Ingersoll Rand - organizing data for visualization with Alteryx

Den Howlett Profile picture for user gonzodaddy September 23, 2014
Summary:
Alteryx helps Ingersoll Rand turn lead into gold as it seeks to visualize data to improve customer insights.

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Alteryx

Organizing data for inclusion in a dashboard is never a simple matter of injecting a data dump into a visualization tool like Tableau and then expecting to get a good outcome. As Sean Otto, market insights at Ingersoll Rand explains,  data needs organizing which is often 'muddy,' What does this mean?

Otto provides an example where he talks about a situation where you might want to pull out email addresses to add them to a campaign. Ingersoll Rand uses Alteryx to turn 'lead into gold' and, according to Otto, the process is as simple as connecting Alteryx to the data source and running a query against that data.

This is a far cry from the days when you'd have to invest in IT resources to extract, cleanse and then load the data into your business intelligence tool. In some scenarios, Ingersoll Rand achieves savings equivalent to 16 hours per month - see slideshare.

During our conversation, I asked why this process has been so hard, even after so many years of development.

Otto was unequivocal. He lays the responsibility firmly at the door of the business schools that fail to teach MBA students about business user needs. He also slams the database companies for the way in which they have insisted on selling directly to the C-suite and avoided the needs of users on the assumption that IT would solve the problems that would be encountered.

At the end of the video, I poke fun at MBA types - it was too good an opportunity to miss ;)

But more seriously, as we learn more about the problems that the business of data science is trying to solve it is clear that collections of data are only going to get more difficult to organize. So for example, I heard today about the way LinkedIn data in one set had more than 620 different classifications for the generic description of 'nurse.' Can you imagine trying to reclassify that data set so that you could find the right types of people to target for recruitment?

We have experienced situations where tagging runs out of control so that you end up with a long tail consisting of 'tags of 1' clusters. This type of situatio has to be managed before the data can be rendered useful for decision making purposes.

It is these kinds of scenerio that tools like Alteryx addresses.

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