The tools are :

· Tableau, a data visualisation tool, for exploring and presenting data beautifully,

· R and packages for data manipulation, plotting, text mining and predictive analytics,

· Excel - for pixel perfect reports,

· Power BI, an analytics and visualisation tool, for doing just that!,

· a SQL database in the cloud for improving data quality,

· a cloud-based machine learning toolkit (Azure ML),

· and cognitive services APIs for text analysis (and how to call them easily from R).

We'll use a wide variety of public datasets in our examples. These include :

· the recent results of the strength of EU banks from the European Banking Authority,

· health, wealth and populations stats from the Gapminder foundation,

· lifespan data from the Lancet and

· the corporate responsibility reports from a large bank.

The examples will also use some fictional data, but based on a real project, about a a trading firm's revenue reporting and other activities.