Data Management and Analytics
Assuming familiarity with basic data management and storage techniques (such as ER models and SQL), which if needed will be repeated in a bridging course, we will in this master class we will focus on more advanced
databases, storage and data management techniques, analytical queries and how to make such tasks scale with big data (i.e. high volume, high velocity or highly heterogeneous data. To this end, we will review traditional indexing techniques and methods to deal with concurrent data access and discuss trands in Data Management and Analytics. Moreover, we will recap Data Analytics Techniques and discuss how these can be scaled.
From Unstructured to Structured Data: Challenges in Data Pre-Processing, Normal Forms and "tidy" data
Indexing Techniques and Query Optimization
Modern Database Systems (NoSQL, Graph Databases, Stream Processing)
Database Access with Python and R for solving Analytical Tasks
Storing, Managing and Analyzing unstructured Data (e.g. Text Documents, Multimedia)