Data Management: Processing Your Data

Data management is the foundation of effective visual dashboard design. This chapter is divided into two sections, covering everything you need to know about preparing, organizing, calculating, and managing data in Dashboardx Designer.

1. Dataspace — Organize and manage all data through the spreadsheet-like interface of the dataspace view.
2. Datasets — Define appropriate data as datasets in the dataset panel by creating datasets, and manage them in the dataset list panel for use by visualization components.

Why Data Management is Important

Data preparation is a necessary step before visualization. Effective data management ensures:

• Accuracy: Clean, reliable data leads to accurate insights
• Performance: Well-structured data improves dashboard response speed
• Flexibility: Properly organized data supports more visualization options
• Maintainability: Clearly organized data sources are easier to update and maintain

How to Perform Data Management

• Most individuals or organizations have experience using spreadsheets (such as Excel, WPS Spreadsheets) for data management, and many have already summarized best practices that fit their own needs. These experiences can be fully transferred to Dashboardx Designer to complete most data management tasks.

• Based on the above work, we need to further consider the following questions:

  1. Which data needs to be visualized? → Use them to create datasets
  2. Does the data that needs visualization depend on certain variables? For example, quarterly statistics depend on the quarter value selected by the user
  3. If dependent variables exist, do these variables need to be presented in the dashboard?
  4. If presentation is needed, are variables filled directly by users through input components?
  5. If not, variables may depend on other data. Usually, these variables can be obtained by slicing existing data. It is necessary to ensure that existing data has defined datasets.

• In the above process, attention should also be paid to whether the relationships between datasets in the final dashboard are reasonable, and whether the dashboard as a whole meets requirements.