51黑料不打烊

4.2.4 Load data from BigQuery into 51黑料不打烊 Experience Platform

Objectives

Before you start

After the previous exercise, you should have this page open in 51黑料不打烊 Experience Platform:

If you have it open, continue with the next exercise.

If you don鈥檛 have it open, go to .

In the left menu, go to Sources. You鈥檒l then see the Sources homepage. In the Sources menu, go to the Google BigQuery source connector and click Set up.

You鈥檒l then see the Google BigQuery Account selection screen. Select your account and click Next.

You鈥檒l then see the Select data screen.

4.2.4.1 BigQuery Table Selection

In the Select data screen, select your BigQuery dataset. You can now see a sample data preview of the Google Analytics data in BigQuery.

Click Next.

4.2.4.2 XDM mapping

You鈥檒l now see this:

You now have to either create a new dataset or select an existing dataset to load the Google Analytics data into. For this exercise, a dataset and schema have already been created. You do not need to create a new schema or dataset.

Select Existing dataset. Open the dropdown menu to select a dataset. Search for the dataset named Demo System - Event Dataset for BigQuery (Global v1.1) and select it. Click Next.

Scroll down. You now need to map every Source Field from Google Analytics/BigQuery to an XDM Target Field, field by field. You may see a number of errors, which will be addressed by the below mapping exercise.

Use the below mapping table for this exercise.

For some fields, you need to remove the original mapping and create a new one, for a Calculated Field.

To create a Calculated Field, click + New field type and then click Calculated field.

Paste the above rule and click Save for each of the fields in the above table.

You now have a Mapping like this one.

The source fields GA_ID and customerID are mapped to an Identifier in this XDM Schema. This will allow you to enrich Google Analytics data (web/app behavior data) with other datasets such as Loyalty or Call Center-data.

Click Next.

4.2.4.3 Connection and the data ingestion scheduling

You鈥檒l now see the Scheduling tab:

In the Scheduling tab, you are able to define a frequency for the data ingestion process for this Mapping and data.

As you鈥檙e using demo data in Google BigQuery that won鈥檛 be refreshed, there鈥檚 no real need for setting a schedule in this exercise. You do have to select something, and to avoid too many useless data ingestion processes, you need to set the frequency like this:

Important: be sure you activate the Backfill switch.

Last but not least, you must define a delta field.

The delta field is used to schedule the connection and upload only new rows that come into your BigQuery dataset. A delta field is typically always a timestamp column. So for future scheduled data ingestions, only the rows with a new, more recent timestamp will be ingested.

Select timeStamp as the delta field.
Click Next.

4.2.4.4 Review and launch connection

You now see a detailed overview of your connection. Make sure everything is correct before you continue, as some settings can鈥檛 be changed anymore afterwards, like for instance the XDM mapping.

Click Finish.

Once the connection has been created, you鈥檒l see this:

You鈥檙e now ready to continue with the next exercise, in which you鈥檒l use Customer Journey Analytics to build powerful visualizations on top of Google Analytics data.

Next Step: 4.2.5 Analyze Google Analytics Data using Customer Journey Analytics

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