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Module 40-Tableau-IE Big Data Literacy with Tableau

Faculty

Responsible for the module

Cycle (beginning)

Credit points and duration

10 credit points

The information on the module duration can be found in the study programs in which the module is used.

Competencies

“Big data” is playing an increasingly important role in the increasingly digitalized society, creating new professions and new fields of activity and requirements in existing professions. The participants of this course will acquire an understanding of Big Data and specific skills for working with it using the example of the established Tableau program.
The students acquire the professional competence to combine different data sources for the analysis. You will gain the ability to use Tableau Prep to cleanse, structure, and link data for analysis. You will perform visual analysis in Tableau and learn which different types of mapping are best for problems and how to create them.
Another skill to be acquired is the ability to create cartographic images. The participants calculate variables and filter the data. You design interactive images to communicate your results more effectively and create dashboards and stories. Students learn how to publish their results on Tableau Public. You develop a Tableau story to present the results of a question you created.
After participating in the course, students will be able to visually analyze large amounts of data using Tableau and present the results using dashboards and stories.

Course content

• Structure and user interface of Tableau Desktop and Tableau Prep
• Menus and editors
• Connection to data sources
• Prepare data in Tableau Prep
• Visual analysis of data
• Image types and creation of images
• Creation of cartographic images
• Design of interactive images
• Calculations and filters
• Create dashboards and stories

Recommended previous knowledge

Basic knowledge of Microsoft Excel is advantageous for this module, but not absolutely necessary.

necessary requirements

Explanation of the module elements

The module consists of an event with self-study units in the LernraumPlus as well as two face-to-face appointments. The self-study units contain tutorial videos, recap tasks, quizzes and exercises, as well as all of the files used in the videos.

Module structure: 1 SL, 1 uPr1

Events

titleArtRotationWorkload (contact time + self-study)LP2
Big data literacy with Tableau

The course consists of 10 online modules in the LernraumPlus, each with approx. 1-hour videos. For each learning unit there are extensive tasks to recapitulate the work steps of the video (80h workload), quizzes to check the learning progress (9h workload) and so-called challenges for each learning unit (40h workload). This is a more complex task on the topic of the learning unit. A workload of 51 hours is set for the overall reflection of the topic through literature and online research.
At the beginning of the semester there is a face-to-face event with information about the course and an introduction to implementation in the LernraumPlus. At the end there is another face-to-face event to prepare for the final presentation.

Guided self-study WiSe & SoSe240h ​​(24 + 216) 8 [SL] [Pr]

Academic achievements

exams

Organizational assignmentArtweightingWorkloadLP2
Big Data Literacy with Tableau (guided self-study)

By the end of the semester, the students create a more complex tableau presentation (so-called story) with 6 to 8 dashboards with self-researched data and upload it to the delivery folder of the LernraumPlus both as a tableau file (* .twbx) and in parallel as a PDF . They describe their approach in a text of approx. 3 pages and upload them to the submission folder for examinations of the LernraumPlus. The examination is ungraded. The criteria for acceptance or rejection are based on the competencies developed in this module and are announced in a document in the LernraumPlus and explained in the second face-to-face event.

presentation ungraded 60h 2

More information

The course participants will be able to use a specific platform (Tableau Online) to work with data and will receive student licenses for Tableau Desktop and Tableau Prep. You will be able to use these licenses until you finish your studies.

The module is used in these courses of study:

Automatic completeness check

An automatic completeness check can be carried out by the system in this module.

Legend

1
The module structure describes the exams and course work required to complete the module.
2
LP is the abbreviation for credit points.
3
The numbers in this column are the semesters in which the start of the module is recommended. Depending on the individual study planning, completely different study courses are possible and useful.
4
Explanations of the binding: "Compulsory" means: This module must be completed in the course of the course; "Elective" means: This module belongs to a number of modules from which a choice can be made under certain conditions. The "Subject-Specific Regulations" regulate more details (see menu on the right).
SL
Academic achievement
Pr
exam
bPr
Number of graded module (sub) exams
uPr
Number of ungraded module (part) exams
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