What is the most used feature in any business intelligence solution? It's the Export to Excel button.

I know this is an old joke in the BI community but I couldn't resist. I was recently forwarded an article on the continued popularity of Excel in the BI community consisting of quotes from 27 experts saying how great and how relevant Excel remains.

We do categorize BI as static and historical as opposed to forward looking predictive analytics but I bet it's still true that Excel is a very widely used tool even by folks that categorize themselves as data scientists.

I'd like to make this more of a discussion than a lecture so here are some questions you can help me and our community ponder about Excel:

Does a high level of usage of Excel point to organizational fragmentation and silo-ing of data?
Does the use of Excel occur even in predictive analytics or mostly in the analysis on historical BI DW data?
Does this point to a lack of standardization around a platform (e.g. SAS or Aster) or around an agreed technique (e.g. R)?
Does this point to a lack of resources to help with analysis either in IT or in your formal analytics group?

Feel free to add your own question.

You can see the original article here.

Tags: Excel

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Comment by Jimmy Shen on October 16, 2015 at 10:33pm: A high level of excel use, from my experience, is due to a company's culture that usually manifests itself as fragmentation and silos. Given that a company has the means to invest in more sophisticated software to facilitate data science but still uses excel a lot, there is a culture of 'business as usual'. Technology and subsequently data science thrives in an open, empowered, and empirical culture. These are not highly sought after traits in the business world where many companies have thrived by adopting an antithetical culture.

Excel is used and understood by most people in this environment but do not understand SAS and why its so expensive. Companies that are just now coming around to data science or a data driven culture have a long way to go and probably enjoy some form of monopolistic status or inelastic demand.

TL;DR If you're a data scientist and the only paid software you use is excel at a company, no one will understand your full potential and you will probably be doing reporting.