What Is Data Visualization?
Being able to collect and analyze data is essential to making smart business decisions. You can learn valuable insights from the actions your customers take as well as from their general behavior online, all of which is available in the form of raw data. The challenge lies in making sense of the data you have in order to gain insight from it. It’s why you need to visualize your data. Data visualization allows you to organize your analytics in a visual way that makes it easy to consume, such as in the form of graphs or charts. Through data visualization, not only is it easier to read and evaluate data, comparing the data you’ve collected becomes much simpler.
The History of Data Visualization
Data visualization is not a new concept. The use of pictures to better understand numbers has been around for hundreds of years. For example, maps and graphs were commonly used in the 17th century, while pie charts became widely used in the 18th century. One of the most famous examples of statistical graphics is of Napoleon’s Russian invasion, which was mapped by Charles Minard to visually show the size of the arm and the path of Napoleon’s retreat. This information was tied to other bits of data, such as time scales and temperature.
The ability to visualize data grew leaps and bounds as technology advanced. These days, data can be processed by computer systems at lightning fast speeds. The use of business intelligence (BI) software makes it easy to automatically visualize this data in a variety of customizable data visualizations.
Characteristics of an Effective Graphical Display
While visualizing data will generally make it easier for you to gather insights from it, not all of the many visualization methods are effective. An effective graphical display should do the following:
- Show your data – The visual representation should be able to display all of your relevant data within a single image. Having to scroll through a number of pages to see the different data sets will not be helpful. It should be able to display a large amount of data in a coherent way. It should also be integrated with the data set’s verbal and statistical descriptions.
- Focus on substance – You don’t want to be distracted by the graphic design, technology behind the visualization, or methodology. An effective visual representation will force you to focus on the substance of the data being displayed.
- Avoid data distortions – In some cases, the way that data can be displayed can affect how you read into it. This can lead to incorrect conclusions based on what you’re seeing. It’s important that the visual representation of your data does not distort your data.
- Encourage comparisons – A good visual representation will draw the user’s eye in a way that they will compare different pieces of data without making a concerted effort to do so.
- Reveal several levels of detail – Not only should a visual representation provide a broad overview of the data it’s displaying, it should also allow you to look at several layers of data for a more detailed look at the fine structure.
- Serve a clear purpose – There needs to be a clear purpose to the visual representation of your data or you won’t be able to draw any conclusions from it.
Why Is It Important?
There are hundreds of BI solutions on the market that not only advertise the ability to collect data or data mine, but that will visualize the data as well. In fact, the selling point for many of these tools is the customizable options available for their data visualizations. At first glance, this might just seem like an added perk that isn’t really necessary; however, there’s a reason why there is such an emphasis on data visualizations. The ability to visualize data is incredibly important for these reasons:
Understand Information Quickly
The amount of data collected by even a smaller company can be overwhelming to comb through–if not downright impossible. Graphical representations of that data make it much easier to digest large amounts of data in a clear and cohesive way. Imagine how time consuming it would be to try and analyze data presented in the form of a spreadsheet. With data visualizations, you can analyze your data quickly–sometimes even at a glance–thereby allowing you to identify issues and answer questions quickly as well.
Identifying patterns when faced with large sets of data that are not visualized can be nearly impossible. When provided with a graphic representation, it will become easier to recognize how your data may be related. By being able to identify such patterns, you can more effectively focus on areas that could influence important business goals.
Identify Emerging Trends
The ability to compare data in a graphic representation makes it easy to identify patterns that can help you make more informed business decisions. For example, viewing a bar graph that charts data over a period of time. The ability to identify emerging trends by being able to compare your data over time can not only help obtain an advantage over your competition, it can also help you identify potential issues (for example, outliers that are affecting customer churn) and to solve them before they become major problems that will affect your bottom line.
Communicate Insights Easily
Not only do data visualizations allow you to make more informed business decisions, they allow you to explain those decisions to others. Data visualizations, such as charts and graphs, make it easy to share insights with anyone in your company and to explain business decisions to shareholders and upper management.
As previously mentioned, there’s no shortage of data visualization tools available to create graphic representations of your data. We’ve listed some of the best data visualization tools currently available on the market:
Tableau is known for being a very user-friendly and efficient data visualization solution. Even though it’s simple to use, it can produce countless interactive visualizations–many more than the standard BI tool. It has the ability to integrate with many advanced database solutions, from Amazon AWS to My SQL, which gives it the ability to handle large and quickly changing datasets. With more than 74,000 customers, Tableau is currently one of the most popular data visualization tools around.
More than 48,000 customers use QlickView around the world. One of the main reasons for their huge customer base is the customizability of their tool, not to mention their extensive feature set. However, this does mean that there is a steeper learning curve involved to get the most out of it. QlickView users tend to use it alongside QlikSense, which enables data exploration and discovery.
According to the provider, Highcharts is used by 72 of the world’s 100 biggest companies. It’s particularly effective if you need a fast and flexible solution due to how user-friendly it is. Beginners won’t need specialist data visualization training to get started. Also lending to its user-friendliness is the fact that it offers cross-browser support, so anyone can view as well as run the tool’s interactive visualizations.
Datawrapper is a data visualization solution that is often leveraged by media companies to present statistics and create charts. It’s an easy-to-use tool that has a clean interface. You’ll have no trouble uploading CSV data, creating charts and maps, and embedding them into reports.
Sisense makes use of an innovative drag-and-drop interface that makes it easy to create charts as well as more complex graphics. Sisense also has the ability to collect data from multiple sources into one repository where you can access it instantly through its dashboards. In fact, their dashboards are quite user friendly and can be shared across your organization –even users without a technical background will be able to use them.
DataHero is unique in that it’s the first total self-service data visualization and data dashboard solution in the world that will convert siloed data into actionable insights. You can import data from cloud-hosted services such as Salesforce, Marketo, MailChimp, and more. One of the biggest selling points is its advanced data classification engine, which automates data classification and normalization. You won’t have to worry about getting the right configurations and can spend more time on gathering insight. Other features include drag-and-drop chart creation and the ability to share across your organization.
RAWGraphs is built on D3.js, which means that you don’t need coding know-how to build them. However, the charts available tend to be for more obscure purposes–you won’t find more basic charts, like line graphs, using RAWGraphs. And although you can bring in custom charts, this will require coding knowledge. If you have it, RAWGraphs can be very useful, especially since it offers very unique visualizations.
How it Works
Knowing what data visualization is and knowing how to actually implement it are two different things. The following are a few important things you will need to know before you can begin using data visualizations effectively:
- You need to understand the size and cardinality (uniqueness of your data values) of your data.
- You need to determine what you want to visualize and what you’re trying to communicate through that visualization.
- You need to know who your audience is to determine how they will process the information visually.
- You will need to choose a visual representation that best conveys your information in the simplest form.
Additionally, you will need to understand data presentation architecture as well as its objectives and scope.
Data Presentation Architecture
Data presentation architecture is a skill set that combines the science of numbers, statistics, and data to discover valuable insights and using data visualization to make it useable, relevant, and actionable. It’s a somewhat broad skill set that includes identifying what data is presented on what schedule and in what format.
Data presentation architecture has two objectives: to obtain knowledge from data in a manner that is effective (data that is relevant, complete, and timely as well as clear and understandable) and a manner that is efficient (data that is displayed in a manner that is not complex or that does not include unnecessary data).
The scope of data presentation architecture includes the following:
- To create effective ways to deliver the data to those who are viewing it.
- To define the meaning of the data.
- To determine how often the data needs to be updated.
- To determine how often the data needs to be seen.
- To identify the right data to display.
- To use the proper presentation formats, such as analysis, visualization, and grouping.
Data Visualization Techniques
There are much more robust visualization options you can use to display larger and more complex sets of data than just pie charts and bar graphs. Here are a few examples of some of the more innovative data visualization techniques out there:
A mind map is a diagram in which order and structure are not important elements. Instead, it’s a graphic representation that links words, items, or concepts around one central concept or subject in a non-linear layout. To get an idea of what a mind map looks like, think of an NCAA Basketball Tournament bracket or a family tree.
A popular graphic representation of news-related data is Newsmap, which is an app that provides a visual representation of Google’s news aggregator. It uses a treemap to visualize a substantial amount of information in a small space and divides that information into color-coded blocks. Not only does Newsmap show the most popular news stories, the color coding and size of the blocks allow you to see underlying patterns (such as what events are generating the most news stories in different parts of the world).
There are many, many creative ways to visually represent data. For example, a commonly used analytics tool is the heat map, which highlights areas of a webpage using different colors to indicate what visitors are looking at and clicking on most. Essentially, it lets you see a visual overview of all of the activity happening on a single page. Another good example is of Time Magazine’s population visualization. They display the population of American cities using visual spikes on a map of the country. The bigger the spike, the bigger the population. A key provides the viewer with an idea of the population represented by each spike.
One of the more unique examples of how connections can be visually displayed is the Shape of Song diagram. This diagram visually expresses the repeated sections of a song, allowing you to see how repetitive or complex the structures of certain songs are.
The ability to visualize more than a single webpage at a time makes it a lot easier to scroll through pages and find the item that you’re looking for as opposed to having to inspect tiny thumbnails. Spacetime’s Flash-operated tool helps arrange your search results in such an easy-to-view manner.
Articles & Resources
For more articles and resources on how data can be visualized, take a look through the Visual Complexity gallery, which has more than 450 examples of data visualizations to reference.
Its Impact on Your Business
Collecting and organizing data is one thing, being able to gain immediate insight from it is another. Data visualization allows your company to view and compare graphical representations of important data, making it easier to understand so that you can make more effective business decisions as well as share valuable insights across your organization. Without data visualization, you’ll find it much more difficult and time-consuming to analyze and present your data and to identify emerging trends that can help to guide your business decisions.
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