Data visualization sits right in the middle of analysis and visual storytelling. At Zion & Zion, we utilize data visualization in several ways. A big component of this is creating online interactive dashboard reporting for clients, mainly with the use of Tableau. Outside of Tableau, there are numerous data visualization tools and technologies that can be used to analyze massive amounts of information and make data-driven decisions. If you’ve ever stared at a massive spreadsheet of data and couldn’t see a trend, then you know how much more effective a visualization can be. Individuals who don’t work in analytics day to day may not know the amount of work and strategic thought that goes into creating some of the great charts and graphs they see as the result.

In this article, I explain what data visualization is, why it is important, and how to get started when you are ready to take your data and bring it to life in ways that will improve and elevate your analytics—regardless of industry you are in and your business needs.

What is Data Visualization?

First and foremost, data visualization refers to taking raw data (typically numbers) and forming a picture or graphic to represent the information. There are numerous techniques used to communicate insights from data through visual representation. These techniques include charts, graphs, maps, etc. Data visualization is often used interchangeably with terms such as information graphics, statistical graphics, and information visualization. The main goal with all of this is to take large datasets and turn them into visual graphics that allow for easier understanding of complex data.

Why is Data Visualization Important?

As humans, our sub-conscious system processes more information through vision, and data visualization is a perfect solution to communicate patterns and insights from data sets. Our eyes are drawn to colors and patterns. Most of us can quickly identify red from blue, squares from circles, and directional cues. Our culture today is extremely visual, including everything from art and advertisements to TV and movies.

Data was not always viewed in a visual way, and throughout history there have been some very analytical-minded people that have developed some of the charts and graphs we still use for visualization today. One of the key players, often considered the father of statistical graphics, is William Playfair. He invented the line and bar chart we often use in the graphical representation of data today. You can learn more about him and other contributors to data visualization here.

Advancements in technology and continued learning about the human mind have taken these ideas even further and explored how different colors, shapes, and sizes can be utilized in a way to make standard visuals speak even more clear. It has been said that approximately 90% of the information we absorb is done so visually—further demonstrating why data visualization has become such a key component of data science and analytics.

How to Get Started

So now you want to transform large amounts of data into an easy to digest visual format, but where to start? One of the biggest pitfalls of today’s ability for so many companies to have access to so much information is to experience of feeling like you are “drowning in data.” To help combat this, it is best to take a step back from the large amount of information you may have and focus on why are you looking at this data in the first place. Essentially, there are two main uses of data visualization: exploratory (to provide information) and explanatory (to communicate insights).

Data Visualization considerations:

  • Who is the audience?
  • What is the purpose?
  • What is the message?

Simply put, what are we trying to do? What are we trying to show? Starting with these very basic questions can help to begin thinking about the much more in-depth considerations that will need to be answered. For example, when we work on a media reporting analysis for clients, some of the considerations we think about are:

  • Is this for internal use and/or client facing use?
  • Are we trying to get granular performance metrics of KPIs across media channels or looking at media in evaluation to client marketing goals?
  • Is there historical data to be incorporated and/or real time data that will need to be structured to feed into our reporting and visualizations?

This last question will lead into the next big step when are getting set up to create visualizations- how do we get the data we need into the format we want? An example of this is utilizing a data warehouse to help with storage and security of a client’s data. If you’re interested in learning more about how to access client data, check out our article on automating database extracts. Additionally, when possible, setting up an API (application programming interface) integration to streamline the process of gathering data from different sources and platforms can exponentially cut down on the need for manual upload and consistent refreshing of extracted data. There can be a lot of work involved when setting up the ability to access important data to build reports and visualizations, so it’s essential to ensure you’ve taken some of the basic questions seriously when considering what your goals are.

Bringing Data Visualization to Life

Once you have the data you need and an understanding of what you are trying to accomplish, there are almost endless ways to turn that information into visualizations that meet your specific goal. Data visualization aides in the understanding of vast quantities of data by applying visual representations to the data.

General types of data visualizations include:

  • Charts
  • Tables
  • Graphs
  • Maps
  • Infographics
  • Dashboards

A benefit of using a dashboard is the ability to combine multiple visuals of different data within a single report. Some commonly used visuals are area charts, bar charts, box-and-whisker plots, pie charts, Gantt charts, heat maps, line graphs, scatter plot, tree maps, and many more! To learn more about when to use different charts and graphs, this article from Tableau is a helpful resource. If your reporting needs to include tracking against different media KPIs to compare different tactics, platforms, and channels there may be a need to view data across different segments of times, filters, and more.

Those who work in analytics are familiar with excel and the fundamental ways to sort and pivot data into ways to analyze. The largest obstacle when using this method is the data itself is then static—both until updated and from an interactivity perspective. These are some of the reasons we utilize Tableau for so much of our reporting needs, both internally and externally for clients. A key element of using platforms like Tableau for digital reporting vs. static charts is that it leads to faster decision making. We have all heard “time is money,” so the ability to gather, view, and quickly act on data in real time is key.

Applying to Business Needs

At Zion & Zion, we routinely use data visualization as a key component in our analytics and reporting. There are endless ways different data and views can be valuable for different business needs. Media and marketing campaign reporting, sales and registrations, and website engagement are some of the main uses of dashboards within the agency.

Below are just a few of the many benefits of using digital dashboards for our clients:

  • Visual presentation of performance measures
  • Ability to identify and correct negative trends
  • Measure efficiencies/inefficiencies
  • Ability to generate detailed reports showing new trends
  • Ability to make more informed decisions
  • Align strategies and organizational goals
  • Saves time compared to running multiple reports
  • Gain total visibility of all systems instantly
  • Quick identification of data outliers and correlations


Today, almost all businesses across various industries are inundated with so much data, it can be hard to know what is important, what is valuable, and to whom. There can be a lot of time lost trying to figure this out that you end up losing the opportunity to make future business decisions.

We are an inherently visual world, where a picture is worth a thousand words. Data visualization is one of many steps forward in the world of analytics and data science as a whole. By knowing the basics of what data visualization is, why it is important, and how set it up, we can be armed with the right tools and processes to further our analytical insights like never before. Don’t drown in data—visualize it!