Study Guide

Objective

The student understands how managers use analytics to formulate and solve business problems. The student recognizes the processes needed to generate, collect, analyze and report business data. The student has gained hands-on experience in using analytics software. The student is familiar with the most frequently employed analytics platforms.

Content

- Managerial perspectives on analytics
- Descriptive, diagnostic, predictive and prescriptive analytics.
- Data sources and mining
- Data preparation, processing and visualization
- KPI’s and dashboards.

Assignment outline: Student will deepen and take responsibility of one's own learning curve in the field of business analytics by given materials, lectures, hands-on exercises and by external sources. Student will demonstrate one's learning process with learning journal and via other individual assignments.

Location and time

There will 5 on-campus meetings:
10.3., 24.3., 14.4., 28.4., 19.5. all held at the same time, 9-12 am.

Teaching methods

This is an ONLINE course. (If you are interested in a similar face-to-face course, please check another implementation held at about the same time, "LY00EC64-3003 Applied Business Analytics").
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Learning outcomes of the course:

The student understands how managers use analytics to formulate and solve business problems. The student recognizes the processes needed to generate, collect, analyze and report business data. The student has gained hands-on experience in using analytics software. The student is familiar with the most frequently employed analytics platforms.

Exam schedules

IMPORTANT! This course includes 5 assignments which should be delivered strictly ON TIME.
The course instructor does NOT consider any assignments/ submissions which are delayed.

NOTE! Assignment 1 should be delivered even before the course starts, and also strictly ON TIME.

You can check the due dates for all assignments in OMA, in the assignment slots.

Student workload

The course workload is 5 ECTS, which is appx. 130h of work (including classes, readings, assignments, and self-study).

Content scheduling

Course contents:

- Managerial perspectives on analytics
- Descriptive, diagnostic, predictive and prescriptive analytics.
- Data sources and mining
- Data preparation, processing and visualization
- KPI’s and dashboards.

Further information

The course is held in English. The course instructor is Niklas Visanko (niklas.visanko@metropolia.fi).

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

Sufficient performance: has completed basic requirements to pass the course and has made an attempt to apply and articulate concepts and information both verbally and in writing but has not made enough effort overall. The student has demonstrated little effort, interest and motivation for individual or team activities / assignments and the output is rather weak.

Assessment criteria, good (3)

Good overall performance: can apply and articulate concepts and information well both verbally and in writing, certain areas of individual or team output require further attention; shows appropriate level of interest and motivation in individual and team activities. Good presentation delivery and analysis.

Assessment criteria, excellent (5)

Excellent performance in all elements of the course: shows interest and motivation in individual and team activities and assignments, fully applies and clearly articulates concepts and information both verbally and in writing. The student is able to support his/her argument with references to the recommended reading and lecture content. Excellent presentation delivery and analysis.

Assessment criteria, approved/failed

Sufficient performance: has completed basic requirements to pass the course and has made an attempt to apply and articulate concepts and information both verbally and in writing but has not made enough effort overall. The student has demonstrated little effort, interest and motivation for individual or team activities / assignments and the output is rather weak.

Assessment methods and criteria

The course is assessed on the 0 (failed) – 5 (excellent) grading scale.

Approved / Failed

Sufficient performance: has completed basic requirements to pass the course and has made an attempt to apply and articulate concepts and information both verbally and in writing but has not made enough effort overall. The student has demonstrated little effort, interest and motivation for individual or team activities / assignments and the output is rather weak.

Satisfactory

Sufficient performance: has completed basic requirements to pass the course and has made an attempt to apply and articulate concepts and information both verbally and in writing but has not made enough effort overall. The student has demonstrated little effort, interest and motivation for individual or team activities / assignments and the output is rather weak.

Good

Good overall performance: can apply and articulate concepts and information well both verbally and in writing, certain areas of individual or team output require further attention; shows appropriate level of interest and motivation in individual and team activities. Good presentation delivery and analysis.

Excellent

Excellent performance in all elements of the course: shows interest and motivation in individual and team activities and assignments, fully applies and clearly articulates concepts and information both verbally and in writing. The student is able to support his/her argument with references to the recommended reading and lecture content. Excellent presentation, delivery and analysis.

Prerequisites

Completed Higher Education Degree

Further information

The language of tuition is English. The class policy regarding late assignments is that students are deducted 10% per day for late submissions. Please note that the lecturer does not grant extension requests in advance of the assignment deadlines. Students that have a doctor's note excusing an absence or late assignment may wish to discuss the matter directly with the lecturer.