Ljubljana, Slovenia

Business Analytics: Management and Technologies

online course
when 5 July 2021 - 23 July 2021
language English
duration 3 weeks
credits 7 EC
fee EUR 500

Today, data is considered the new oil and the most valuable commodity of the digital age. Firms adopting data driven decision making have achieved significant productivity gains over competitors. Decision makers are using more computerized tools to support their work. Even consumers are using analytics tools, either directly or indirectly, to make decisions on routine activities such as shopping, health/healthcare, travel, and entertainment. The field of business intelligence and business analytics has evolved rapidly to become more focused on innovative applications for extracting knowledge and insight from data streams. New applications turn up daily in healthcare, sports, travel, entertainment, supply-chain management, utilities, and virtually every industry imaginable. The term analytics has become mainstream. In industry, the hottest job these days is the Data Scientist. Data scientists combine technical and statistical skills, analytical thinking, and business insight. One of the complaints about the data scientists trained in computer science departments is that they are “just technical”; understanding algorithms well, but lacking important skills in problem formulation, evaluation, and analysis. On the other hand, those trained in business schools tend to have underdeveloped technical skills. This course will cover aspects of both.

To help future managers use and understand analytics, this course provides students with a solid foundation of data analysis and business intelligence that is reinforced with hands on practice. This course takes a managerial approach to business Intelligence, emphasizing the applications and implementations behind the concepts. This approach allows students to understand how DA and BI works in a way that will help them adopt these technologies in future managerial roles. Real world cases will be covered that present a challenge, solution, and results. Each case is paired with questions for students to dig into the details and think critically about the case.

Course leader

Popovic Ales, NEOMA Business School, France

Target group

Master students and Bachelor students in their final year of study

Course aim

- Understand the need for computerized, support of managerial decision making, recognize the evolution of such computerized support to the current state – analytics/data science, understand the different types of analytics and see selected applications, understand the analytics ecosystem to identify various key players and career opportunities;
- Understand the nature of data as it relates to business intelligence (BI) and analytics, learn the methods used to make real-world data analytics ready, describe statistical modeling and its relationship to business analytics, learn about descriptive and inferential statistics, define business reporting, and understand its historical evolution, understand the importance of data/information visualization, learn different types of visualization techniques, appreciate the value that visual analytics, brings to business analytics, know the capabilities and limitations of dashboards;
- Understand the basic definitions and concepts of data warehousing, understand data warehousing architectures, describe the processes used in developing and managing data warehouses, explain data warehousing operations, explain the role of data warehouses in decision support, explain data integration and the extraction, transformation, and load (ETL) processes, understand the essence of
business performance management;
- Understand the applications of prescriptive analytics techniques in combination with reporting and predictive analytics, understand the basic concepts of analytical decision modeling, understand the concepts of analytical models for selected decision problems, including linear programming and simulation models for decision support, describe how spreadsheets can be used for analytical modeling and solutions, explain the basic concepts of optimization and when to use them, describe how to structure a linear programming model,
explain what is meant by sensitivity analysis, what-if analysis, and goal seeking, understand the concepts and applications of different types of simulation;
- Define data mining as an enabling technology for business analytics, understand the objectives and benefits of data mining, become familiar with the wide range of applications of data mining, learn the standardized data mining processes, learn different methods and algorithms of data mining;
- Describe text analytics and understand the need for text mining, differentiate among text analytics, text mining, and data mining, understand the different application areas for text mining, know the process of carrying out a text mining project, appreciate the different methods to introduce structure to text-based data, describe sentiment analysis, develop familiarity with popular applications
of sentiment analysis, learn the common methods for sentiment analysis;
- Learn what Big Data is and how it is changing the world of analytics, understand the motivation for and business drivers of Big Data analytics, become familiar with the wide range of enabling technologies;
- Explore some of the emerging technologies that may impact analytics, BI, and decision support.

Credits info

7 EC
Certificate of Attendance: awarded at the end of the summer school to all students who complete the 3-week programme.
Transcript of records (with credits and grades): awarded only to students who complete all course obligations and pass the final examination.

Fee info

EUR 500: What is included?

- tuition for online synchronous lectures and access to all course materials/software/platforms;
- non-refundable registration/administrative fee,
- Certificate of Attendance and Transcript of records;
- professional administrative support before, during and after the programme;
- some organized activities during the programme to foster the intercultural experience.