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Postgraduate Studies

Big Data & Analytics in Business and Management

6 Oct 2023 - 15 Dec 2023

Bridge the gap between technical concepts and business applications of big data and analytics techniques.

Practical information:

6 Oct 2023 - 15 Dec 2023
Leuven
English
Target audience: Chief Data Officers, Analytics Officers, data architects, data scientists, business analysts, and managers, etc.

Want to register?

  • Register until: 15 Sep 2023
  • Prerequisites: academic or professional bachelor degree with a min. of one year of practical experience in business analysis, data analytics, data anlysis, statistics, data management, project management...
  • Price: €5500
More info & registration ⇗

Georganiseerd door:

Aim of the programme

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).

Programme Structure

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