Data Analytics Infrastructure

Code

IT-DAI1

Version

3.0

Offered by

ICT Engineering

ECTS

Prerequisites

Completed the 2nd semester Software Engineering course “IT-DBS1” or a similar course (fundamentals of database systems)

Main purpose

The course introduces the student to selected topics in the design and implementation of infrastructure to support data analytics.
Within this area, the course will introduce students to different tools and techniques for data acquisition, cleansing and integration. The students will also be introduced to data modelling for analytics and basic visualization.

Knowledge

Having completed this course, students should be able to describe basic techniques within the field, and argue the choice and applicability of these for different use scenarios.

This includes:
• Application of analytical data processing, and differences to transactional processing
• Types of analytical data processing, such as reporting and visualization
• Sources of data for analytical processing
• Server and locally hosted platforms for data storage and analytical processing
• Modelling techniques for designing data models for integration of multi-source data, including structured, semi-structured and unstructured data, and for modelling time-variant data/history
• Design of systems for data acquisition, validating and cleansing data, integration and publishing of data.

Skills

Having completed this course, students should be able to:
• Design and implement data models for integrating multi-source data, including dimensional data modelling, for structured and semi structured data
• Design and implement data models for time-variant data
• Design, implement and test systems for data acquisition, validation, integration and delivery from multiple sources and platforms
• Design, implement and test basic descriptive statistical analysis on integrated data
• Design, implement and test basic visualizations and graphs of data and analysis results.
• Give relevant peer feedback on handins and exercises throughout the semester

Competences

Having completed this course, students should be able to
• Discuss and argue pros, cons and trade-offs of choices
• Use basic statistics and visualization to find and explain patterns of information in data
• Evaluate and act upon peer feedback

Topics

Teaching methods and study activities

Details to be determined.

Resources

Evaluation

Examination

Exam prerequisites:
None

Type of exam:
Individual oral exam, 20 minutes without preparation.
Exam is based upon four course assignments handed in before deadline.
Internal assessment

Tools allowed:
N/A

Re-exam:
Same as the ordinary exam

Grading criteria

Grading according to the Danish 7-point-scale.

Additional information

Responsible

Knud Erik Rasmussen (KERA)

Valid from

01-08-2023 00:00:00