Applying Data Mapping to a datastream

This guide explains how to apply Data Mapping to a datastream so that it conforms to your unified naming and formatting conventions in Adverity.

Introduction

Data Mapping maps source fields to target fields in a datastream to apply standard naming conventions. This enables you to easily compare similar data from different data sources. Only mapped fields can be loaded into Adverity Data Storage or a destination.

Adverity automatically maps source fields for which Default Data Mapping is defined.

For example, total cost is called spend in Facebook Ads and cost in Google Ads. In this case, spend and cost are source fields. You can create the costs target field in Adverity and map both source fields to this target field. As a result, both of these source fields will be displayed using the field name costs in Adverity.

Once you have mapped your source fields to target fields, you can view the target fields in your Data Dictionary.

This guide explains how to configure basic Data Mapping for your datastreams. For more information on configuring advanced Data Mapping, see Configuring advanced Data Mapping.

Prerequisites

Before you complete the procedure in this guide, perform all of the following actions:

• Create a datastream.

• Fetch data for the datastream.

Viewing current Data Mapping

To view the Data Mapping currently applied to your datastream, follow these steps:

1. Select the workspace you work with in Adverity and then, in the platform navigation menu, click Datastreams.

2. Open the chosen datastream by clicking on its name.

3. In the top navigation panel, click Data Mapping.

In the Data Mapping, the Source field column displays the original name of each source field. The Target field column displays the field that you want to use instead of the source field. When you apply the Data Mapping, Adverity maps each source field to the chosen target field.

The values in the Target field column indicate the following:

• A green field name in the Target field column means that the source field is mapped to a metric.

• A blue field name in the Target field column means that the source field is mapped to a dimension.

• An empty value in the Target field column means that the source field is unmapped. Unmapped fields are not loaded into Adverity Data Storage or your destination.

Applying custom Data Mapping

To apply custom Data Mapping to your datastream, follow these steps:

1. Select the workspace you work with in Adverity and then, in the platform navigation menu, click Datastreams.

2. Open the chosen datastream by clicking on its name.

3. In the top navigation panel, click Data Mapping.

4. In the Target field column, for each field you want to map in the Source field column, enter the name of the target field and select the target field from the drop-down list.

   If the field does not appear in the drop-down list, click + Create new to create a new target field. For more information about creating new target fields, see Mapping a source field to a new target field.

Video guide: How to set up Data Mapping and Data Dictionary

This video guide explains what Data Mapping is, how to map your fields in Adverity, and how to use the Data Dictionary.

What’s next?

After collecting and harmonizing your data, load your data into Adverity Data Storage or an external destination to further process the data.