Foundation in Databases

Understand and interact with different types of databases (SQL, NoSQL)

Data science applications usually require a lot of data. Usually, these data are stored in databases so that they can be efficiently searched later on according to certain search criteria. Foundation in databases gives an insight into different database systems and the type of data that are managed with them. Through Foundation in databases students become database users.

Overview: Students have an overview of the most important database types. In particular, they know the differences between relational and non-relational (NoSQL) databases, can classify the databases offered on the market and name their typical areas of application.

Data Model: Students can analyse an existing data model (e.g. tables and their interaction; attributes with their data types and characteristics) and describe it using a modelling language. Knowledge of database design and possible optimizations help to understand an existing database even better and to recognize which types of accesses allow a performant data query.

RelationalDatabases (SQL): Students understand the relational data model. Starting from an existing data model, they can analyse and describe it.
Students know how to extract data from an existing relational database using standard SQL queries. They can filter, order and aggregate data, and join data from different tables. They can apply indexes. They know how to store frequently recurring queries as views. They can apply what they have learned from programming environments (e.g. Python/R) to concrete problems.

Non-Relational Databases (NoSQL): Students know the most common non-relational data models (e.g. key-value, document, graph and time series databases). Starting from an existing data model, they can analyse and describe it.
Students know how to extract data from an existing non-relational database. Accordingly, they can familiarize themselves with specialized query languages of NoSQL databases as well as data format specific query languages (XPath for XML and JSONPath for JSON). They can filter, order, and aggregate data. Students can apply what they have learned from programming environments (e.g. Python/R) to specific problems.