview
Syllabus
- Intro to DBMS: Relational and Non-Relational Databases
- Get introduced to database management systems, as well as learning the difference between relational and non-relational databases.
- Normalizing Data
- Find out about the different forms of normalized data for optimizing database storage.
- Data Definition Language (DDL)
- Learn about the data definition language, such as creating tables and different data types.
- Data Manipulation Language (DML)
- Dive into the data manipulation language in order to alter existing tables and data.
- Consistency with Constraints
- Find out how to keep consistency amongst your data by adding constraints.
- Performance with Indexes
- Maximize your database performance by using indexes when and where appropriate.
- Intro to Non-Relational Databases
- With your relational database skills in hand, you’re ready for a look into the other side of data, with non-relational databases.
- Udiddit, A Social News Aggregator
- Investigate a poorly designed database for Udiddit, a social news aggregator. You’ll design a new, normalized and performant database and migrate over data from the previous database.
Taught by
Ziad Saab
