Data Analytics Insight

As a decision maker, you need to use data to take the right direction, ask the right questions, and eventually opt for solutions that fit your business. But how to best exploit the potential offered by Big Data, Business Analytics, Datamining, Data Warehousing, Artificial Intelligence etc? This course will take the buzz out of these buzzwords and offer you research based insight into the power and limitations of data analytics.

The course is built around two complementary modules:

A. Analytics as a Service. In this module we start from the observation that public clouds provide a wide range of services that can be combined to build advanced analytics solutions. These services include (i) data platforms for storing, managing and processing data at rest as well as streaming data, and (ii) analytics services based on machine learning, data mining or streaming analytics. We will review the architectural principles that underlie advanced analytics solutions based on such services. We will also discuss in depth issues related to non-functional requirements such as performance and security. We will also discuss the differences between big data analytics and business intelligence.

B. Inside Analytics. In this module, we will review the processes that make it possible to extract insights from data. We will rely on concrete examples and real data sets to analyse successive analytics stages: data exploration, data preparation, data mining and data visualisation. We will illustrate the most common problems encountered in each stage and we will review the fundamental principles that underlie most solutions.

The course enables you to:

  • Analyse the basic components of a modern data analytics IT infrastructure
  • Evaluate infrastructure designs proposed by your team or suppliers
  • Decompose the computation processes of data driven analytics
  • Identify strong predictors of business analytics queries
  • Avoid pitfalls of datamining and business intelligence
  • Understand how datamining algorithms go beyond classical statistics by using data structures such as trees and graphs

The course helps your business by giving you the foundation for informed decisions:

  • Organize your analytics team and hire people with competences that fit your needs
  • Choose the right technical solutions from your team and suppliers
  • Set a roadmap for your team that achieves your analytics business goals
  • Avoid costly setbacks of buzzword right, but content wrong solutions for your business


The course is aimed at decision makers that graduated before education in business analytics existed but now find themselves responsible for a business intelligence team or responsible for building up such a team and/or establishing an IT infrastructure for analysis of big data in the company.

The objective of the course is to give an executive introduction to the essence of business analytics without the fuzz and buzzwords, so you can be comfortable at setting a strategy for your company and carry the responsibilities that goes with it. The course is not for technical experts already with an analytics degree wanting to know the latest news. It is for their managers.


Philippe Bonnet

Philippe Bonnet is professor at the IT University of Copenhagen. Philippe is an experimental computer scientist with a background in database management. For twenty years, he has explored the design, implementation and evaluation of database systems in the context of successive generations of computer classes, including sensor networks and most recently high performance storage systems. Philippe is teaching big data management courses for both software and business students at the IT University.

philippe bonnet

Rune Møller Jensen

Rune Møller Jensen is associate professor at the IT University of Copenhagen. He is conducting research on optimization algorithms for container vessel stowage planning and service network design. He has carried out data analytics research collaborations with companies in logistics, health care and retail. He is the founder of Optivation which is a business analytics consultancy company with 10 employees working for Maersk Line and providing the optimization engine for the stowage planning tool StowMan that today has 62% of the world market.

Rune Møller Jensen

Der er stor hype om, hvad kunstig intelligens kan gøre for erhvervslivet, men ifølge to forskere på IT-Universitetet er begrebet overhypet. De mener, at hypen er farlig, fordi den giver indtryk af, at man kan meget mere med data, end man i virkeligheden kan. Konsekvenser kan være fejlagtige investeringer i umoden teknologi eller menneskelige omkostninger, såsom forkerte fyringer.

- Kunstig intelligens bliver ofte italesat, som om man som virksomhed er fortabt, hvis man ikke investerer i det, men der er så meget ævl og mystik omkring begrebet. Man tror, at man kan det hele med kunstig intelligens, men der er rigtig mange begrænsninger, og mange vigtige spørgsmål at stille, før man overhovedet går i gang, understreger Rune Møller Jensen, som er lektor på IT-Universitetet og forsker i algoritmer til optimering inden for en række områder.

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Practical info

Time and place
The course is a one-day course and will take place on the 31 October 2017.

Admittance and registration

Courses under ITU Professional Courses do not link to other educations at the IT University and do not release ECTS-points. Therefore there are no requirements when registrating for courses offered by ITU Professional Courses.

You can register for the course by sending an e-mail to Write your name, workplace, name of the course, and a few lines about your educational background and work experience. When we have received your registration, we will send you a receipt.

You can register until the day the course starts.

Limited number of seats
The number seats on this course is limited. Seats are distributed according to the first-come-first-served principle.