Energy Business FT
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Data Analysis

level of course unit


Learning outcomes of course unit

Students are familiar with the structure of mass data in Energy Business. They are also able to use software for the execution and evaluation of data analyses and prepare graphic assessments. They consolidate the energy-management concepts of energy and power.

prerequisites and co-requisites

Energy-Efficient Building, Internet Technologies, Introduction of Data Science

course contents

Introduction to used hardware and software. Acquiring of data series for electrical production and consumption devices. Data preparation by means of software. Graphic illustration of the load profile and assorted duration curve. Creation of the laboratory report and documentation

recommended or required reading

Grus J.: Einführung in Data Science: Grundprinzipien der Datenanalyse mit Python, 1. Auflage, O’Reilly Media, 2016
Fasel D.; Meier A.: Big Data: Grundlagen, Systeme und Nutzungspotentiale, 1. Auflage, Springer Verlag, 2016
Runkler T.A.: Data Analytics: Models and Algorithms for Intelligent Data Analysis, 2. Auflage, Springer Verlag, 2016

assessment methods and criteria

Paper, presentation,

language of instruction


number of ECTS credits allocated


planned learning activities and teaching methods


semester/trimester when the course unit is delivered


name of lecturer(s)


year of study


recommended optional program components

Not specified

course unit code


type of course unit

Compulsory lecture

mode of delivery


work placement(s)

Not applicable