Load Dow Jones Risk and Compliance data to DuckDB

Dow Jones Risk & Compliance APIs provide programmatic access to global risk screening, monitoring, and entity search data for compliance workflows. Everything needed to build a working Dow Jones Risk and Compliance → 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 Dow Jones Risk and Compliance 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 Dow Jones Risk and Compliance 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 Dow Jones Risk and Compliance 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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Dow Jones Risk and Compliance API at a glance

These values come from the Dow Jones Risk and Compliance API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Dow Jones Risk and Compliance API?

The API uses OAuth 2.0-based authentication where clients exchange credentials for a Bearer token (JWT). The token must be included in the Authorization header as 'Authorization: Bearer '.

1. Get your credentials

To obtain access to Dow Jones Risk and Compliance APIs, you must first be an authorized customer or partner. Contact your Dow Jones Account Manager or email service@dowjones.com to initiate the registration process. Once authorized, register your application on the Dow Jones Developer Portal to receive a unique client ID and client secret. Depending on your specific integration, you will either use these credentials to perform an OAuth 2.0 flow (e.g., Service Account Integration) to obtain a short-lived Bearer access token, or use them as specified in your integration agreement for API key-based access. Always store your credentials securely and never hardcode them in your codebase.

2. Add them to .dlt/secrets.toml

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[sources.dow_jones_risk_and_compliance_source]
api_key = "your_api_key_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 Dow Jones Risk and Compliance data can I load into DuckDB?

These are the Dow Jones Risk and Compliance endpoints dlt can load into DuckDB:

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How do I load only new Dow Jones Risk and Compliance records?

The Dow Jones Risk and Compliance API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.

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{"name": "profiles_revisions", "endpoint": {
    "path": "profiles/{profile-id}/revisions/",
    # Replace with a field that increases on every write.
    "incremental": {"cursor_path": "REPLACE_ME", "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 Dow Jones Risk and Compliance pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading risk-search and screening-cases from the Dow Jones Risk and Compliance API into DuckDB:

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

@dlt.source
def dow_jones_risk_and_compliance_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.dowjones.com",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "profiles_revisions", "endpoint": {"path": "profiles/{profile-id}/revisions/"}},
            {"name": "profiles_versions", "endpoint": {"path": "profiles/{profile-id}/versions/"}}
        ],
    }
    yield from rest_api_resources(config)


def load_dow_jones_risk_and_compliance_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="dow_jones_risk_and_compliance_pipeline",
        destination="duckdb",
        dataset_name="dow_jones_risk_and_compliance_data",
    )
    load_info = pipeline.run(dow_jones_risk_and_compliance_source())
    print(load_info)


if __name__ == "__main__":
    load_dow_jones_risk_and_compliance_to_duckdb()

Run it with python dow_jones_risk_and_compliance_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 Dow Jones Risk and Compliance 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("dow_jones_risk_and_compliance_pipeline").dataset()
df = data.profiles_revisions.df()
print(df.head())

SQL:

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SELECT * FROM dow_jones_risk_and_compliance_data.profiles_revisions LIMIT 10;

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

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How do I deploy the Dow Jones Risk and Compliance 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 Dow Jones Risk and Compliance 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 Dow Jones Risk and Compliance 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