MANAGING KNOWLEDGE COMPLEXITY THROUGH VISUALIZATION

Managing complexity often comes down to being able to easily select the data to be viewed, and to vary the view or analysis to adapt to what is found initially as the exploration process continues. “We can present users with alternate outcomes depending on the selections they make,” Longhurst added, “such as a change in inflation or units of measure or changing how the data is aggregated.”

Filtering of data allows the application to be personalized for each user. “We are able to send the right data to the right person,” observed Longhurst. “If a metric is out of range, we can send an alert, and then if the person needs more detail, they can get a visualization on their mobile device.” Domo focuses intensively on the user experience. “The data may need to be seen by the content creator, a data consumer, an analyst, and then go to a decision maker, each of whom needs a different subset and view of information.”

Workflows in Domo allow analyses to be converted directly to action. For example, if sales of a particular product drop, Domo can send an alert, and a pricing agent can make a decision as to whether a promotional discount should be offered. Domo then updates the price on the seller’s ecommerce site and tracks the results, presenting graphs on the analyst’s device that show the impact of the change. “This feature brings together BI with accessible data that the user can interact with in order to complete a task, rather than being sent to multiple systems,” Longhurst concluded.

The flexibility of current visualization tools makes them an asset to any analytical initiative. These products can visualize data contained in relational databases or graph databases, and they provide engaging opportunities for exploring data to reveal information that predefined queries would not. As AI capabilities are incorporated and natural language interfaces become the norm, visualization will only become easier and more valuable in the coming years.