Raw Data Report

This pipeline can be used to request and retrieve raw data reports from the Google Analytics 4 API. You may also use filters to return rows matching certain conditions.

Not all dimensions and metrics can be queried together. Only certain dimensions and metrics can be used together to create valid combinations. Our connector setup form will ensure combinations are valid. However, checking yourself beforehand will avoid any surprises.

Use these Google resources to pick your metrics and dimensions:

  1. Review dimension or metric description with Dimensions & Metrics Explorer.

  2. Use the GA4 Query Explorer to review the report yielded by a given combination of dimensions and metrics.

Configuring the Credentials

Select the account credentials which has access to relevant Google Analytics data from the dropdown menu & Click Next

Credentials not listed in dropdown ?

Click on + Add New for adding new credentials

Data Pipelines Details

Data Pipeline

Select Raw Data Report from the dropdown

Account

Select one or more accounts from the drop-down

All accounts which your credentials have access to should be available here. If they are not, please check the credentials selected / configured by you. While you can add multiple accounts, the table size may become too large and so it is advisable to add one account per pipeline and use Union queries in the data warehouse to join the data for consumption
Property

An account can have one or more properties. Select the desired property as per the requirement.

Dimensions and Metrics

Select the dimensions and metrics you would like to fetch from the Google Analytics platform. You can click on View Schema anytime to see the schema of the table being created.For more details about dimensions and metrics go here

Each of the selected dimension / metric will create one or more columns in the database table in the destination warehouse.

Setting Parameters

Parameter Description Values

No of Days

Required

Number of days for which you wish to get the data in each run.

Integer value (Recommended value 2)

Insert Mode

Required

Specifies the manner in which data will get updated in the data warehouse : UPSERT will insert only new records or records with changes, APPEND will insert all fetched data at the end, REPLACE will drop the existing table and recreate a fresh one on each run.

{Upsert, Append, Replace}

Default Value: UPSERT

Advanced Options

Parameter Description Values

Dimension Filters

_Optional

Select the dimension and the filter you would like to apply to this dimension to return data for specific dimension values.

{EXACT, BEGINS_WITH, ENDS_WITH, CONTAINS, FULL_REGEXP, PARTIAL_REGEXP, N_LIST_FILTER}

Metric Filters

_Optional

Select the metric and the filter you would like to apply to this metric to return data for specific metric values.

{EQUAL, LESS_THAN, LESS_THAN_OR_EQUAL, GREATER_THAN, GREATER_THAN_OR_EQUAL}

Keep Empty Rows

_Optional

Specify if you wish to recieve a data row with all metrics as zero. FALSE will remove each row with all metrics equal to zero and TRUE will return rows with zero as well (in case they are not separately removed by a filter).

{TRUE, FALSE}

Currency Codes

_Optional

Specify if you wish to keep the currency code as the account’s default or to any other such as "AED", "USD", "JPY". The currency codes are in ISO4217 format.

{TRUE, FALSE}

Datapipeline Scheduling

Scheduling specifies the frequency with which data will get updated in the data warehouse. You can choose between Manual Run, Normal Scheduling or Advance Scheduling.

Manual Run

If scheduling is not required, you can use the toggle to run the pipeline manually.

Normal Scheduling

Use the dropdown to select an interval-based hourly, monthly, weekly, or daily frequency.

Advance Scheduling

Set schedules fine-grained at the level of Months, Days, Hours, and Minutes.

Detailed explanation on scheduling of pipelines can be found here

Dataset & Name

Dataset Name

Key in the Dataset Name(also serves as the table name in your data warehouse).Keep in mind, that the name should be unique across the account and the data source. Special characters (except underscore _) and blank spaces are not allowed. It is best to follow a consistent naming scheme for future search to locate the tables.

Dataset Description

Enter a short description (optional) describing the dataset being fetched by this particular pipeline.

Notifications

Choose the events for which you’d like to be notified: whether "ERROR ONLY" or "ERROR AND SUCCESS".

Once you have finished click on Finish to save it. Read more about naming and saving your pipelines including the option to save them as templates here

Still have Questions?

We’ll be happy to help you with any questions you might have! Send us an email at info@datachannel.co.

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