Visual Analytics is Different Than Data Analytics.

Anyone can become a Data Detective with Visual Analytics.

This last decade was the decade of big data; we have seen the exponential growth of data and data sources, and see only more growth on the horizon. Much of the data we’ve collected were unstructured and difficult to work with. With that came data scientists who created processes to make data more structured and easier to work with. As data analytics evolved and broadened, a newer field of visual analytics began to emerge.

Steamgraph of immigration to USA — A picture really is worth a thousand words

Visualization enables one to comprehend large amounts of data at a glance. Data visualization tools conveniently provide a way to see and understand data with the help of visual elements like charts, graphs, and maps. As a subspecialty, visual analytics is defined as “a multidisciplinary field in which interactive visual interfaces are used to support analytical reasoning.” Some interfaces and tools that you may be familiar with include Tableau, Looker, and even Excel. Broadly speaking, Visual Analytics goes one step beyond Data Visualization, wherein it uses interactive visual representations for pattern discovery to drive focus for decision making. Where Data Visualization helps to answer the “what” or “who” type of questions — such as ”what are the trends” or ”who are the top five customers”, Visual Analytics digs further by answering the “why”.

Objects in low-earth orbit — Earth’s trash to infinity and beyond.

Why use Visual Analytics?

The research is out there:

1. Share your findings with your broader team
2. Track the process of your current projects
3. Understand insights from your data more quickly
4. Execute decisions faster

With so many team syncs, 1-on-1s, and meetings, you want to be able to easily interpret and share the work you do. Rather than spending hours pouring over lists of numbers and relying on verbal explanations to convey your findings, you’ll save time and strain by employing visualization and visual analytics tools. Work smarter, not harder! If you and your team members can easily understand data and share insights, the hours you’ll save on interpretation and conveyance can be put to project execution.

Earth as a Cherry Tomato in a Garden of Planets — Sometimes you’ve gotta put things in perspective!

So… Who can use Visual Analytics?

On the surface, visual analytics may seem like a mechanism designed only for scientists and statisticians. In reality, it can be used by even the average business person! You don’t need extensive knowledge or a background in data or stats to make good, intuitive use of visual analytics methods. In fact, this is exactly where visual analytics shine: by empowering the average person to analyze data like a pro. Visual analytics tools are often interactive and leverage visual components that communicate patterns and trends to help users make better decisions.

How can your business make use of Visual Analytics?

Resultid, for example, is an app that allows users to perform visual analytics on text-based data. (Kyle, our lead developer, recently wrote an article concisely describing the goal of Resultid’s app.) One of the data narratives we currently have is called Theme Discovery. A narrative is the story you are building from the data you are reviewing. Examples of narratives include “How can I improve my product?” or “What are my competitors doing that my company is not?” We are hard at work to expand the narratives available every week! A core visual analytics component within our Theme Discovery narrative is Interactive Text Clustering, wherein a user can control the number of themes identified by tweaking parameters with a slider. Searching for just two themes might yield more general results such as “the customers hate this product for various reasons” while searching for four themes may break down the results into “customers dislike the product because of its price” or “customers dislike the product for its quality”, et cetera.

Let’s put some fun data about Disneyland into Resultid’s Theme Discovery narrative.

I grabbed a dataset containing reviews on U.S. Disneyland in 2018 and dropped it in the Theme Discovery narrative within the Resultid App. The app did its processing and in seconds it populated a number of preliminary themes, with the default being 17 themes (that’s the middle point between our minimum of 2 and maximum of 32). Next to each theme is the number of data points relevant to that theme — clusters — which the user can click to further expand and see the relevant accumulations of data. On the right side, a simple and familiar slider invites you to interact and manipulate the data easily.

I used the slider to shift from 17 themes to 7, which makes the more common themes apparent. By reducing the number of themes, we’re able to pull out the big ideas from the data, and if we expand the themes to 32, we can get granular and dig deep into the data. The slider is a simple visual component that helps me to easily arrange and rearrange the analysis.

After shifting the theme slider to your ideal number, clicking the Summary button generates a strategy based on the key themes. This analysis can save users a lot of reading time. This short example is just the tip of the iceberg of what applying visual analytics on your data can do.

To try out the Resultid platform yourself, click here.

Bottom line? Simplification.

The meteoric rise of Data over the last decade has coined the commonly referenced term “Big Data”. There has been a correlated rise in Data Analysis tools that aim to manage the capture, storage and analysis of information, and which have been helpful to businesses of all sizes. These tools are evolving to include advances in Machine Learning and Artificial Intelligence that aim to solve complex challenges in the deployment of Big Data. Resultid has a simple mission: to help you find patterns in your data that help you make decisions. Visual Analytics assists both the non-technical user and the sophisticated data scientist when it comes to understanding the themes in their Big Data. Providing approachable and interactive visual representations for pattern discovery simplifies the data analysis process for every user.

Now, everyone can become a data detective with Visual Analytics. Join our beta testing group here as we rapidly iterate towards an increasingly robust tool.