VizQL is a patented technology that provides interactive data visualization. It was developed in 2003 at Stanford University and it has fully changed the paradigm of analytical work with the data.
Traditional analysis tools work by organizing the data in rows and columns, and the user has to select the slice of data for a certain period, form tables from these data and then create visualization objects for the table.
VizQL technology eliminates all these steps and makes it possible to visualize data simultaneously with your actions, transforming them into a database query and then expressing the answer graphically.
As a result, the analyst gets a deeper understanding of the data "in a flash" and can run much faster, creating a "complex" visualization.
So, VizQL allows you to explore the data and receive the best understanding of it. With the arsenal of a wide range of visualizations, the VizQL user is able to see and understand the data in a completely new way, without limiting the perception of the traditional "flat" patterns of analytical reporting.
This provides an important principle of the natural way of thinking of the user while working with the information. Self-selected areas of analysis and detail with filters form a complete and thorough understanding of the situation.
Data Engine Technology
Data Engine is an innovative technology for data analysis developed by Tableau Software and Stanford University. Data Engine eliminates the limitations of existing data warehouse and provides interactive visual analysis process, enabling fast processing of large volumes of data.
With this Tableau technology you can analyze millions of data rows in seconds without custom programming scenarios of the analysis.
With Data Engine Technology you can:
- Receive an instant response to a request from the hundreds of millions of rows on a regular laptop.
- Avoid restricting the analysis of aggregated data and have access to the most detailed data
- Carry out unregulated requests without prior computing and programming
- Provide integration with existing enterprise data warehouses and the infrastructure.
- Provide connectivity to sources and produce fast loading of data.