Data Visualization

With our data visualisation tool, DATA V, you may examine and display vast and intricate data indexes as visual dashboards. Through an intuitive graphical interface, DATA V seeks to make data visualisation more accessible to a wider audience and assist engineers in building effective visual applications. 

In the circumstances like conferences and presentations, business monitoring, risk warning, and geographic data analysis, DATA V can meet your requirements for data visualisation. This data-driven process enables effective data mining and analysis, allowing the client to reap many benefits.

Why DataV?

  • Use a variety of graphs and widgets. 

    DATA V provides many primary and thirdparty chart libraries to help users create excellent infographics. 

  • Create projects for expert geographic visualisation. 

    With DATA V, you can overlay geographic data and produce effects like heat maps, regional chunks, flying lines, geographic trajectories, and 3D globes. 

  • Construct visualisation projects using templates created for various sectors. 

    To better serve your organisation, DATA V offers a wide variety of industry-specific data templates. 

  • Easily create visualisation projects 

    DATA V requires little programming knowledge and allows you to develop expert visualisation projects with straightforward drag-and-drop operations.  

  • Publish visualisation projects with flexibility.

    Projects for DATA V visualisation can be modified and divided into a variety of unusual arrangements. You can establish access control and secure the information displayed on the dashboards by publishing projects with a password or token authentication. 

  • Availability of multiple databases and data formats. 

    Use dynamic requests to connect to databases such as OracleDB, ApsaraDB for RDS, and APIs. The CSV and JSON formats for static data are also supported by DATA V. 

  • Simple editing and publishing 

    A quick and effective way to set up component interactions, enabling interactive data analysis by transferring parameters from one component to another. 

01
Identify areas that need attention or improvement
02
Clarify which factors influence customer behavior.
03
Help you understand which products to place where.
04
Predict sales volume

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