Set up custom data

Available with Business Analyst license.

A Business Analyst license in ArcGIS Pro provides access to Business Analyst data. Additionally, you can bring in your own data, such as sales figures or service rates. Once you bring this input data into Business Analyst, you can configure the variables, add Business Analyst data to the custom dataset, and create calculated variables—this is known as setting up custom data.

Variables you set up are stored as a statistical data collection and can be used alongside Business Analyst data. Statistical data collections, also called SDCXs, are accessed through the data browser on the Custom data node. Custom data is created from the variables in the data source, along with metadata of how to statistically apportion or calculate numeric data.

Statistical data collections are stored in the project home folder as an .sdcx file, containing the path to the source dataset, information about apportionment, and other custom data properties such as calculated variables. It is linked to the active Business Analyst dataset and references its data for apportionment and aggregation.

Potential applications

The following are potential applications of custom data in ArcGIS Business Analyst Pro:

Application	Description	Examples of data used
Climate risk assessment	An insurance company sets up FEMA's National Risk Index data to assess localized physical climate risks, such as floods, hurricanes, and wildfires. The company runs a benchmark comparison for all the counties in California to understand how region-specific risks may affect the business they insure. To create this example yourself, see the Set up custom data for infographics tutorial.	FEMA's National Risk Index data
Yard waste collection	A yard waste collection company wants to perform analysis on the number of bags of leaves they pick up from residential areas. They add their pickup data for each block group in their region, and then use a custom apportionment layer containing the number of trees in each block group. They create drive-time areas to calculate how many bags of leaves each driver will pick up.	Layer of leaf pickup data Point layer of trees

Input data and apportionment layers

To successfully create custom data in ArcGIS Business Analyst Pro, you must have the appropriate input data and apportionment layer.

Input data

You can set up polygon data contained in feature classes. For example, you may have a feature class containing county-level hospital admissions data for an entire state. You can add this file and align it with geographic boundaries in Business Analyst to use the patient counts as variables in your analyses.

Input data must be in the form of a file geodatabase containing data in polygons.

Apportionment layers

In addition to valid input data, you must have an apportionment layer to set up custom data. Data apportionment approximates the distribution of any variable (such as sales figures you've mapped) based on the known distribution of another variable, such as population.

An apportionment layer can be either of the following:

• A local dataset (typical)
• An apportionment layer containing points, such as a file geodatabase that was shared with you

Set up polygon data

You can add a polygon feature class and set up its variables as standard geographies or custom polygons. To set up polygon data, do the following:

1. Set the data source in one of the following ways:
   • Select a local Business Analyst dataset as the data source. (typical)
   • Select Custom Data as the data source.

     Tip:

     Use the Custom Data option when you do not have access to a local Business Analyst dataset. This option allows you to use your own point layer as an apportionment layer.

2. On the Analysis tab, click Business Analysis to open the gallery and click New Statistical Data Collection .

   The Create Statistical Data Collection window appears.

3. Use the Input Data drop-down list or click the browse button to select an input feature class. Click OK.

   The input feature class is the polygon data you are bringing in to Business Analyst.

4. Leave the Output Statistical Data Collection name and storage location as the defaults, enter a different name, or click the browse button to select a different storage location.

   The file type for the statistical data collection is .sdcx. This can be helpful to know when locating the file for later use.

5. Click Create.

   The statistical data collection editor window appears; the window's title is the name of the statistical data collection. It contains the following tabs:

   • Source—Contains general information about the data, including the performance index status.
   • Variables—Contains information about variable settings, such as Precision, Field Format, and Apportionment Method.
   • Properties—Allows you to edit the properties of the statistical data collection, including Title, Data Vintage, Author, and Tags. You can also select a custom icon for the statistical data collection.

6. On the Source tab, click the Build Index button to build a performance index.

   Building a performance index is not required, but is recommended to ensure the best performance when using custom data in workflows.

7. Click OK to save all changes.

   The window closes. The Catalog pane appears, and the newly created statistical data collection is displayed.

Set up legacy (.bds) layers

If you are migrating from ArcMap, you might have already set up your custom data as a Business Analyst data source (.bds) file. You can create a statistical data collection directly from the .bds file. To set up data from a .bds file, do the following:

1. Select a local Business Analyst dataset as the data source.
2. On the Analysis tab, click Business Analysis to open the gallery and click New Statistical Data Collection .

   The Create Statistical Data Collection window appears.

3. Click the Import Legacy Data (BDS) button.
4. Under Input Business Analyst Datasource (BDS), click the browse button and select an input .bds file.

   If the .bds file contains dynamic joins or calculations, Business Analyst automatically creates a feature class, which will be the input for the new statistical data collection.

5. Click OK, then click Import.

   The statistical data collection editor window appears; the window's title is the name of the statistical data collection. It contains the following tabs:

   • Source—Contains general information about the data, including the performance index status.
   • Variables—Contains information about variable settings, such as Precision, Field Format, and Apportionment Method.
   • Properties—Allows you to edit the properties of the statistical data collection, including Title, Data Vintage, Author, and Tags. You can also select a custom icon for the statistical data collection.

6. On the Source tab, click the Build Index button to build a performance index.

   Building a performance index is not required, but is recommended to ensure the best performance when using custom data in workflows.

7. Click OK to save all changes.

   The window closes. The Catalog pane appears, and the newly created statistical data collection is displayed.

Edit variables

Once you have created the statistical data collection in Business Analyst, you can use the editor window to configure its variables. Variable configuration settings define how the data is apportioned or calculated, as well as how it is displayed and used in the data browser, infographics, and reports.

Tip:

You can resize the editor window to make the variable table more readable.

To edit one or more variables, do the following:

1. Open the Catalog pane and locate your statistical data collection on the Project tab, under Business Analyst > Statistical Data Collections. Right-click the statistical data collection and select Edit.

   The statistical data collection editor window appears.

2. In the editor window, on the Variables tab, you can edit variables in the following ways:
   • Change a variable's properties directly in the variable table by clicking a cell. For example, you can type a new alias for a variable or use a drop-down list to change the option selected.
   • Double-click a variable in the Field Name column to open the variable's properties window.
   • Right-click a row and select Properties to open the variable's properties window.
   • Select multiple variables by clicking a row, then press Shift while clicking another row. Then right-click the selection and click Properties. Any fields with differing values between variables are not editable in this view.
3. Modify fields by entering text or choosing from the options in the drop-down lists. The fields are as follows:

   Field	Description
   Field Name	The name of the variable. This is not editable.
   Alias	The name of the variable as it appears in the data browser.
   Category	The category within the statistical data collection where this variable appears. You can create a new category; note that this category does not persist in the data browser.
   Vintage	The year this data represents or was created.
   Precision	For supported variable types, set the number of digits after the decimal point. The default is 6 digits.
   Field Format	Set the units to match the type of values in the data: Count (default), Percent, or Currency.
   Summary Type	Define the way aggregated values are summarized for custom data polygons that intersect the area of interest. The summary type affects the options available for the Weight and Apportionment Method fields. Sum (default)—Adds the aggregated values. You cannot change the Weight field, which is set to NONE. You can select a variable from the local data source or apportionment layer (such as a population variable) or GEOM as the apportionment method. Selecting GEOM uses the geometric area of geographies to apportion custom data. Avg—Calculates the average of the aggregated values, omitting null values. You can set the Weight field to AREA or another variable from the input data. You cannot change the Apportionment Method field, which is set to NONE.
   Weight	Define the field used to calculate the weighted sum, either AREA or another variable from the input data. This parameter is editable only when Summary Type is set to Avg. When Avg is not selected, NONE is automatically selected for Weight.
   Apportionment Method	Set the apportionment method for custom data polygons that intersect, but do not match exactly, the area of interest. The apportionment options vary, depending on the local dataset or apportionment layer you are working with.
   Output Type	Displays the variable type, such as Double. This is not editable.

4. When you are done editing, click OK.

   The properties of the selected variables are modified and saved to the statistical data collection.

Add variables from the data browser

You may want to add Business Analyst variables to a statistical data collection, either for convenience or to use them to create calculated variables. To add variables from the data browser, do the following:

1. Open the Catalog pane and locate your statistical data collection on the Project tab, under Business Analyst > Statistical Data Collections. Right-click the statistical data collection and select Edit.

   The statistical data collection editor window appears.

2. In the editor window, on the Variables tab, click the Add button to open the data browser and select variables.

   From the data browser, you can search and browse for data by category, from custom data, saved variable lists, and from data you have saved as favorites.

3. Click OK to add the variables.

   The variables are added to the statistical data collection.

Create calculated variables

You can build custom variables by using Python calculations to combine existing statistical data collection variables, Business Analyst data, or some combination of the two. For example, you can create custom per-capita variables, as well as density variables such as sales density or household density. Custom expressions can be a simple calculation based on a single field, combinations of two or more existing fields, or a complex Python script.

Once created, the custom variable can be saved as a label expression file (.lxp) in the statistical data collection, and can be imported and exported to share with other users. To create a custom calculated variable, do the following:

1. Open the Catalog pane and locate your statistical data collection on the Project tab, under Business Analyst > Statistical Data Collections. Right-click the statistical data collection and select Edit.

   The statistical data collection editor window appears.

2. In the editor window, on the Variables tab, click the Add Calculation button.

   The Calculate Variable window appears.

3. Build a calculation in the Expression field, then click the Verify button to verify the expression.

   For instructions on building calculations using Python, visit Calculate Field Python examples.

   Note:

   Custom calculations and scripts support double, string, and integer field types. For example, specifying a string field allows flexibility to output textual descriptions, such as displaying Dominant Tapestry Name, attribute properties, or a street name. To learn more, see ArcGIS field data types.

4. Provide a name and alias for the new variable in the Name and Alias fields.
5. Click OK.

   The new Calculated Variable field is added to the statistical data collection.

6. To modify the calculated variable, do any of the following:
   • To edit the calculation, select the Calculated Variable field and click Edit Calculation or right-click the field and click Edit Calculation.
   • To modify the variable's properties, right-click the field and click Properties and edit the Vintage, Field Format, or Category field.
   • To remove the calculated variable, select the field and click Delete.

Custom data notes and best practices

The following notes provide guidance on statistical data collections, including how they are stored, used, and managed:

• By default, custom data is stored in the project's home folder. If the statistical data collection is stored in this default location, it is accessible only in the project it was created in.
• Custom data is linked to the Business Analyst data source that was used to create it. You must be connected to this data source to use the statistical data collection.
• While it is possible to select an online layer, such as one from ArcGIS Living Atlas or ArcGIS Online, as a custom apportionment layer, it is not a best practice. Custom apportionment layers should be loaded locally in your project to build sustainable statistical data collections. Where possible, make a local copy of the data to use for apportionment.

Geoprocessing tools

The custom data workflow uses the Generate SDCX Index tool to create a performance index. You can use this geoprocessing tool to build a performance index directly in ArcGIS Pro, or as part of a Python script or a model. When using custom data, building an index is recommended for optimal performance.

To create an index for a statistical data collection, do the following:

1. On the Analysis tab, in the Geoprocessing group, click Tools.

   The Geoprocessing pane appears.

2. On the Toolboxes tab, in the Business Analyst Tools section, expand the Statistical Data Collections toolset and click Generate SDCX Index.

   The Generate SDCX Index tool opens in the Geoprocessing pane.

3. Click the Browse button to open the Input SDCX File dialog box and choose an existing .sdcx file from other projects or folders.
4. Click Run.