Create a Data Source

1. The first step in building a NinjaCat Data Cloud dataset is accessing a Data Provider by creating a Data Source. Follow the instructions in this linked article to Add a Direct Network Connection

2. The next step after adding a Data Source is adding a Single Data Source Connection to a NinjaCat Account

Associate an Existing Network Connection with a Dataset

If you have already added a native data source connection (such as Simpli.fi, or any other compatible provider), you can associate it with a Data Cloud dataset directly from the Network Settings page. This is an alternative to the Data Cloud → Connect → Add Data Source flow described below.

Steps

1. Go to Setup Settings and locate the network connection you want to associate with a dataset
2. Click on the network connection to open its Network Settings
3. Find the compatibility group that is enabled for your connection
4. Click the "Associate with dataset" button on the compatibility group

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When to Use This Method

This approach is especially useful for data providers that support dataset association through Network Settings but may not appear in the Data Cloud "Add Data Source" connector list. For example, Simpli.fi can be associated with a dataset using this method. If you cannot find a provider in the Data Cloud connector list, check whether it can be associated via its Network Settings page instead.

Once associated, the dataset will appear in your Data Cloud datasets list, where you can customize fields, apply transformations, and combine it with other datasets.

Add Credentials

3. After clicking on "Data Cloud" click on the "Connect" subheading

4. Click on the "Add Data Source" button near the upper right

5. Click on the desired Data Provider

6. Click on the "Name" field and type in a unique name

7. Click on "Add Credentials" near the middle

8. Click on the desired Data Network from the list

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The Dataset you want to build may require data from multiple data sources. Repeat steps 7 and 8 to add any more desired data sources to this Dataset.

9. Click the "Save Connector" button near the bottom right

Add a Dataset

10.  Click "Add Dataset" near the bottom center

11. Click on the disclosure arrow on the right side of each line item to see the list of specific data columns included in the dataset line item

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NinjaNote: When viewing the lists of fields hovering over the information icon will revel the API name for the field.

12. Click on the radio button on the left side of the desired line item to select it (only one item can be selected)

13. Click the "Next" button near the bottom right

14. On the following page, you are able to add a specific name for this new dataset and set the backfill date to define the earliest data available in the set

15. If the profile you selected by clicking on its radio button is all you need with no alterations, you can move on to the next step by clicking the button in the bottom right labeled "Save & Import Data"

16. Click "Customize Fields" near the center of the page to start the process of adding and removing fields from your selected profile

Customize Fields

The Customize Fields page displays all the available fields delivered by the provider you selected in the Create a Data Source step.

1. Uncheck the boxes of any fields you want to omit

2. Check the box for any field you want to add to your profile

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The fields are divided into two lists. One for dimensions and one for metrics. Each list has a search bar at the top, allowing for the filtering of the lists by typing.

Combine Datasets

1. Click on "Data Cloud" in the menu bar

2. Click on the "Datasets" subheading

3. Click on the "Combine Datasets" button in the top right

4. Type a name for the combined set

5. Select the first desired data set from the first drop-down

6. Continue selecting up to twenty (20) total datasets to combine

7. When you're done selecting datasets click the "Save and Preview" button near the right

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The result will be displayed in the dataset explorer. The system will find ways to combine columns that it believes are related using two methods:

• First, the system will use our existing Aggregate Metric and Dimension definitions to identify columns that are related. For example, suppose we know that a column is the Aggregate Campaign on two different data sources. In that case, we'll automatically combine those columns into a single column in the unified data set.
• Additionally, if a source dataset column isn't tagged with a shared definition, it will attempt to combine fields that have the same name. This will assist with datasets that are not fully mapped (custom-mapped sources) or for common dimensions and metrics but are not part of our standard Aggregate Metrics and Dimensions.