Chinese

Personality+

Customized Solutions for Smart Data Products

Multi-type Data Access | Drag-and-drop of Modules with Various Combinations

Summary
The customization solution for Smart Data Product is a one-stop solution for the automatic integration and visualization of Gridsum's data generated from its products with external various type of data . The program breaks the Gridsum standard product model, rapidly drag-and-drop components according to business needs and application scenarios by different functions, and quickly realizes personalized product interfaces to meet customer's needs and maximize the value of data.

Multi-type Data Access and Rapid Establishment of Data Model

Data product customization solutions can be linked to a variety of data sources, such as Gridsum's own product data, offline files, third-party databases, and third-party data interfaces through the flexible data access layer. It provides a more convenient and fast method for data association between multiple systems. Business personnel are able to quickly set up the data model and analyze the business requirements.

Configuration Completed through Drag-and-drop of Components to Quickly Meet Business Needs

System interface is created through configuration in a drag-and-drop way and can be optionally customized via component size, position, and specific data. The system can eliminate complicated processes such as code changes, testing, and publishing so that people who do not know much about technology can make their own business systems quickly, reducing demand response time and adding value to data as soon as they are collected.

Various Types of Components to Create Personalized Services

These services provide dozens of charts, such as pie charts, trend charts, and funnel charts, as well as a variety of visual components, such as off-site links and embedded web pages. The content and style of each chart and component can be highly customized. Through different types of presentation, it can achieve personalized services, mine the deep value of data, and meet different needs for different viewers of the data.
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