Best practices for building an analytical report on SAS® Visual Analytics

Creating a report in SAS® is very easy and you can build impressive reports with a few clicks. Although, it is not enough just creating. We should make it effective. To construct something like that, questions can show up like: How to build it? What means an effective report/dashboard? How to use my data in ways that mean something real? How make my dashboard help in decision making?

First, we must understand our data and then transform it into the information that we need.

SAS® Visual Analytics is an easy-to-use, web-based solution product that leverages SAS high-performance analytic technologies. It is designed for users to create reports and dashboards very quickly. You can create, test, and compare models based on patterns discovered during data exploration. This enables users to perform a wide variety of tasks including preparing data sources, exploring data, designing reports, analyzing, and interpreting data. And it can be displayed on the desktop or a mobile device.

Best Practices

Context

The success in data visualization does not begin with the data visualization. Instead, before beginning with the data communication, the attention and the time should be turned to understand the context of the need to communicate.

Context helps us to understand the information at the first sight, without needing to investigate for a long time.

It is also important to tell stories with data, more known as storytelling. With this technique, the presentations go far beyond a group of data arranged on a dashboard.

Simplicity

Attributes can be used strategically in two ways: First, they can be used to help direct your audience’s attention where you want them to focus. Second, can be used to create a visual hierarchy of elements, to conduct your public through the information that you wish to communicate or want them to understand.

Minimize the number of visual types and use the most simplified representation, it is important to understand how many visuals there are and what they mean, it needs to be coherent and visually pleasing since it represents your highlights priorities.

The style and communication are also very important when we want something clear.

Audience

Visualizations and dashboards need to be attractive for users to interact with. Using interactive elements allows the audience to work with the information, raise questions and reach conclusions on their own. This factor increases the credibility of the data displayed.

Be sure and be specific about who they are. Example: general public, CEO, technical, what type of customer and commerce, etc.

Effective Visual

There are a lot of different graphics and other types of visual information displays, but only a few will work for many of your needs. To be effective, you will need titles, subtitles, highlights, and comments for your reader to understand better what is being displayed.

Keep in mind that effective is almost affective. A good visualization generates an emotional response and genuine interaction with your audience.

Focus

Use techniques to draw attention to the key areas. Stay on one topic story. Readers start at the headline then work their way through all the linked visuals.

Try to eliminate distractions, we also want to analyze what we have and consider how we want our public interacting without visual communications.

For example, views need to be vivid, memorable, and contextualized with a logical sequential structure.

Think like a designer

Form follows function. When we talk about our data visualization form and function, we think at first about what we need our public to make with the data (function) and then we create a visualization (form) that allows this easily.

Get creative, use the space you have, choose the right colors for each situation, nice themes, different sizes to represent visual values, and a consistent font style.

Conclusion

Data visualization is at the intersection between science and art. We have a lot of ways to face the options about building a visualization, and there are a lot of distinct solutions to the same challenge in data visualization. Frequently, we will have a lot of possible paths to effective data communication.

Thus, if it makes sense for the task you are doing, let your creativity flow when communicating with data.