Visual analysis engine Rainbow
Rainbow helps detect hidden patterns, predict, and assess the future by visualizing big data and the analysis result from various perspectives. Not only does it visualize simple individual data, but it also converges, reorganizes, and provides a visual analysis of data through dynamic dashboards.
< Visual analysis engine concept map >
Data expressed by workbench’s visualization libraries is managed through the engine’s temporary internal repository. These data can be published on the web, corporate portals, and social media. Rainbow is the best big data visual analysis engine that helps obtain solutions and answers through data. It obtains new insights from big data beyond the limits of conventional BI (Business Intelligence) and visualization tools.
Supports various data sources and file formats
– Data filtering, data association and aggregation, regression analysis
– Dynamic visualization of 30 types of standard HTML5 and web/mobile publishing
– Quality drag-and-drop visualization and dashboards
Main features and specifications
Rainbow can combine and connect different data sources to calculate and filter the data selected. With the final purified data, it can easily generate interactive visualized elements. In addition, it can verify generated visualized elements by publishing them to a web server and sharing them with other people.
< visual analysis engine operation process >
- Supports real-time connection of various data source
This is a preliminary step to extract data from various heterogeneous big data platforms and storage This is a preliminary step to extract data from various heterogeneous big data platforms and storage server environments in real-time from DBs, various data files, and URLs. It has various linkage support features as follows.
- Select to extract and combine real-time data
Through data connection, the engine can extract the required data from the data source or from data-needed areas for analysis. While there are several data sets, only necessary fields can be selected, purified, combined, and generated as analytical data.
- Various interactive visual analysis
By connecting to various data sources, the selected data can be calculated, filtered, and combined between different data sources. The engine can easily visualize refined data results using 30 different powerful interactive charts in the visualization libraries.
- HTML5-based web publishing(report)
The ability to validate established visual elements through publishing to a web server or share them with others and export reports on the web using HTML-5-based web publishing functions.