My Sources page allows you to view and manage all data sources that you’ve used in your Wrangler workspace. It will show you all your sources - whether they are files you uploaded to Wrangler or data sources created from the Data Catalog.

My Sources page is accessible directly from Wrangler’s main menu.

My Sources screen is split into two halves - the left half provides an overview of all the sources you’ve already created while the right half allows you to view details and manage the source you select.

The table showing all sources provides basic information for each source:

Additional actions are available when you hover over each item in the table or by clicking on the three-dot menu for each item.

When you select a source in the table, the right half of the screen will show you additional details about that source including data preview. It will also allow you to edit its configuration.

To edit the configuration, click on the Edit button in the Configuration section. This will open a dialog that will allow you to change the parameters of your data source.

The exact layout of this dialog will depend on the source type: you will either get the CSV data source settings dialog or the dialog to configure the data source connector provided by a library similar to one in Add to My Sources wizard.

There are several ways to add data sources to My Sources:

When adding data source connectors, the Add to My sources wizard opens to allow you to configure settings for your data source. The dialog will look different for each data source since it shows the parameters for that specific data source. If a data source settings is updated, a warning will be displayed to remind you to reload preview data to reflect the changes in the data preview.

To update the data source in an existing job, click on the Source button in the overview diagram of your job at the top of the transformation editor screen or click on the icon which appears when you hover over the Source step.

You will be redirected to a page listing all your sources added to your My Sources page. Select a new source by performing one of the following:

After performing one of these steps, you will be asked to confirm the data source change.

Wrangler allows you to use custom data source connectors that are created, managed and maintained by your CloverDX Server administrators and IT. These connectors can read data from any data source such as a database or a third-party interface.

The CSV data source allows you to read data from CSV files uploaded to your Wrangler workspace.

When you want to create a new CSV data source, you can do so either from My Sources or directly from the Create a new job screen. In both cases, you can simply upload a file by dragging & dropping it or by selecting the file on your computer.

Once a file is uploaded, the CSV connector will scan your data and automatically determine the data structure. The algorithm looks at a sample of data at the beginning of the file to determine the columns and their data types.

You will be able to see the preview of your data to verify that the automatically determined file structure matches your expectations. You can read more about data types available in Wrangler in the Data types section.

The Excel data source allows you to read data from Excel .xlsx or .xls files uploaded to your Wrangler workspace.

When you want to create a new Excel data source, you can do so either from My Sources or directly from the Create a new job screen. In both cases, you can simply upload a file by dragging & dropping it or by selecting the file on your computer.

Once a file is uploaded, the Excel connector will scan data from the first sheet and automatically determine the data structure. The algorithm looks at a sample of data at the beginning of the file to determine the columns and their data types. You can read more about data types available in Wrangler in the Data types section.

My Targets page allows you to view and manage all data targets that you’ve used in your Wrangler workspace. It will show you all your targets - whether they are files or data targets created from the Data Catalog.

My Targets page is accessible directly from Wrangler’s main menu.

The table showing all targets provides basic information for each target:

When you select a target in the table, the right half of the screen will show you additional details about that target, as well as allow you to edit its configuration.

To edit the configuration, click on the Edit button in the Configuration section. This will open a dialog that will allow you to change the parameters of your data target. The exact layout of this dialog will depend on the target type:

There are several ways to add data targets to My Targets:

To update the data target in an existing job, click on the Target button in the overview diagram of your job at the top of the transformation editor screen or click on the icon which appears when you hover over the Target step.

You will be redirected to a page listing all your targets added to your My Targets page. Select a new target by performing one of the following:

After performing one of these steps, you will be asked to confirm the data target change.

Some data target connectors may require data in certain format - they may have required columns and their data types. This is most often used to ensure that all required data gets to the target system. For example, when writing to a CRM like Salesforce, you most likely will see that the person’s name is required.

Such data targets will require mapping - a transformation from your data layout to the data layout required by the target. Mapping is always done at the end of the job and is clearly shown in the step list.

If your selected data target requires mapping, a Mapping step will appear above the Target step. The Mapping step allows you to assign which columns from your data at the end of the job get assigned to which columns in the target. The Mapping step will display the number of currently mapped vs. mappable fields, including a note about how many fields are required.

To edit the mapping, click on the Mapping step (or on the little pencil next to the step). The view will switch to Mapping mode which will display preview of your data as well as Mapping editor.

In the Mapping editor you can link your dataset preview columns to specific data target connector columns. The target columns are listed on the right side, and the mapping is performed on the left side in the Preview column section. You can easily tell which columns are required: required columns are highlighted to distinguish them from optional columns.

There are multiple ways to map columns:

You can freely combine automapping with drag & drop mapping for maximum effectivity.

Your mapping changes are saved automatically - you’ll see a little status notification about this at the top of the mapping editor.

You can use the Search mapping in the mapping editor to display just the columns that contain your search term in their name. The search returns results from both the Preview and Target columns.

You can also use advanced search by clicking on the funnel icon on the right side to filter based on the mapping status (Required, Optional, Unmapped, Mapped, With error). The text under the Search mapping field will keep you informed about how many columns out of the total number of columns are currently displayed.

Note that the mapped columns need to have the same data type as the target column - mapping will not perform any type conversions for you. The target column data type is indicated by an icon next to the column name, and you can also see it in the tooltip which appears when you hover over it. If the data types do not match, the mapping is considered invalid. If your job includes invalid mapping, the job run will fail.

When a column is mapped, an icon appears above its column name in the transformations editor to indicate that the column is linked to a target column. If the mapping is successful, you will see a blue "link" icon . If the mapping of this column is invalid (e.g., the data types do not match), you will see an error icon .

When you click on any of these icons, the Mapping editor opens.

To unmap a column, hover over the desired column in the Preview column section, and click on the X button, or, to quickly unmap all columns, use the Unmap button in the Mapping editor.

The Mapping editor keeps track of all the mapped, unmapped, required, and optional fields, as well as the number of errors. It also automatically adjusts the numbers when you make a change. The Mapping step displays the overview as well.

When files are written by Wrangler, they are stored in your workspace. You can download your files from Wrangler user interface from the My Jobs screen by clicking on the Download result button:

Wrangler offers an option to produce a reject file: a file which stores information about rows which contained errors. Reject files can be written in two different formats - a CSV file (for CSV data target) or XLSX file (for Excel data target). In both cases, the information in the file is the same and the only difference is the file format itself. The file provides information about why each row was rejected, including the data in the rejected row at the end of the transformation. For more information see Errors and output.

The reject file contains one row for each rejected row. Since there can be multiple errors in each row, all errors for given row are collected in the single reject file row.

Besides the error details, the reject file also contains the data that was rejected. The data is all stored as string columns to ensure that invalid values can be written to the reject file as well.

The reject file contains the following columns:

Wrangler allows you to use data target connectors that are created, managed, and maintained by your CloverDX Server administrators. These connectors can be found in the Data Catalog, from where you can choose to add them to My Targets and use them in your jobs.

For steps on how to add an existing data target connector from the Data catalog to My Targets, refer here.

These target connectors do not generate an output file; instead, they write data directly to a configured external target within the connector, such as a database or a third-party interface. Depending on the connector’s design, certain target connectors may require mapping your transformed data into the target structure. For further details, refer to the target mapping section.

CSV data target allows you to write your data into CSV files that are stored in your Wrangler workspace. To change your data target settings, click on the Target button in the overview diagram of your job at the top of the transformation editor screen or click on the icon which appears when you hover over the Target step.

A page listing all the targets added to your My Targets will appear. Your currently used target will be automatically selected and its details displayed on the right side. To change the configuration of your CSV file, click on the Edit button next to Configuration.

To select a different target, select the desired target from the list, click on the Select ⟶ button, and confirm your changes.

Excel data target allows you to write your data into Microsoft Excel files in the XLSX format. The target produces a file with one sheet and a header. Formatting of data in the output file will follow the formatting configured for columns in your Wrangler job.