1. Explain the role of Business Analytics in supporting organizational decision-making.
2. Distinguish between descriptive, predictive, and prescriptive analytics and identify suitable business applications for each.
3. Prepare, summarize, and visualize business data using basic analytical techniques and tools.
4. Apply descriptive, predictive, and prescriptive analytics techniques to business cases.
5. Interpret analytical results and translate them into clear managerial recommendations.
6. Critically reflect on the assumptions,\nlimitations, and responsible use of analytics.","fi":"1. Explain the role of Business Analytics in supporting organizational decision-making.
2. Distinguish between descriptive, predictive, and prescriptive analytics and identify suitable business applications for each.
3. Prepare, summarize, and visualize business data using basic analytical techniques and tools.
4. Apply descriptive, predictive, and prescriptive analytics techniques to business cases.
5. Interpret analytical results and translate them into clear managerial recommendations.
6. Critically reflect on the assumptions,\nlimitations, and responsible use of analytics."},"tweetText":null,"content":{"en":"This course introduces BSc students to the foundations and practical applications of Business Analytics. The course focuses on how organizations use data, analytical methods, and decision models to understand business performance, predict future outcomes, and support managerial decision-making.
The course is designed as a self-study-oriented 3 ECTS course, combining short video lectures, quizzes, personal reflection, applied fictional cases, and a final report.
The course has five main modules.
1. Foundations of Business Analytics.
2. Data Preparation and Descriptive Analytics
3. Predictive Analytics and Forecasting
4. Prescriptive Analytics and Decision Support
5. Communicating Analytical Results
The course can be completed using Microsoft\nExcel. Other tools can be used optionally.The course is completed through participation and completion of required assignments.
Assessment is based on the extent to which students demonstrate understanding of key Business Analytics concepts and are able to apply them to practical business cases
This course introduces BSc students to the foundations and practical applications of Business Analytics. The course focuses on how organizations use data, analytical methods, and decision models to understand business performance, predict future outcomes, and support managerial decision-making.
The course is designed as a self-study-oriented 3 ECTS course, combining short video lectures, quizzes, personal reflection, applied fictional cases, and a final report.
The course has five main modules.
1. Foundations of Business Analytics.
2. Data Preparation and Descriptive Analytics
3. Predictive Analytics and Forecasting
4. Prescriptive Analytics and Decision Support
5. Communicating Analytical Results
The course can be completed using Microsoft\nExcel. Other tools can be used optionally.The course is completed through participation and completion of required assignments.
Assessment is based on the extent to which students demonstrate understanding of key Business Analytics concepts and are able to apply them to practical business cases
No prior quantitative experience is required. The course is designed for BSc students who are new to Business Analytics or who have limited prior experience with applied data analysis.
Basic familiarity with Microsoft Excel and\nintroductory knowledge of statistics are recommended but not required.","fi":"No prior quantitative experience is required. The course is designed for BSc students who are new to Business Analytics or who have limited prior experience with applied data analysis.
Basic familiarity with Microsoft Excel and\nintroductory knowledge of statistics are recommended but not required."},"compulsoryFormalPrerequisites":[],"recommendedFormalPrerequisites":[],"literature":[],"learningMaterial":{"en":"Articles, book chapters, Excel tutorials, and other learning materials provided by the lecturer.
","fi":"Articles, book chapters, Excel tutorials, and other learning materials provided by the lecturer.
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