Intermediate Course to Business Analytics - a kick-off course for my Business Analytics exploration journey

I decided to continue my learning journey again four years after my bachelor's graduation. Back in my bachelor’s degree, I didn’t have the chance to study with so many colleagues that come from several places around the world. The most extraordinary characteristic is that my classmates acquire various expertise across industries before joining this programme.

As they have obtained diverse backgrounds, e.g. Business, Information Technology, Computer Science or Information Processing Science, it is significantly intriguing to join a course together to discuss and explore different perspectives of Business Analytics.

Business Analytics is not just about business or data analytics. What I have learned from the course is that it should be a combination of business, data science and information processing science. There are 4 pillars of Business Analytics, including data, people, process and technology which reminds me of the similar key pillars that most organizations would consider when developing their target operating models – organization, people, process and technology.

Business Analytics consists of four main types: descriptive, diagnostic, predictive and prescriptive analytics. It is remarkably interesting to discover how people can use data to perform these types of analytics. For example, a top energy company in Oulu has utilized heating data to describe and understand the heating situation across the region (descriptive analytics), predict consumption peaks, identify potential demand response opportunities and determine interventions (predictive analytics).

The Business Analytics programme also introduces management information systems, data infrastructure and existing trends of computer hardware platforms, with cloud computing acting as the most impactful movement in the industry.

As my background comes from Business, I was eager to learn how Business Analytics would be applied in real business case studies.

It was so refreshing to have interviews with several researchers and experts who have extensive experience in using data analytics across industries, e.g., gaming, social media, biometrics, tourism, media, electronics, business advisory, etc.

One of the highlights to me is the case of opinion mining – a solution that could help businesses to generate and how it is conducted through media monitoring software.

The course also provides a wide range of materials for self-reading and research. I usually come to the library to borrow these books, do reading and have discussions with my classmates on what we have learned or complete assignments. The library is one of my favourite places in the university and an ideal place to study effectively but still have fun at the same time!