MSc in Business Intelligence
"Enrolling on the Business Intelligence Master's Degree at the University of Dundee has been the single most important thing I have done to further my career since starting to work in IT 18 years ago. Not only have I thoroughly enjoyed the course and project work but I have met some great people and established a strong network of friends who work in the industry. Not to mention landing a dream job as a Data Scientist with Teradata at the end of it!"
Most enterprises now collect very large quantities of data – customer data, sales data, HR data and so on. The problem is not usually collecting or storing that data, it is finding the information buried within it. Which are the most profitable customers, which the least, which products are the most profitable and so on? Business Intelligence describes a set of technologies that are used to extract information from data.
This innovative degree is delivered largely by Prof. Mark Whitehorn, the internationally recognised expert who specialises in the areas of data analysis, data modelling, data warehousing and business intelligence (BI). Another of his major areas of interest is Data Science and the School of Computing is currently creating a new Masters degree in this subject (expected to start in Jan. 2013) which will complement the existing Masters in BI. More details are available : here.
The BI world is desperately short of well-trained BI people yet a comprehensive understanding of BI is rare.
When BI skills are found, they are typically focused on the ability to drive a particular product, not on a core understanding of how data should be structured and handled for analysis. However it is this core understanding that is crucial for the design of effective BI systems and hence is the key to the MSc in Business Intelligence (BI) that is being offered by The School of computing at Dundee University.
So, for example, instead of focusing on how to drive a particular software package, the masters course is concerned with the underlying principles of BI.
• How does data differ from information?
• How can data be structured for transactions?
• How can it be structured for analysis?
• What is the difference between the Kimball and Inmon models?
• What is multi-dimensional data?
• How do we capture user’s analytical requirements?
• How can we use MDX (the analytical equivalent of SQL)?
However it is also important that students of the course will acquire practical skills and the course benefits from substantial industry involvement.
"I've always enjoyed learning new software, programming languages and methodologies, but this course has shown me that I was simply skimming the surface. It was a real inspiration to be given the time and encouragement to explore so many aspects of Business Intelligence in real depth, which I could never have done alone. The intensive weeks allowed all the students to discuss the finer points raised during the lectures. Mark's teachings were always engaging and drew upon his experience within the business world and his scientific approach to BI. The combined knowledge and experience of the students that were attracted to the course also lead to fascinating discussions and insights; I now also have a growing network of friends that I can call upon for advice or just a few drinks in the pub!!"
The BI industry is huge but, in recent years, through acquisitions it has consolidated into a relatively small number of major players – notably (in tactful alphabetical order):
This is not to imply that other vendors are unimportant, but these four taken together represent a significant proportion of the entire BI industry.
The ways in which we can perform BI is, inevitably, heavily influenced by the software that the vendors produce. As a very simple example, Teradata has produced a very fast relational database management system. BI systems designed to use Teradata consolidate data into a relational data warehouse and run analytical queries directly against that. In contrast, BI systems designed for the Microsoft BI stack tend to consist of either a relational or dimensional warehouse. However analytical queries are not usually run directly against the warehouse, instead they are run against data marts. Data marts are typically subsets of the data from the warehouse which are held by a dimensional database engine which pre aggregates the data to improve query response time.
This program is avowedly vendor neutral in the sense that it does not actively support one vendor’s approach over any other. Instead it presents the main approaches that are currently taken to BI and explains their pros and cons.
However, there is a catch. If this vendor-neutrality is taken to extremes, then the students would never see or use any vendor’s software and would be unable to perform any practical work. This is clearly unacceptable in such a practical subject. One alternative is to expose the students to software from every vendor; the problem here is that this is likely to result in a very high workload for the students just so that the program can demonstrate its vendor agnostic credentials. So the students will actively use software from at least two of the major vendors (Microsoft and Teradata); in addition the students can expect to see and hear about the products from all the major vendors.
All Students who progress to the final semester are expected to complete a major project. Examples of projects competed in the past few years include:
Unified schema for multidimensional modelling (usmm)
A supervised clustering data mining algorithm
An investigation into the incidence of acute kidney injury at nottingham university hospitals
Analytics system development for social network applications
Automatic wind turbine data analysis
Data mining of commercial insurance data
Design and implementation of a business intelligence solution to analyse hesa returns for the university of dundee
Encouraging public interaction with open nhs data via data visualisations
End to end business intelligence solution
Information extraction and data visualisation of university court minutes
Investigation of the extraction, transformation and loading of mass spectrometer raw files
Proteomics bi system
For more information on Data Science and Business Intelligence at the School of Computing see: Dundee Data Science Center
Format of course
The course runs from 14 January 2013 until 13 January 2014.
The programme consists of three taught modules in semester 1 (January – March), three taught modules in semester 2 (April – June) and a research project in semester 3 (July – December). See below for more details of the module contents. The programme will be available for both full time attendance and part-time.
The full time course is specifically aimed at home and international BSc and MBA graduates who wish to know more about this topic and significantly improve both their employment and pay prospects.
The part time course is essentially identical to the full time except that the students will take two years to complete the course rather than one. It is specifically aimed at professionals currently working in database and related business and industry.
For more information see the course details
We normally expect applicants to have a degree in computing, with a grade equivalent to at least a Class 2.1 Honours degree from a UK university, or the equivalent. However, if you don’t meet this requirement you may still apply in which case you will need to prove that you have equivalent experience in the field in order to be accepted onto the course. If you don't have a recent computing degree then we will need to see a full CV and you may be asked to attend an interview at Dundee with an academic panel. That CV should contain all the usual material that makes up a normal CV. However, in addition, you may want to include information that answers the following questions:
- Do you have some ‘internet community’ recognition – for example, are you an MVP (Microsoft Valued Professional)?
- Have you acquired any technical/commercial qualifications – such as being an Oracle certified DBA or attended any relevant commercial courses?
- How much experience do you have in the database industry – number of years, achievements?
- How much experience do you have in the BI industry– number of years, achievements?
- Have you any experience of MDX?
- What database/BI software have you used?
If you are not sure if your degree is eligible then please contact us for advice.
All applicants will be interviewed, where they will have an opportunity to highlight any areas of experience that demonstrate an aptitude for this kind of work. Telephone (or Skype) interviews will be arranged for those unable to attend Dundee in person.
Applications for the course should reach us before 18th October 2012. We will invite you to an interview in order to determine if you are suitable for the course. Interviews will be held in the last quater of the 2012
Students should be aware that they must attend the first intensive week in January. Overseas students must be in Dundee the week before the first intensive week for matriculation. Failure to do so will result in the loss of the place on this course
Applications should be made online using UKPASS.
If your first language is not English, you also need to provide evidence of a sufficient level of proficiency in English. The School of Computing requires one of the following qualifications or the equivalent:
- TOEFL 580 (or 237 for the computer based test)
- IELTS 6.0