5409651: C19 Data Management (CPE)

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Semester:WS 22/23
Type:Module
ECTS-Credits:3.0
Scheduled in semester:1
Semester Hours per Week / Contact Hours:30.0 L / 22.5 h
Self-directed study time:67.5 h

Module coordination/Lecturers

Curricula

Master's degree programme in Information Systems (01.09.2019)
Master's degree programme in Entrepreneurship and Management (01.09.2020)
Master's degree programme in Finance (01.09.2020)

Description

Data Management covers the modern data-management cycle, from the collection of data from diverse sources to the preparation of data for data-driven applications. Students learn how to handle various data formats, how to assess and improve data quality, and how to store and process data using SQL, NoSQL, and Hadoop technologies. The course covers eight primary topics:

  • Modern data-management requirements
  • Database system architecture
  • Diagnosing and handling data quality problems
  • Relational databases (SQL)
  • Hands-on labs with MySQL
  • Concurrency control techniques
  • NoSQL databases (e.g., MongoDB)
  • Apache Hadoop (HDFS, MapReduce)

Learning Outcomes

After successful completion of the course, students will:

  • understand the basic concepts and methods of modern data management
  • be able to collect and prepare data for data-driven applications
  • be able to select and apply appropriate technologies for building data-driven applications

Qualifications

Lectures Method

  • The module involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
  • The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.

Literature

Compulsory reading:

  • Elmasri, R., & Navathe, S.B. (2016). Fundamentals of Database Systems, 7th edition. New York: Pearson Education
  • Harrison, G. (2015). Next Generation Databases – NoSQL, NewSQL, and Big Data. California: Apress Media.

Exam Modalities

Written exam (60min)