4th - 7th May 2016

Liverpool

Mark_Whitehorn.jpg

Mark Whitehorn

Mark Whitehorn


Mark Whitehorn specialises in the areas of data science and BI.

 

Mark works with national and international companies, designing BI systems and Data Science solutions.  In addition to his consultancy practice he has also acted as an expert witness in cases of patent infringement and for the police in cases of computer fraud.

 

He is a well-recognised commentator on the computer world.  He is a regular contributor to The Register, has written numerous white papers and also eleven books on database and BI technology. The first one, Inside Relational Databases has been selling well since it was published in 1997 and is now in its third edition. It has also been translated into three languages. Another of his books FastTrack to MDX was co-written with the inventor of the language, Mosha Pasumansky. 

 

Mark is also an associate with QA Ltd.  He has developed several of the company's courses (data science and big data course, database analysis and design, MDX, Dimensional modelling) and teaches them all.

On the academic side, Mark is the emeritus Professor of Analytics at the University of Dundee where he designed and runs a Masters course in Data Science.  There he also works with the prestigious Lamond labs. applying BI and Data Science to proteomics

For relaxation he collects, restores and races historic cars which keeps him out of too much trouble. He only wears a tie under duress, doesn't possess a suit that fits and unashamedly belongs to the beard-and-sandals school of computing.

http://www.dundee.ac.uk/study/pg/data-science/
Mark Whitehorn has submitted a session for SQLBits XV, although the agenda hasn't been chosen yet. See all submitted sessions.

Pending Sessions

Analytics is all about having a good set of analytical tools. Last year at Sqlbits I outlined 4 such tools, this session will expand on that set. We’ll cover: • Dark Data • Probability calculations • RFI

Previous Sessions

Why and when denormalisation makes sense.
This talk looks at MDX and DAX, examining their similarities and differences. It won’t turn you into an expert in either but it will help you to decide, given your particular career plans, if either or both are worth learning.
There are some little-known but very useful ways of extracting information from data. This session will cover: • Monte Carlo simulations • Nyquist’s Theorem • Simpson’s paradox • Benford’s Law These will rock your world (they certainly rocked mine).