PASS SQL Saturday Business Analytics

Yesterday was the first PASS SQL Saturday Business Analytics event in London and Europe.  This event wouldn’t have been possible without the event organiser Jen Stirrup and a whole raft of other people.  It was an amazing privilege to help at the event  also along side my colleague Jason Linham for the Data Community. The purpose of the event for Business Data now and future: interacting with data to drive the business, at the velocity of the business.  This event supplements the core SQL Server community events such as SQLBits, PASS SQL Saturdays and Local User Groups. The event was for those people Business Analytics and Business Intelligence professionals who were interested in knowing more about analytical features in Excel, Big Data, Azure Machine Learning, Hadoop, R and SQL Server Business Intelligence.

The keynote was presented by Jonathan Woodward, Microsoft UK’s Business Lead for BI, Analytics, Big Data and Data Science on Data Culture : From BI & Analytics to Big Data and Data Science.

There was an introductory session on predictive analytics which covered the history of data mining, algorithm choice and the CRISP-DM methodology. The CRISP-DM (cross-industry process for data mining) methodology is a methodology for providing a robust structured approach to data mining.
 

Image from: http://www.sv-europe.com/crisp-dm-methodology/

  

A few useful links to find out more

R Programming https://www.coursera.org/course/rprog

www.codeschool.com/

There were various sessions on excel charts with a strong emphasis on never using the 3Dcharts  or cones as a choice for data visualization. (Edward Tufte, The Visual Display of Quantitative Information is a recommended read)

A few resources to look at

Peltier Tech Excel Charts and Programming Blog http://peltiertech.com/

chandoo.org  http://chandoo.org/wp/

www.excelcharts.com/ for dashboards

One of my favourite sessions was delivered by Mark Wilcock on Using R, Cubes And Data Visualisation To Answer “What If” Questions. The session provided some interested insight into how data exploration and data munging lead to data visualization and drew on a combined tool set. It was very interesting to see the benefits and disadvantages of each area R, Excel, SQL and Cubes across the Load, Model and Visualization stack. He recommended watching a presentation delivered by Prof. Mark Whitehorn, School of Computing, University of Dundee on the Monte Carlo scenario.

Microsoft Finance shared how they used the full set of BI tools to deliver finance dashboard and drilldown reports.

The day concluded with an excellent session from Chris Webb on the usage scenarios for Power Query and the use of the M language. 

This was a fun and informative day which I hope will be repeated next year.