Business Information and Data Analysis (10cr)

Evaluation scale

H-5

Content scheduling

Online: Self study package 8.1. - 26.1.
On campus: Information and data analytics workshop 27.1 - 31.1.
On campus: BI tools in practice 3.2. - 28.2.

Objective

Tieto puuttuu

Content

Tieto puuttuu

Location and time

Self study online: 8.1. - 26.1.2020
On campus: 27.1 - 28.2.2020

Materials

1.) Loshin, David. Business Intelligence : The Savvy Manager's Guide, Elsevier Science & Technology, 2012. ProQuest Ebook Central,
https://ebookcentral-proquest-com.ez.lapinamk.fi/lib/ramklibrary-ebooks/detail.action?docID=1034439.
2.) Nussbaumer, Knaflic, Cole. Storytelling with Data : A Data Visualization Guide for Business Professionals, John Wiley & Sons, Incorporated, 2015. ProQuest Ebook Central, https://ebookcentral-proquest-com.ez.lapinamk.fi/lib/ramklibrary-ebooks/detail.action?docID=4187267.
3.) Parmenter, David. Key Performance Indicators (KPI) : Developing, Implementing, and Using Winning KPIs, John Wiley & Sons, Incorporated, 2010. ProQuest Ebook Central, https://ebookcentral-proquest-com.ez.lapinamk.fi/lib/ramklibrary-ebooks/detail.action?docID=485633.
4.) Simon, Phil. Analytics : The Agile Way, John Wiley & Sons, Incorporated, 2017. ProQuest Ebook Central, https://ebookcentral-proquest-com.ez.lapinamk.fi/lib/ramklibrary-ebooks/detail.action?docID=4901712.

Teaching methods

The course is implemented through a problem-based learning approach. Teachers supervise the learning process, lecture, guide the practical work, organize workshops, and provide coaching to the students. Invited speakers from the business life and the academic field could also be involved in coaching activities. Teaching sessions may take place on campus and online.

Employer connections

This course may include a case company selected by the university. In addition, students are able to propose your own case companies, whose business information and data analytics they would like to develop. Students must provide a free form commission agreement from their own case companies.

Completion alternatives

Before the course starts, students may propose to the course teachers their personal implementation plan. The plan must be realistic and result in verificable development in the targeted competence(s). In addition, guidance from MIGRI and student visa must be taken into account. Course teachers accept or reject student's plan based on their own consideration.

Student workload

The student's estimated workload of this implementation is 270 h and consists of following elements:
Suprvised study 60h
Teamwork 40h
Self study 170h

Assessment criteria, satisfactory (1)

Evaluation target
Satisfactory

You are able to recognize relevant and useful information and data in digital ecosystems and to apply analysis methods and tools:
You know the main principles and methods of enterprise information and data management, tools, standards and policies, including security issues and are able to use the appropriate tools to create, extract, maintain, renew and propagate business information and data.

Assessment criteria, good (3)

Evaluation target
Good

You are able to recognize relevant and useful information and data in digital ecosystems and to apply analysis methods and tools:
You are able to apply correctly the principles of enterprise information and data management. You are able to select and use the appropriate tools to create, extract, maintain, renew and propagate business information and data.

Assessment criteria, excellent (5)

Evaluation target
Excellent

You are able to recognize relevant and useful information and data in digital ecosystems and to apply analysis methods and tools:
You are able to identify, analyze and overcome challenges related to enterprise information and data management processes.

Further information

The self study package will be published in January 8th, 2020.