Load Bing Ads data to DuckDB

Microsoft Advertising (Bing Ads) is a platform that provides programmatic access to advertising campaign management through a JSON REST API. Everything needed to build a working Bing Ads → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your Bing Ads to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from Bing Ads to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the Bing Ads API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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Bing Ads API at a glance

These values come from the Bing Ads API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Bing Ads API?

All requests require an 'Authorization: Bearer {token}' header. Additionally, requests must include a 'DeveloperToken' header to identify the developer account.

1. Get your credentials

To obtain API credentials for Microsoft Advertising (formerly Bing Ads), you must perform two main setup processes: 1) Obtain a Developer Token and 2) Register an application for OAuth 2.0 authentication. First, get your Developer Token by navigating to the Microsoft Advertising web interface at https://ads.microsoft.com/cc/Settings/DevSettings. Sign in with Super Admin credentials, select your account, and click 'Request Token'. Second, set up OAuth 2.0 via the Microsoft Entra ID (formerly Azure AD) portal at https://portal.azure.com: 1. Go to 'App registrations' and select 'New registration'. 2. Choose 'Any Entra ID Tenant + Personal Microsoft accounts' for supported account types. 3. After registration, save the 'Application (client) ID'. 4. Under 'Certificates & secrets', create a new client secret and copy its value immediately (it will not be visible again). 5. Configure the Redirect URI (e.g., http://localhost:8080) in your app's 'Authentication' settings. Finally, use your Client ID, Client Secret, and Developer Token to perform the OAuth flow (authorization code grant) to generate the required Access and Refresh tokens for API requests.

2. Add them to .dlt/secrets.toml

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[sources.bing_ads_source]
developer_token = "your_developer_token_here"
client_id = "your_application_client_id_here"
client_secret = "your_client_secret_here"
refresh_token = "your_oauth_refresh_token_here"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What Bing Ads data can I load into DuckDB?

These are the Bing Ads endpoints dlt can load into DuckDB:

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How do I load only new Bing Ads records?

Bing Ads exposes Index on CustomerManagement/v13/SearchAccounts, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "accounts", "endpoint": {
    "path": "CustomerManagement/v13/SearchAccounts",
    "data_selector": "Accounts",
    "incremental": {"cursor_path": "Index", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated Bing Ads pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading AuthenticationToken and DeveloperToken from the Bing Ads API into DuckDB:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def bing_ads_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://campaign.api.bingads.microsoft.com",
            "auth": {"type": "bearer", "token": access_token},
        },
        "resources": [
            {"name": "accounts", "endpoint": {"path": "CustomerManagement/v13/SearchAccounts", "data_selector": "Accounts"}},
            {"name": "customers", "endpoint": {"path": "CustomerManagement/v13/SearchCustomers", "data_selector": "Customers"}}
        ],
    }
    yield from rest_api_resources(config)


def load_bing_ads_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="bing_ads_pipeline",
        destination="duckdb",
        dataset_name="bing_ads_data",
    )
    load_info = pipeline.run(bing_ads_source())
    print(load_info)


if __name__ == "__main__":
    load_bing_ads_to_duckdb()

Run it with python bing_ads_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query Bing Ads data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("bing_ads_pipeline").dataset()
df = data.accounts.df()
print(df.head())

SQL:

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SELECT * FROM bing_ads_data.accounts LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the Bing Ads to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw Bing Ads loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load Bing Ads data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack