What is Good Data?

How different data visualization tools like Tableau, Power BI, Crystal by SAP, Domo, Tibco, and now Newton can tell stories that matter, in ways people can quickly understand

Big data, scalability, complex systems, the information age—the sheer number of data-related buzzwords and catchphrases are enough to give anyone pause. It’s true: we are surrounded by data, as well as ways to collate and present it. 

But when do we ask ourselves: what is good data? 

And how do we separate useful material from the ongoing cacophony? How can we tell stories with data instead of just looking at a collection of numbers on a page? How can we present data in ways that truly help us make better, more informed decisions?

What is good data? 

While it might be an ever-evolving and contextual definition, we’re confident good data is at least the following: 

  • Accurate 
  •  Complete  
  • Consistent 
  • Timely 
  • Validated or vetted 
  • Memorable

It may be also useful to think of good data as information that allows you to answer the questions you have in a given moment. 

And our ability to answer those questions is made possible—and even easy—through data visualization techniques.  

Why does data visualization matter? 

The purpose of data visualization is not just to make sure your clients, patients, or colleagues are engaged. The purpose of visualizations is to allow clear, quick insight. 

When data is visualized effectively, patterns, and links between cause and effect, become obvious. Your audience will be able to identify connections, identify opportunities, and understand complex material. This can help everyone, from researchers to parents, draw more accurate conclusions and make more informed decisions. 

Data visualization also matters because our brains process visual information about 60,000 times faster than text. While this is heartening (great to know you can skip the lengthy reports and get down to business!), it also opens another question: what are the best ways to present certain kinds of information? 

Let’s use an example. 

Not all data is created equally! Sometimes, we need ways to compare different types of data in order to develop a comprehensive understanding of a topic. For this example, let’s talk about land usage in the continental US. 

Land usage is a succinct way of referring to a complicated amount of data, including information like how to define terms such as “pasture” vs “cropland,” how to envelop the billions of acres reaching across the county and state lines, and of course, how to measure all of this over time. 

The go-to reporting for this kind of information is static spreadsheets and numerical charts that require meticulous attention (cue the snoozefest). [But] Data visualization tools like Tableau and Newton can make complicated interactions jump out to us immediately. 

This is a snapshot of a geographical map with color-coded indicators of the variety of land usage (cropland, pasture, forest, special use, and miscellaneous) from Tableau. 

Cartographical images like this allow us to see big patterns easily. From this kind of static, “zoomed out” image, we can identify there is more pasture in the midwest and more forest in the eastern half of the US. 

Tableau offers options to see the results state by state, and also as ratios of the whole. With many opportunities to toggle through ways to get both specific and general information, this graphic offers a lot of insight into a moment in time. 

But what if we’re trying to understand an additional layer to the story? How have these land usage divisions changed over time? 

Let’s layer on Newton by Triplidata

In the graph below, we have information presented in a different way. 

How much usage is happening across the U.S.?

With a moving 3D visualization, we’re able to abstract the data away from our preconceived notions of the US and what we expect to see. 

We’re also able to see the values change over time—a hugely valuable tool that broadens our perspective and allows us to immediately see trends. This, in turn, allows us to more rapidly forecast where those trends might lead. For example, it looks like land usage for cropland may continue to spread both east and west, from its current density in the central US. 

All of this information is useful; all the data is good: but, depending on what your questions are, you might need both visual aids to tell the full story. If you’re looking to understand where pasture land is saturated and identify where you should invest for maximum sustainability over the next decades, you’ll need maps as well as trends. When combined, these visual aids can provide deep insight and bolster your ability to make intelligent choices. 

Next time you’re assimilating a large amount of data for your project, consider how you can make it come alive. You deserve tools that allow you to tell the whole story.

If you’re already a Tableau user, come experience Newton to see how things can get even better. Newton’s engaging, customizable options now allow even more flexibility and ease—and most importantly, they allow you to showcase what good data really is.