Data Visualization

Join both Natalie Bendroff & Darryl Hofer in today’s Data & AI Happy Hour Chats Vlog on Data Visualization.

N: Thank you for joining us today!

My name is Natalie Bendroff and I’m a Project Manager in the Data and AI practice.

D: And I’m Darryl Hofer! I’m a Senior Consultant also in the data AI practice and I’m going to be asking Natalie few questions today concerning data visualizations.

Uh, so Natalie, I can tell you everything you need to know about data visualization in one word and that would be…

N: What’s that?!

D: that would be story.

Everywhere we go, whether we’re at work, or in our personal lives, via social media, were constantly inundated with data visualizations, right? And for good reason, because it’s such a powerful and effective way to quickly summarize and inform us of a million different things.

Unfortunately do this simplicity, I often to see a lot of misrepresented data and people who aren’t effectively telling their story due to bad visualization practices. Umm, so let’s start off with what is data visualization and why is it so important?

N: Great question!

Well, data visualization just to define, it’s the practice of translating information into a visual context. Such as a map or a graph; and it’s to make data easier for the human brain to understand and pull insights from. In addition to that, the main goal of database visualization is to make it easier to identify patterns, trends, and outliers in large data sets. So, if you really think about it, data visualization is extremely important in almost every career, regardless of industry or size. All types of businesses are using data visualization to help make sense of their data, because it provides a quick and effective way to communicate information in that universal manner.

D: Ok.

So, in these visualizations are there any types that are better than others?

N: You know, it really depends on the story that you want to tell. So, you need to consider how the end user will need to interact with that data, and then make that data as clean and beautiful as possible. Hmm so based off of what that story is, then you can define that trend or pattern that you’re trying to build.

Hmm, so a few different types of data visualizations include bar graph, Clamor area charts, pivot tables, line graphs and pie charts; and each visualization option provides that unique way to tell the story. But, as you mentioned, you have to know what story you want to tell in order to select the most effective visual to go along with that.

D: Cool.

And what about bad types of data visualization?

N: Yeah, so that’s very prominent in today’s society. Uhm, the bad types you know believe it or not, there are plenty of opportunities for data visualization to be presented in a way that is an effective, or for lack of a better term, presented poorly or just plain bad. So, a few examples that I can think of poor data visualization includes misleading labels and headers, charts within charts, and then simply just meaningless visualization. So, things that may affect the end user to misinterpret that data when you’re trying to compare items that aren’t apples to apples. So there really are a lot of different types of bad data visualization. Uh, do you Darryl have any examples of a bad data visualization that you come across in today’s society?

D: Yeah, I’ve seen a lot. Hmm, one thing that’s been more recent is we have this whole Covid-19 going around, right? And I keep seeing the same visualizations over and over. And while they are, it is accurately telling the information, like you said, it’s not comparing apples to apples. You know it doesn’t have a population density or age distribution to compare with because we’re comparing to a lot of countries that aren’t anything like what we are. Or just having too many, trying to tell too many details in one visualization. Uh, it’s definitely better to air on the side of keeping it simple. That way you’re more effective and users understanding what that story is or trying to communicate.

N: Absolutely.

D: So what about… what is some of the value businesses and clients can pull out of these visualizations?

N: Well, data visualization is extremely valuable. Some tools that it can help companies use is to identify those patterns and relationships, comprehending information quickly, and then also even predicting business processes. Such as future sales volumes and consumer behaviors to pinpoint emerging trends. It really, it really does help people make better more informed decisions because it tells a story. So, it allows that average person to easily read and see what may have once been a complicated algorithm or oversized spreadsheet.

And that will wrap up this chat! I just want to reiterate that not only do the different types of data visualizations vary, but it’s crucial to remember that to make it accurate and effective, your data must also be accurate, filtered, and clean. And don’t forget your data visualization should always tell a story. So thank you for joining us today. See you next week.

D: Thank you.