47C58600 - Data-Driven Decision Making, Lecture, 29.5.2023-1.9.2023

Inträde för gästanvändare
Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Business data analytics is at the intersection of business and technology. Companies gather a large  amount of data to aid business governance. Data is being captured everywhere we look and is used in  practically every business process, from product development and advertising to hiring. Data and  algorithms have a tendency to outperform human intuition in a wide variety of circumstances. In this  course you will learn the basics of operational and analytical databases, data mining, and data  visualization, which will enable you to identify different data resources, differentiate between numbers  and numbers that matter, and make data-supported business decisions 

Credits: 6

Schedule: 29.05.2023 - 01.09.2023

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Victor de Bruin

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    Operational Databases 

    Entity Relationship Modeling (ER Modeling) 

    Relational Modeling 

    Data Querying 

    Data Quality 

    Data Warehouses 

    Dimensional Modeling (Star Schemas) 

    Data Visualization 

    Data Mining 

    Big Data 

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Class participation
    Quizzes
    Individual assignments
    Group project

Workload

  • valid for whole curriculum period:

    Total 160 h (6 ECTS)
    Lectures 42 h
    Independent and team work: 118 h
    Compulsory attendance, max. 3 absences

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Summer
    2023-2024 Summer

    Enrollment :

    Registration for courses will take place on Sisu (sisu.aalto.fi). Course available as a part of the Information & Service Business track of the Information Technology Program. Application to the program through itp.aalto.fi.

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Aalto University Code of Academic Integrity and Handling Violations Thereof