Studies in Big Data and Analytics in Business and Management

On the one hand, the programme will provide participants with a thorough understanding of the key technical aspects of big data and analytics technologies. On the other hand, the programme focuses on business and management applications, substantiating how big data and analytics techniques can create business value and providing insights on how to manage big data and analytics projects and teams. As such, this inherent interdisciplinary focus is the unique selling point of our programme.

The programme is founded on the lecturers' experience of advising and collaborating with industry and governmental organizations in Belgium and abroad. After successful completion of the programme, participants will be up-to-date with the latest developments related to big data and analytics. Furthermore, they will understand how to apply these techniques in practice and create value for their organization. The programme is relevant for participants from different sectors: business (marketing, finance, auditing, HR, CRM, consulting), government (fraud, open data, process optimization), healthcare (care flows, data-driven diagnostics), media (sentiment analysis, opinion mining, usability analytics), education (evidence-based performance management, learning analytics), energy & transport (smart data).

Our programme also offers extensive network opportunities for participants, enabled by the provisioning of full catering (coffee breaks + sandwich dinners) on every session day, plus two networking dinners on the first and final session day.

Participants should have obtained an academic or professional bachelor's degree. The programme aims at participants with a minimum of one year of practical experience in the area of business analysis, data analytics, data analysis, statistics, data management, project management, etc. This criterion is strict: if you don't have sufficient work experience, you will not be admitted. Applications are evaluated by the academic coordinator based on the requested information in the registration form. The goal is to build a homogeneous participant group to foster discussions and share experiences.

Example target profiles are: chief data officer, chief analytics officer, compliance and risk officers and managers, data architects, data project managers, junior industry data scientists, data-related programme managers, business analysts, product managers, IT project managers, etc. However, this list is not exhaustive!

1. Fundamentals of Data Analytics

• Predictive analytics: supervised learning techniques
• Descriptive analytics: unsupervised learning techniques
• The analytics process model: data collection and preprocessing, model construction and evaluation

2. Analytics Business Applications

• Marketing analytics
• Recommender systems
• Insurance analytics
• Text mining
• Web mining
• Social network analytics
• Fraud detection
• Decision mining

3. Big Data Technologies

• Hadoop and its ecosystem
• The MapReduce paradigm
• Big data analytics using Apache Spark and H2O
• NoSQL databases
• Graph databases

4. Process Analytics

• Process discovery
• Event log data
• Conformance checking
• Predictive process mining
• Sequence mining
• Case studies

5. Managing Big Data & Analytics Projects and Teams

• Model deployment
• Valorization of analytics
• Analytics and IT integration
• Data quality and security
• Data privacy and compliance
• Ethics and privacy

Optional hands-on exercises will be provided through a DataCamp classroom.

Evaluation and diploma

To obtain the postgraduate certificate 'Postgraduate Studies in Big Data & Analytics in Business and Management', awarded by KU Leuven and signed by the Rector, the participant will need to write a dissertation about a case study in the field of big data analytics, along with an oral defence of the case study.

The case study should performed in the participant's organization and deal with the (potential) application of big data and analytics techniques in practice. Participants will be actively guided by one of the lecturers. We will use three possible timelines for the dissertation, with submission deadlines available end of April 2025, end of June 2025, or end of August 2025. The dissertation will be complemented by an oral presentation to be scheduled in the week following the submission deadline.

Sessions are scheduled on Fridays from 13.30 until 21.00 on the following dates:

• 4 October 2024
• 11 October 2024
• 18 October 2024
• 25 October 2024
• 8 November 2024
• 15 November 2024
• 22 November 2024
• 29 November 2024
• 6 December 2024
• 13 December 2024

Location: Faculty of Economics and Business - Naamsestraat 69, 3000 Leuven (view on Google Maps)