Big Data Management and Analytics

Description:

The module "Big Data Management and Analytics" consists of the two courses "Big Data Management" and "Big Data Analytics".

The certificate program gives an overview of current challenges, characteristics and applications of Big Data from a scientific perspective. Based on many application examples, a high level of practical relevance is created. In the certificate program, various database technologies for Big Data are presented. Batch and stream processing of Big Data as well as data mining and graphical data are addressed.

Learning Objectives: Big Data Management

M1: Introduction to Big Data (characteristics, occurrence, enabling technologies for Big Data, Big Data as a business)

M2: MapReduce (basics, Error Handling, examples)

M3: Distributed Big Data (CAP theorem, ACID and BASE, NoSQL datastores)

M4: NoSQL datastores (Google's BigTable, Amazon's DynamoDB)

M5: Big Data Processing with Spark (History and Basics, Resilient Distributed Datasets)

Learning Objectives: Big Data Analytics

A1: Frequent Itemsets and Association Rules (e.g. A-priori Algorithm, PCY Algorithm)

A2: Finding similar items (e.g. min-hashing, locality-sensitive hashing)

A3: Community Detection (e.g. social network analysis with GraphAnalytics, Girvan-Newmann algorithm).

A4: Web link analysis (e.g., PageRank Algorithm, Power Interation Method).

A5: Data streaming (e.g. Spark streaming, Apache Storm)

Upon successful completion of this module, students understand the challenges of management and of the analysis of vast amounts of data and data streams in modern data-intensive applications and master IT-based solution approaches.

Course fee: 370€

This certificate course will take place in the winter semester 2024/2025!

This certificate course can be credited to the master program "Intercultural Leadership and Technology".

Prof. Dr. Sven Hartmann