Overview

The CData Python Connector for Google Ads models Google Ads entities in relational views and stored procedures. The provided views will give you access to your Google Ads data using the Google Ads API. The CData CData Python Connector for Google Ads for Google Ads models Google Ads entities in relational views and stored procedures. The provided views give you access to your Google Ads data using the Google Ads API.

Key Features

• The 本製品 models Google Ads entities like documents, folders, and groups as relational views, allowing you to write SQL to query Google Ads data.
• Stored procedures allow you to execute operations to Google Ads.
• Predefined Report views to make access to data easier.
• Live connectivity to these objects means any changes to your Google Ads account are immediately reflected when using the 本製品.

Views

ビュー describes the available views. Two types of views are made available:

• Base Views are statically defined to model Campaigns, AdGroups, Customers, and more. They are used to create your custom reports instead of being used standalone. By default. these views return data from all time aggregated into a single row.
• Predefined Report Views are a set of standard reports that mimic exactly what you see in the Google Ads UI. All Predefined Report Views have "report" appended to their name. By default, these views return data from all time with a daily breakdown.

The Resources view shows the names of the resources, attribute resources and segmenting resources, which you need for the CreateReportSchema stored procedure.

Stored Procedures

ストアドプロシージャ are function-like interfaces to Google Ads. They allow you to execute operations to Google Ads, the most important being CreateReportSchema, which is used to create views from resources (like 'distance_view') with attribute resources (like 'customer' in this case) and segmenting resources (like 'campaign' in this case).

Date Ranges and Aggregation

All tables and views support date ranges and aggregation.

Date Ranges

Date ranges can be defined in the WHERE clause using the Date field using =, <,>, between delimiters.

Additional predefined date fields are available, specifically:

• week
• month
• quarter

When filtering on these, you can use the = operator with the date set to the first day of the time period. If you specify a different date, an error is returned.

For example, to specify the month of May in the year 2022, use the following condition, specifying the first day of that month:

month = '2022-05-01'

Aggregation

Aggregation can be applied at multiple levels:

“Date” returns daily data in the query results. For example,

SELECT CampaignBaseCampaign, CampaignName, CampaignStartDate, CampaignEndDate , Impressions, Clicks, "Date" FROM CData.GoogleAds.Campaign WHERE "Date" BETWEEN '2022-01-01' and '2023-01-31' and CampaignId = '17999934124'

“Hour” returns data aggregated by hour across the date range selected. For example, querying two years of data and selecting “Hour” returns 24 rows of data (one for each hour) with two years of data aggregated for each hour.

“DayofWeek” returns data aggregated by week across the date range selected. For example, querying two years of data and selecting “DayOfWeek” returns seven rows of data (one for each day) with two years of data aggregated for each day.

“Week” returns data aggregated by week across the date range selected. For example, querying two years of data and selecting “Week” returns 104 rows of data (one for each week) with data aggregated for each week.

“Month” returns data aggregated by month across the date range selected. For example, querying two years of data and selecting “Month” returns 24 rows of data (one for each month) with data aggregated for each month.

“MonthofYear” returns data aggregated by month across the date range selected. For example, querying two years of data and selecting “MonthofYear” returns 12 rows of data (one for each month) with two years of data aggregated for each month.

“Quarter” returns data aggregated by quarter across the date range selected. For example. querying two years of data and selecting “Quarter” return eight rows of data (one for each quarter). Note that a Quarter is defined as starting on the 1st of the month of January, April, July, and October.

“Year” returns data aggregated by year across the date range selected. For example, querying two years of data and selecting “Year” returns two rows of data (one for each year) with data aggregated by year.

NOTE: Selecting "Date" overrides any other date metric. It always returns daily data only.