In this 40-minute video Carmel Gunn and Bob Duffy from Prodata SQL Centre of Excellence explore the ’10s Irish Economic Crisis from multiple perspectives, using Microsoft visualisation tools from a previous version of Power BI, Power Query, Power Map, Power View and Q&A. The technology has improved since this video was originally published in 2015 (to numerous accolades!) but their approach as budding citizen data scientists is still quite novel even a few years on.

They take a very common business angle, where people need to find data and to make sense of it, fast, but don’t know what questions to ask, nor how to combine available sources in a way that makes sense.

We start by discussing early research on Wikipedia (1:52) into the available economic metrics (1:31). This data is accessed using Power Query and Excel (3:37) to bring a first view of the Irish GDP vs the economic crisis (8:09). Using natural-language Q&A feature Bob quickly builds a dashboard comparing Irish GDP against that of UK and Germany (15:06) before introducing the concept of the timeline (15:55). After Carmel’s insightful comments about the concern of GDP growth vs the growth of government debt (16:33) you see a powerful, animated visualisation which we call the Recession Line: it uses Power View animated bubble (scatter) charts to literally play back the economic crisis as it happened (17:45)—do not miss this part of the video!

A second part of this story focuses on the way the crisis money was spent (21:57) including the strange growth of the housing stock in those parts of Ireland that really did not need any such housing, shown on a Power Map (28:33). Subsequently, we touch a very interesting point: where did the money come from (34:05) which shows both the previously unexpected shift in the risk and the lack of its supervision or management on the side of the borrower and, perhaps, even the lender countries, while also showing you a good way to use a colourful stacked column chart in Power View. Finally, Carmel asks the question if Irish books have been balanced (38:09) at this moment in time, but you will have to watch the video to find out her answer.

Finally, Bob goes behind the scenes, showing you, briefly, some of the data model and DAX calculations that were needed (32:40).

Could Power BI have helped prevent a small country owing over 200 billion euro (40:00) in debt?