Information and Data Management

In this course you will learn how to model, manage, and query information in a Database Management System (DBMS). We will focus on different data modelling techniques, but also on aspects of query processing like for example query parsing or optimization. Also transaction management is a central topic of interest. The core focus is on classic relational OLTP databases, but we will also briefly touch alternative systems like the current NewSQL-trend and systems optimized for in-memory or OLAP applications. Additionally, NoSQL systems and their respective data models will be discussed.

• Database normalization: modelling in an unambiguous and non-redundant manner in relational tables such that inconsistencies and anomalies are avoided.

• File-organization and indexing: the data structures and their associated algorithms to store data in memory and on disk, such that it can be retrieved and processed efficiently when needed.

• Query processing and optimization: the techniques that are used by a DBMS to execute certain SQL queries as efficiently as possible, taking into account how the data is stored and which indexes are present. This also covers Relational Algebra.

• Transaction management and concurrency control: the techniques that a DBMS offers to allow different users and application to operate in parallel on the same data without interfering with each other or causing inconsistencies in the data.

• NewSQL and alternative system: the systems beyond traditional relational database design space optimized for specialized requirements like extreme OLTP performance, OLAP queries, or in-memory storage.

• NoSQL and non-relational data: in the recent years, systems not relying on the relational model became popular. We will also discuss how this affects data modelling, especially with respect to document models, key-value models, wide-columnar models, but also graph models.