Study Guide

Objective

As a Student, you
- know and are able to evaluate the significance of data for the organizations (eg. data collection, management and utilizing in operations, processes, tasks, decision making).
- know the basics and special features of traditional data management and big data management.
- know and are able to apply the principles, design, implementation methods and technologies of data integration and data warehousing.
- are able to produce a technical solution for the ETL / ELT process to transfer and integrate of data from different data sources.
- are familiar with the importance of API-interfaces and various data storage and formats in data storage and other data management applications.
- understand the basics of data quality management and is able to apply them.
- understand the importance of automation in data management.
- understand the importance of data security in data management.

Content

- Importance of data for organizations
- Data management and utilization; traditional and big data, applications (operating systems, data warehousing, visualization, analytics, automation, machine learning)
- Data engineering, data management solutions, platforms, technologies and processes (on-premises-cloud-hybrid, Databases, data Warehouse - data warehouses, data lakes, ETL, ELT, OLAP, system independent solutions)
- APIs / interfaces and formats; mm. transfer files: CSV, XML, JSON, database interfaces: SQL, noSQL, data warehouses, web services, system-specific APIs.
- Data processing and transformations
- Data quality management
- Processes, automation and data management
- System-independent data management solutions.
- Data management automation needs and capabilities.
- Specific security issues related to data management.

Evaluation scale

H-5