Visual analysis engine


Visual analysis engine Rainbow

Rainbow helps to detect hidden patterns, as well as predict and understand the future by visualizing big data and the analysis result from various perspectives. Rainbow not only visualizes simple individual data, but also converges and reorganizes different data, and enables visual analysis through dynamic dashboards.


< Visual analysis engine concept map >

Data expressed by various visualization libraries through the workbench is managed through the engine’s temporary internal repository and can be published on the web, corporate portals and social media. Rainbow is the best big data visual analysis engine to help obtain solutions and answers through data, and obtain new insights from big data beyond the limits of conventional BI (Business Intelligence) and visualization tools.

Main Features

Supports various data sources and file formats
  • Data filtering, join, set operation and regression analysis
  • Dynamic visualization of 30 types based on standard HTML5 and web/mobile publishing
  • Drag-and-Drop-type Visualization and Strong Dashboards

Main features and specifications

Rainbow can combine different data sources, calculate and filter data selected by connecting various types of data sources, and easily generate interactive visualized elements with the final purified data. 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 server environments in real time from DBs, various data files, and URLs. It has various linkage support features as follows.

  • Refinement for real-time data extraction and combination

Through data connection, the preferred source data can be extracted in the original form, or data can be extracted after only the fields in the data needed for analysis are selected and refined. When 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. Interactive visualization libraries can be used to visualize the results of refined data using 30 different powerful interactive charts and dynamic visualization libraries.

  • HTML5-based web publishing(report)

It is a feature which allows you to check the visualization elements created by publishing to a web server or share them with others, and share and export them by using HTML5-based web publishing features in a report format on the web.

Main engine screen