Category Archives: Uncategorized

Using R With Small Data – Links

Here are the links and demos from my talk on ‘Using R With Small Data’ at the Infiniteconf in London on July 6th 2016.

This OneDrive folder contains the materials for the talk. The files are the slide deck (in PDF format) and the generated html from the R markdown document.

The European Banking Authority (EBA) 2016 Stress Test Results online map tool is here.

Data Insights ‘Visualising Financial Data’ Talk – Links

Here are the links and demos from my talk on ‘Visualising Financial Data Using Power BI and R’ at the Data Insights Summit.
The video recording on youtube is here.
The code for the demos are on my GitHub page .  They include
  • Text Mining of Corporate Responsibility Reports
  • Operational Risk And Controls Assessment (RCSA) Visualisations
  • Large Project Gantt Style Visualisations
  • Visualisations based on the Gapminder dataset
They include the Power BI Desktop files and the R Scripts.
The European Banking Authority (EBA) 2016 Stress Test Results are here.
The online map tool is here.  Hans Rosling’s famous YouTube video of ‘200 Years, 4 Minutes – The Joy of Stats’ is here.
The London Business Analytics Group meetup page is here.  This shows our upcoming events.  Recordings of a few of our previous talks are on the Skills Matter page here.

Links for ‘Banking On Machine Learning’ talk

I gave a talk to Microsoft Student Partners about incubating machine learning into a large organisation, in particular into a big bank.  The slide deck is here.  I mentioned several events and articles during the talk.  Here are the links.

Rohan Kopparapu (4th year UCL) and Microsoft Student Partner  wrote a blog post about the UCL Data Science Student Challenges.

The video recordings of the two recent talks  about building a data-driven culture in an organisation are  Transforming a Museum to be data-driven using R – Alice Daish and
From nothing to something, a local government journey- John Kelly.

The podcast of the BBC Radio 4 interview with Anthony Jenkins, ex-CEO of Barclays, and others about how fintech and ML are disrupting banking is available here.

I suggested some London-based meetups (LBAG, my one)

The Economist article on the change of culture at Microsoft and its focus on cloud and AI is here.

 Dr Andy Pardoe runs a comprehensive list of AI and ML resources at as well as a personal site.  He has been named a Top 30 AI influencer recently.

The abstract for the talk is below.

Banking On Machine Learning

Many of the audience will have recently attended a hackathon at UCL. Over a weekend participants applied Azure Machine Learning to financial datasets supplied by Bloomberg and derived some insightful results – a fantastic achievement. This was for many their first taste of a hackathon and data science.  However, for many organisations, getting to the stage where they are doing hard data science as part of a viable project is a long way into the journey of introducing and successfully taking advantage of ML.

This talk looks at the experience of starting ML at a few organisations then focuses on the challenges faced by big diversified banks.  We look at why banks are rushing to embrace ML and consider both the  opportunities and threats that ML poses.  We’ll consider the steps to introduce and incubate ML within the bank; through awareness, education, crowdsourcing, mobilisation (including hackathons) and finally implementation of ML as the new normal.

We’ll conclude that the successful introduction of ML into an organisation is about communication, culture, change, marketing, business analysis… and finally the hard data science of the sort that we saw in the hackathon.

Power BI March Update – Links

I gave the March round-up talk at the London Power BI User Group last night, before John Kelly’s inspiring talk, without the benefit of slide deck or demos due to the AV issues.  So here is my slide deck and links of the events and resources I mentioned during my talk. And I have posted  8 minute video to demo the Power BI desktop February and March updates on youtube, and also on OneDrive

The details of the SQLBI ‘Mastering DAX Workshop’ training in London on March 22-23 are here.

The PASS Business Analytics Marathon on March 29th features two Power BI talks from London PUG organisers; Prathy Kamasani at 6pm and David Moss at 7pm.  Register here.

The PBI motion scatter diagram of the Gartner Group Magic Quadrant of the last several years is here.

Now that we can theme our colours, the color brewer site is a very useful resource for selecting good palettes of categorical, sequential or diverging colours that forms best practice.

The Power BI team video of the March desktop update is here.

The data storytelling course by Albert Cairo is here.

The Economist produce wonderful charts on a daily basis in their Graphic Detail section of their website.

My London Business Analytics meetup group is having a talk on Wednesday next week (15th March).  The subject is transforming a museum to be data driven with R. Sign-up here.

BA Marathon: Using R To Clean And Transform Small Data – Links

This page contains the links and references for my talk “Using R To Clean And Transform Small Data” at the PASS BA Marathon on 14th December 2016.

The video recording and slide deck  are  here.

The Microsoft Professional Program Certificate in Data Science has two R courses.  These are  the Introduction To R For Data Science and Programming With R For Data Science.  I also recommend the DataCamp online R courses.

The London Business Analytics Group (LBAG) meetup page where you can see upcoming events is here and the videos of some of the past events are here.  The London Power BI User Group (PUG) meetup page is here.  Mark Butler’s blog of recent PUG and LBAG events is here.

Visualising Risk

Risk Managers need to analyse and make decisions on data that changes at least daily. Each day trading and risk systems generate huge volume of data – millions, perhaps billions of rows. There is lot a variety within this deluge of data including trades, positions, sensitivities, prices and risk results such as value-at-risk (VaR). Reference data such as bank’s hierarchy, counterparty details, instrument details, countries, currencies are also required.

Dashboards and visualisations are essential to make sense of this. A good visualisation will provide a top-level view to bring out the big picture and overall trends, and highlight any outliers or exceptions that need attention. The best visualisations will then allow risk managers to drill down to the detail.

The next series of blogs will describe useful visualisations for showing certain aspects of risk and explain what features make them helpful. We will look at
• Tree maps for visualising VaR
• Mechanisms to drill down a firm’s hierarchy
• Bullet charts for comparing risk usage against limits
• Line charts to show P&L history and other time series

Links for ‘A Month Of Predictive Analytics’

I gave a short talk titled ‘A Month Of Predictive Analytics’ to the first meeting of the wonderful Meetup Mashup group on 18th June 2015. Here are the resources mentioned in the talk.

My slide deck is here.

Recent News about AI Machine Learning




  • Data Smart – John W Foreman
  • Practical Data Science With R – Nina Zumel and John Mount
  • Data Science For Business – Foster Provost and Tom Fawcett
  • Applied Predictive Analytics – Dean Abbot

Online Courses

My webinar for PASS Business Analytics Virtual Chapter (BAVC) comparing tools for exploratory data analysis is here together with previous webinars presented at PASS BAVC.

SQL Saturday Conference at Edinburgh ‘Learning R’ – Resources

Here are the links from my ‘Learning R through a typical BI task’ talk at the SQL Saturday Conference in Edinburgh on June 13th 2015.

The OneDrive folder contains

  • the slide deck
  • the R source code file for the Titanic demo
  • the CSV file containing the Titanic passenger list data used in the code above
  • the R source code file for the Iris demo

The books I mentioned in the Resources slide are

  • Data Smart – John W Foreman
  • Practical Data Science With R – Nina Zumel and John Mount

The course I mentioned in the Resources slide are

A presentation on Azure ML from Microsoft’s Andrew Fryer and Amy Nicholson featuring a sample to predict flight delays is on Amy’s One Drive

If you have any questions about the slide deck or the demo resources, please get in touch.