For anyone interested in data visualization, there had to be some level of satisfaction in seeing the controversy sparked by a chart tweeted out by Bill Gates.  The chart, one of several in an infographic Gates included in a tweet was a fairly simple area chart, but the concept it was illustrating (or purporting to illustrate depending on your point of view), the decline of extreme poverty, turned out to contain much more than met the eye.  Objections to the chart reached its author and a controversy was born.

For a summary of the economics and politics of the controversy you can check out this article in Vox; my observation is about how ubiquitous these types of visualizations have become. We have come to a point where we have high expectations for the kind of data presentations we expect from anyone attempting to convey information that involves any kind of data. Our level of sophistication regarding these visualizations has increased with the frequency and technological artfulness of what we see from a variety of sources and not just the those like 538, for example, that specialize in data analysis. Fancy data graphics are turning up everywhere.

As was the case with other aspects of on-line technology, we expect these capabilities to be available to us as tools in our own workplaces.  For firms with ample resources that has never been a problem. Smaller firms, particularly nonprofits perennially on tight budgets, have not been so fortunate. That may be changing as the threshold cost for implementing data analytics and related visualizations is getting lower.

One scenario that seems to be getting traction involves SalesForce paired with Microsoft’s Power BI. The company says over 30,000 nonprofits use the Nonprofit Success Pack or NPSP which is made available at a small scale for free. Whether it’s NPSP or another Salesforce product, integration with Power BI is fairly straightforward. Power BI is a powerful analytics and visualization tool that can scale to the enterprise level but is also very useful and cost effective at a small scale.  It can also be used with a variety of other applications, databases, Excel spreadsheets or csv files.

A typical implementation involves a few basic steps:

  • determine the type of analytics required and the necessary data
  • decide what tables and reports to use as sources for the data
  • determine the type of security required and the associated user roles
  • design data model to support the analytics
  • build the data model
  • build the analytics

The selected software along with organization’s readiness and experience with these sorts of projects will of course go a long way to determining the size of the effort. Whatever the tool selection, sophisticated analytics and visualizations have become a required part off every organization’s reporting and data distribution capabilities.  Once you acquire these tools, it’s worth bearing in mind that it only takes one well-placed chart to put you unexpectedly at the center of a data-driven controversy.