Weekly Airbyte data catalog in Notion for business teams
Every Monday morning, refresh a Notion database with one row per Airbyte pipeline so marketing, sales, and finance stop asking the data team what's fresh.
Airbyte
NotionOperationsEngineeringData SyncAI ReportsEvery Monday at 6am, refresh a Notion "Data Catalog" database so non-data teammates in marketing, sales, and finance have a self-serve view of everything flowing through our Airbyte pipelines, without having to ping the data team.
Start by pulling the current picture from Airbyte. Use Airbyte List Connections to enumerate every pipeline, Airbyte List Sources and Airbyte List Destinations to resolve each connection's source system and destination system by id, and Airbyte Get Connection Details on each connection to read its schedule and the list of streams that are actually enabled. For the most recent successful sync per connection, call Airbyte List Jobs filtered by that connection id with jobType=sync, then pick the newest entry whose status is succeeded.
Then, for each Airbyte connection, use Notion Create a Page inside the pre-existing Data Catalog database. The database already exists and its id will be provided at setup — do not create a new database, only add pages to that one. Populate the following properties on each page:
Title: a short human-readable name like "HubSpot → Snowflake (Marketing)". Source system: the source connector name (e.g. HubSpot, Salesforce, Stripe). Destination system: the destination connector name (e.g. Snowflake, BigQuery, Redshift). Sync schedule: rendered in plain English like "Every 6 hours", "Daily at 2am UTC", or "Manual" — not a cron expression. Last successful sync time: the timestamp of the most recent succeeded sync job; if the connection has never succeeded, leave it empty and note "never synced". Streams synced: the enabled stream names as a comma-separated list. Summary: a two-to-three sentence plain-English description of what data this pipeline moves and who typically consumes it — for example, "Pulls contacts and deals from HubSpot into Snowflake every six hours. Feeds the marketing attribution dashboard and the weekly AE pipeline review."
When writing summaries, remember the audience is non-technical. Avoid data-engineering jargon like CDC, incremental, namespace, or upsert. Frame each summary as (1) what data flows from where to where, (2) how often, and (3) who or what downstream tool tends to use it. If you don't know the consumer, make a reasonable guess based on the source system (e.g. HubSpot data is usually consumed by marketing and sales; Stripe data by finance; product event data by product and analytics).
If a Notion page already exists in the catalog database for a given connection (match on the connection id or title), overwrite it with the fresh values so the catalog stays current instead of accumulating duplicates. If a connection has been deleted from Airbyte since the last run, leave any existing Notion page alone but do not create a new one for it.
What does this prompt do?
- Reads every Airbyte connection, source, and destination and matches each pipeline to its most recent successful sync.
- Refreshes a Notion 'Data Catalog' database with one row per pipeline covering the source system, destination, sync schedule, last successful sync, and streams included.
- Writes a short plain-English summary of what each pipeline moves and who tends to consume the data, so non-data teammates can self-serve lineage answers.
What do I need to use this?
- An Airbyte Cloud account with your connections, sources, and destinations already set up.
- A Notion workspace with a database ready to hold the catalog (one row per pipeline).
- That Notion database shared with your Notion connection so the workflow can write pages into it.
How can I customize it?
- Shift the schedule — run daily, twice a week, or on a different day and time.
- Add extra columns to the Notion database like data steward, downstream dashboard, or business owner and ask the agent to fill them.
- Tune the tone of the summaries (formal, plain-spoken, or business-jargon-friendly) to match how your teams talk about data.
FAQs
Do I need a data engineer to set this up?
What happens when we add a new Airbyte pipeline?
Can our team still edit the Notion catalog by hand?
Will this work with Airbyte Self-Managed as well as Airbyte Cloud?
Does the summary read like it was written by an AI?
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Give marketing, sales, and finance a self-serve view of what data lives in the warehouse and how fresh it is, so the data team stops fielding the same lineage questions every week.