Data

Use the Data page to build reusable, cleaned data models so that standard users can easily generate reports without needing to write complex SQL queries.

Best Practices

• Limit Data Size: Only include columns and rows that are strictly necessary for reporting to optimize performance.
• Use Clear Naming: Rename raw database columns to business-friendly terms (e.g., change proj_id to Project ID) so end-users understand the fields.
• Filter Early: Apply filtering transforms as early as possible in the data cube flow to reduce the amount of data processed downstream.
• Storage Type: For very large datasets, consider changing the storage type to Warehouse or In-Memory to improve dashboard load times. (Keep in mind the 24-hour refresh cycle of the Snapshot-Data Warehouse).

Data Connector

A data connector holds the information necessary to connect to a data source. It lets you connect to your data through a provider.

The connection information required is different depending on the type of data provider that you select. For example, to connect to SQL Server, you generally need to choose an authentication method, specify a server instance, and indicate the database you want.

Once you've created a data connector, you can go to the Explore window to locate it and its access native data structures such as tables. For example, you can drag columns from native tables under your data connector and visualize it right away on your dashboard. Behind the scenes, items such as metric sets are auto generated to have a complete data flow.

Users can create custom data connectors only for data from Trimble Unity Construct.

Hover over each setting to see a tooltip providing a description of the setting.

To create a data connector

1. From the main menu, click Data, then click Data Connector.
2. Click Create.
   The New data connector dialog is displayed with various settings available based on the type of data provider you want to use.
3. Enter or specify details in the following fields:
   • Name: Enter a name and select the folder location of the connector to be saved.
     

     To create a subfolder, right-click an existing folder and click Create Folder.

   • Data Provider: The data provider must match the type of data you wish to connect to.
     • Click Test connection to verify the entered information. A message will appear in the bottom-right corner of your browser window indicating whether the connection was successful.
   • Data provider information: Enter the information for the selected data provider. The settings below may change after changing the data provider.
   • Check In: This option is checked by default. When selected, the data connector will automatically be checked in and shared with other users who have access to the current project. If not selected, the data connector will only be saved.
4. Click Save.
   A message confirms that the data connector was created and that a discovery operation was started to automatically find and list all the tables, stored procedures, and other available data 'structures' for you to work with. This runs in the background so you don't need to wait for it. If you want to make changes to the data connector, you can re-open it from the main menu.
   

Data Cubes

Use data cubes to integrate data from different sources, transform the data, and produce a reusable data model with optional data storage capabilities.

A data cube is where specific data is stored. Every data warehouse entity or table is a single data cube in advanced reporting.

To create a custom data cube

1. From the main menu, click Data, then click Data Cube.
2. Click Create and then select a blank canvas or a pre-existing data cube type.
3. In the Explore window, expand Data Connectors to locate the required Trimble Unity tables.
4. Drag and drop the desired table onto the canvas.
   When you add the first data source, a simple process is automatically created consisting of two transforms, with data flowing from left to right. A data cube name is automatically assigned and displayed in the status bar at the bottom, which you can double-click to rename. The first node in the process represents a query to select data from this table.
   The second node is a Process Result transform, which represents the output or result of the data cube. This transform doesn't do any data processing but allows you to configure the way the data is made available to users accessing data from the cube.
5. Add a second database table to the canvas. It will be displayed in red because it is not yet connected to the first table.
6. To insert a join transform node connecting the first source and the process result, click the connection link between them and then use the Transform options in the Add/Edit section on the top toolbar such as Join.
7. Click and drag a connection from the second input to the transform option. To configure any transform, select it and click Configure in the toolbar or from its right-click context menu. You can add nodes (Transforms) from the toolbar to filter, join, or aggregate the data as needed. For a list of available transforms, see List of transforms in the tool's Online Help.
   To add a third table, you will need to insert another join transform into the process because each join accepts only two inputs. Configure the transform after it is connected.
8. Configure the final output of the data that users with read access will see when using it as a data source in metric sets.
   1. Click the Process Result transform to open the Data cube elements panel which shows the list of measures (numeric) and hierarchies (usually non-numeric) output from this data cube. Click on an element or its pencil icon to edit its settings. You can customize each element's name, description, predefined formatting, and more.
   2. Double click the Process Result transform to open the Process Result dialog. Unselect any duplicate values to guarantee that each value shows up only once.
9. Open the Data Preview window to preview the data processed up to whichever transform is selected.
10. Click Close.
11. Click Check In to check in the data cube and make it available for other users.

Data Joins

Data joins allow you to combine records from two or more tables based on a common field (like a Project ID or User ID). This is essential when your reporting requires pulling project details from one table and financial records from another.

To create custom data joins

1. From the main menu, click Data, then click Data Cube.
2. Click Create and then select a blank canvas or a pre-existing data cube type.
3. Inside the data cube designer, drag two tables onto the canvas. A Join transform node is often created automatically if relationships are predefined; if not, drag a Join transform from the toolbar.
4. Connect the output lines of your two tables to the input of the Join node.
5. Click the Join node to open its configuration panel. Specify the Join Type (such as inner, left, right) and define the mapping logic (such as Table A.ProjectID = Table B.ProjectID).
6. Select which specific elements (columns) from each table should be passed forward to the final output.
7. Click Close.