Learning Design Oriented Data Visualization

Learning Design Oriented Data Visualization - learning design oriented data visualization

Learning Design Oriented Data Visualization – Data visualization: A wise investment in your big data future.

Humans have a powerful capacity to process visual information, skills that goes back thousands of years. And since the dawn of science, we have employed intricate visual strategies to communicate data, often utilizing design principles that draw on these basic cognitive skills. In a modern world where we have far more data than we can process, the practice of data visualization has gained even more importance. From scientific visualization to stylistic infographics, designers are increasingly tasked with incorporating data into the media experience. Data has emerged as such a critical part of modern life that it has entered into the realm of art, where data-driven visual experiences challenge viewers to find personal meaning from a sea of information, a task that is increasingly present in every aspect of our information-infused lives.

Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns. With interactive visualization, you can take the concept a step further by using technology to drill down into charts and graphs for more detail, interactively changing what data you see and how it’s processed.

Why is data visualization important?

Because of the way the human brain processes information, using charts or graphs to visualize large amounts of complex data is easier than poring over spreadsheets or reports. Data visualization is a quick, easy way to convey concepts in a universal manner – and you can experiment with different scenarios by making slight adjustments.

Data visualization can also identify areas that need attention or improvement, clarifying which factors influence customer behavior, helping you to understand which products to place where and predicting sales volumes.