Data Management SS2020
(INF.01017UF VO, INF.02018UF KU, 706.010 VU)

This course covers, primarily from a user perspective, foundations of database systems in terms of design and data modeling, query languages and APIs, physical design, query and transaction processing, as well as foundations of modern, distributed data management and analysis. Thus, the course consists of two main parts: (a) database systems, and (b) modern data management. Due to different course types and ECTS schemes, INF.01017UF includes lectures of parts (a) and (b), INF.02018UF includes exercises of parts (a) and (b), while 706.010 includes lectures and exercises of part (a) only.

Lectures

In detail, the course covers the following topics, which also reflects the course calendar. All slides will be made available prior to the individual lectures.

A: Database Systems

  • 01 Introduction and Overview [Mar 02, pdf, pptx]
  • 02 Conceptual Architecture and Design [Mar 09, pdf, pptx]
  • 03 Data Models and Normalization [Mar 16, pdf, pptx]
  • 04 Relational Algebra and Tuple Calculus [Mar 23, pdf, pptx]
  • 05 Query Languages (SQL, XML, JSON) [Mar 30, pdf, pptx]
  • 06 APIs (ODBC, JDBC, OR frameworks) [Apr 20]
  • 07 Physical Design and Tuning [Apr 27]
  • 08 Query Processing [May 04]
  • 09 Transaction Processing and Concurrency [May 11]

B: Modern Data Management

  • 10 NoSQL (key-value, document, graph) [May 18]
  • 11 Distributed file systems and object storage [May 25]
  • 12 Data-parallel computation (MapReduce, Spark) [May 25]
  • 13 Data stream processing systems [Jun 08]
  • 14 Q&A and exam preparation [Jun 15]


Exercises

The lectures are accompanied by mandatory exercises for gaining practical experience. This year's application domain is DBLP publications (dataset).

A: Database Systems

  • Exercise 1: Data Modeling [published Jan 14, deadline Jan 31]
  • Exercise 2: Query Languages and APIs [published Apr 7, deadline Apr 28]
  • Exercise 3: Tuning and Transactions [published Apr 28, deadline May 19]

B: Modern Data Management

  • Exercise 4: Large-Scale Data Analysis [published May 26, deadline Jun 16]


Organization

  • Lecturer: Univ.-Prof. Dr.-Ing. Matthias Boehm, M.Tech. Arnab Phani, ISDS
  • Teaching Assistants: Dardan Dermaku, Alina Herderich, Paul Mirtl, Oliver Nikolic, Olga Ovcharenko, Melanie Willfurth
  • Final written exams: TBD
  • Grading 706.010: 30% exercises (mandatory), 70% final exam
  • Exercises: passed, if total points ≥ 50% and all submitted