SELECT account_performance_report."customer.descriptive_name" AS "account_performance_report.customer_descriptive_name" , avg(account_performance_report."metrics.active_view_cpm") AS "account_performance_report.active_view_cpm_avg" , avg(account_performance_report."metrics.search_budget_lost_impression_share") AS "account_performance_report.search_budget_lost_impression_share_" FROM "your-username~google-ads".account_performance_report GROUP BY 1 ORDER BY 1
Here are all the tables you will be able to access when you use Splitgraph to query Google Ads data. We have also listed some useful queries that you can run.
repositories: - namespace: CHANGEME repository: airbyte-google-ads # Catalog-specific metadata for the repository. Optional. metadata: readme: text: Readme description: Description of the repository topics: - sample_topic # Data source settings for the repository. Optional. external: # Name of the credential that the plugin uses. This can also be a credential_id if the # credential is already registered on Splitgraph. credential: airbyte-google-ads plugin: airbyte-google-ads # Plugin-specific parameters matching the plugin's parameters schema params: customer_id: 6783948572,5839201945 # REQUIRED. Customer ID(s). Comma separated list of (client) customer IDs. Each customer ID must be specified as a 10-digit number without dashes. More instruction on how to find this value in our <a href="https://docs.airbyte.com/integrations/sources/google-ads#setup-guide">docs</a>. Metrics streams like AdGroupAdReport cannot be requested for a manager account. start_date: '2017-01-25' # REQUIRED. Start Date. UTC date and time in the format 2017-01-25. Any data before this date will not be replicated. normalization_mode: basic # Post-ingestion normalization. Whether to normalize raw Airbyte tables. `none` is no normalization, `basic` is Airbyte's basic normalization, `custom` is a custom dbt transformation on the data.. One of none, basic, custom normalization_git_branch: master # dbt model Git branch. Branch or commit hash to use for the normalization dbt project. end_date: '2017-01-30' # End Date (Optional). UTC date and time in the format 2017-01-25. Any data after this date will not be replicated. custom_queries: # Custom GAQL Queries (Optional). - query: SELECT segments.ad_destination_type, campaign.advertising_channel_sub_type FROM campaign WHERE campaign.status = 'PAUSED' # REQUIRED. Custom Query. A custom defined GAQL query for building the report. Should not contain segments.date expression because it is used by incremental streams. See Google's <a href="https://developers.google.com/google-ads/api/fields/v11/overview_query_builder">query builder</a> for more information. table_name: '' # REQUIRED. Destination Table Name. The table name in your destination database for choosen query. login_customer_id: '7349206847' # Login Customer ID for Managed Accounts (Optional). If your access to the customer account is through a manager account, this field is required and must be set to the customer ID of the manager account (10-digit number without dashes). More information about this field you can see <a href="https://developers.google.com/google-ads/api/docs/concepts/call-structure#cid">here</a> conversion_window_days: 14 # Conversion Window (Optional). A conversion window is the period of time after an ad interaction (such as an ad click or video view) during which a conversion, such as a purchase, is recorded in Google Ads. For more information, see Google's <a href="https://support.google.com/google-ads/answer/3123169?hl=en">documentation</a>. tables: sample_table: # Plugin-specific table parameters matching the plugin's schema options: airbyte_cursor_field:  # Cursor field(s). Fields in this stream to be used as a cursor for incremental replication (overrides Airbyte configuration's cursor_field) airbyte_primary_key_field:  # Primary key field(s). Fields in this stream to be used as a primary key for deduplication (overrides Airbyte configuration's primary_key) # Schema of the table, a list of objects with `name` and `type`. If set to ``, will infer. schema:  # Whether live querying is enabled for the plugin (creates a "live" tag in the # repository proxying to the data source). The plugin must support live querying. is_live: false # Ingestion schedule settings. Disable this if you're using GitHub Actions or other methods # to trigger ingestion. schedule: credentials: airbyte-google-ads: # This is the name of this credential that "external" sections can reference. plugin: airbyte-google-ads # Credential-specific data matching the plugin's credential schema data: credentials: # REQUIRED. Google Credentials. developer_token: '' # REQUIRED. Developer Token. Developer token granted by Google to use their APIs. More instruction on how to find this value in our <a href="https://docs.airbyte.com/integrations/sources/google-ads#setup-guide">docs</a> client_id: '' # REQUIRED. Client ID. The Client ID of your Google Ads developer application. More instruction on how to find this value in our <a href="https://docs.airbyte.com/integrations/sources/google-ads#setup-guide">docs</a> client_secret: '' # REQUIRED. Client Secret. The Client Secret of your Google Ads developer application. More instruction on how to find this value in our <a href="https://docs.airbyte.com/integrations/sources/google-ads#setup-guide">docs</a> refresh_token: '' # REQUIRED. Refresh Token. The token for obtaining a new access token. More instruction on how to find this value in our <a href="https://docs.airbyte.com/integrations/sources/google-ads#setup-guide">docs</a> access_token: '' # Access Token (Optional). Access Token for making authenticated requests. More instruction on how to find this value in our <a href="https://docs.airbyte.com/integrations/sources/google-ads#setup-guide">docs</a> normalization_git_url: '' # dbt model Git URL. For `custom` normalization, a URL to the Git repo with the dbt project, for example,`https://uname:email@example.com/organisation/repository.git`.
Use our splitgraph.yml format to check your Splitgraph configuration into version control, trigger ingestion jobs and manage your data stack like your code.
Splitgraph connects your vast, unrelated data sources and puts them in a single, accessible place.
Splitgraph handles data integration, storage, transformation and discoverability for you. All that remains is adding a BI client.
Focus on building data-driven applications without worrying about where the data will come from.
Splitgraph supports data ingestion from over 100 SaaS services, as well as data federation to over a dozen databases. These are all made queryable over a PostgreSQL-compatible interface.
Splitgraph stores data in a columnar format. This accelerates analytical queries and makes it perfect for dashboards, blogs and other read-intensive use cases.
Read more about Splitgraph’s support for Google Ads, including its documentation and sample queries you can run on Google Ads data with Splitgraph.
Splitgraph has a PostgreSQL-compatible endpoint that most BI clients can connect to.