A rapidly increasing need for data driven decisions is driving users to embrace Business Intelligence (BI) tools to visualize and explore data. Yet most BI tools and dashboards fail to reach their intended outcome and therefore lack user adoption. For example, predefined presentations, workflows and dashboards are static and decision makers cannot find answers to questions that are not already built into the original content and workflow of the predefined content. Also, dashboards contain either too much or too little information. Consequently, users are either overwhelmed or under informed. Further, existing visualization and presentation practices assume a learning curve and users are expected to know how the information hierarchy is laid out before they can effectively navigate to the user's point of interest. Conventional presentations are generally static with slides that are fixed.
In conventional technology, data visualizations, for example, interactive computer slide presentations, need to be prebuilt by a content creator. Accordingly, conventional data visualizations cannot answer a question that is not already anticipated and prebuilt into the data visualizations. Moreover, they do not provide the capability to ask follow-up questions with reference to a graph for further drilldown or recommend a next best question to ask of the data. Conventional technology provides capabilities to decipher intent from a user request or other user input and then provide an output such as initiating a conversation with an application to complete tasks based on the user input such as ordering a pizza, booking a taxi, etc. However, conventional technology does not provide the capability to anticipate the next best question a user can ask. While conventional technology provides an ability to determine a context of a user query and to extend a context lifespan when interpreting user queries, conventional technology requires the context determination to be parameterized and context determination cannot be done dynamically. Additionally, none of these tools of conventional technology have a way to render interactive data visualizations dynamically to fit data requested by the user during presentation of the interactive data visualizations.
A system that allows adaptive, on demand, and intuitive contextual navigation of visual content is a new and useful change to existing data visualization and presentation practices. It serves as a natural fit to people's decision making compared to predefined dashboards, templates, and spreadsheets.
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