Google Cloud BigQuery and Ghost Integration

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Google Cloud BigQuery

Ghost

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Cloud BigQuery and Ghost

Create a New Scenario to Connect Google Cloud BigQuery and Ghost

In the workspace, click the “Create New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Cloud BigQuery, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery or Ghost will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery or Ghost, and select the appropriate trigger to start the scenario.

Add the Google Cloud BigQuery Node

Select the Google Cloud BigQuery node from the app selection panel on the right.

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Configure the Google Cloud BigQuery

Click on the Google Cloud BigQuery node to configure it. You can modify the Google Cloud BigQuery URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Add the Ghost Node

Next, click the plus (+) icon on the Google Cloud BigQuery node, select Ghost from the list of available apps, and choose the action you need from the list of nodes within Ghost.

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Authenticate Ghost

Now, click the Ghost node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Ghost settings. Authentication allows you to use Ghost through Latenode.

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Configure the Google Cloud BigQuery and Ghost Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Run node once

Set Up the Google Cloud BigQuery and Ghost Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring Google Cloud BigQuery, Ghost, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking “Run once” and triggering an event to check if the Google Cloud BigQuery and Ghost integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and Ghost (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Google Cloud BigQuery and Ghost

Ghost + Google Analytics + Slack: When a new post is published on Ghost, Google Analytics runs a report to track its performance. If the report indicates a trending post based on predefined criteria (e.g., high views), a notification is sent to a designated Slack channel to alert the team.

Ghost + Google Analytics: When a new post is published on Ghost, Google Analytics creates a key event to track the post's performance.

Google Cloud BigQuery and Ghost integration alternatives

About Google Cloud BigQuery

Use Google Cloud BigQuery in Latenode to automate data warehousing tasks. Query, analyze, and transform huge datasets as part of your workflows. Schedule data imports, trigger reports, or feed insights into other apps. Automate complex analysis without code and scale your insights with Latenode’s flexible, pay-as-you-go platform.

About Ghost

Integrate Ghost with Latenode to automate content workflows. Automatically publish new posts, manage member data, or trigger email campaigns. Use Latenode's visual editor and flexible nodes to build custom workflows around Ghost, bypassing manual tasks and scaling content operations without code. Connect Ghost to other apps to streamline your publishing process.

See how Latenode works

FAQ Google Cloud BigQuery and Ghost

How can I connect my Google Cloud BigQuery account to Ghost using Latenode?

To connect your Google Cloud BigQuery account to Ghost on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Google Cloud BigQuery and click on "Connect".
  • Authenticate your Google Cloud BigQuery and Ghost accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I analyze Ghost blog post performance in BigQuery?

Yes, you can! Latenode allows you to automate data transfer from Ghost to Google Cloud BigQuery, providing powerful analytics to understand content performance and audience behavior.

What types of tasks can I perform by integrating Google Cloud BigQuery with Ghost?

Integrating Google Cloud BigQuery with Ghost allows you to perform various tasks, including:

  • Automatically backing up Ghost content to Google Cloud BigQuery for data safety.
  • Creating custom reports on member activity and engagement metrics.
  • Analyzing website traffic data alongside content performance metrics.
  • Generating personalized content recommendations based on user data.
  • Syncing subscriber data between Ghost and Google Cloud BigQuery for analysis.

Can I schedule automated data exports from Ghost to BigQuery?

Yes! Latenode's scheduling features allow you to automate data exports from Ghost to Google Cloud BigQuery at specific intervals.

Are there any limitations to the Google Cloud BigQuery and Ghost integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Initial data schema setup in Google Cloud BigQuery may require technical knowledge.
  • Large data transfers might incur costs associated with Google Cloud BigQuery usage.
  • Real-time synchronization depends on the APIs of both Google Cloud BigQuery and Ghost.

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