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Use Google Vertex AI to enrich Microsoft SQL Server data, like adding sentiment analysis to customer feedback. Latenode's visual editor and affordable execution-based pricing makes it easier to scale custom AI-powered data solutions.
Connect Google Vertex AI and Microsoft SQL Server in minutes with Latenode.
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Create a New Scenario to Connect Google Vertex AI and Microsoft SQL Server
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 Vertex AI, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Vertex AI or Microsoft SQL Server will be your first step. To do this, click "Choose an app," find Google Vertex AI or Microsoft SQL Server, and select the appropriate trigger to start the scenario.
Add the Google Vertex AI Node
Select the Google Vertex AI node from the app selection panel on the right.
Google Vertex AI
Configure the Google Vertex AI
Click on the Google Vertex AI node to configure it. You can modify the Google Vertex AI URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Microsoft SQL Server Node
Next, click the plus (+) icon on the Google Vertex AI node, select Microsoft SQL Server from the list of available apps, and choose the action you need from the list of nodes within Microsoft SQL Server.
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Microsoft SQL Server
Authenticate Microsoft SQL Server
Now, click the Microsoft SQL Server node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Microsoft SQL Server settings. Authentication allows you to use Microsoft SQL Server through Latenode.
Configure the Google Vertex AI and Microsoft SQL Server Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Google Vertex AI and Microsoft SQL Server Integration
Use various Latenode nodes to transform data and enhance your integration:
JavaScript
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AI Anthropic Claude 3
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Microsoft SQL Server
Trigger on Webhook
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Google Vertex AI
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring Google Vertex AI, Microsoft SQL Server, 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 Vertex AI and Microsoft SQL Server integration works as expected. Depending on your setup, data should flow between Google Vertex AI and Microsoft SQL Server (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Slack + Google Vertex AI + Microsoft SQL Server: When a new message is posted in a Slack channel, the message content is analyzed using Google Vertex AI for sentiment and key topics. These insights are then stored in a Microsoft SQL Server database for further analysis and reporting.
Microsoft SQL Server + Google Vertex AI + Slack: When a new or updated row is detected in Microsoft SQL Server, Google Vertex AI generates a summary of the changes. This summary is then sent as a direct message to a specified user in Slack.
About Google Vertex AI
Use Vertex AI in Latenode to build AI-powered automation. Quickly integrate machine learning models for tasks like sentiment analysis or image recognition. Automate data enrichment or content moderation workflows without complex coding. Latenode’s visual editor makes it easier to chain AI tasks and scale them reliably, paying only for the execution time of each flow.
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About Microsoft SQL Server
Use Microsoft SQL Server in Latenode to automate database tasks. Directly query, update, or insert data in response to triggers. Sync SQL data with other apps; simplify data pipelines for reporting and analytics. Build automated workflows without complex coding to manage databases efficiently and scale operations.
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How can I connect my Google Vertex AI account to Microsoft SQL Server using Latenode?
To connect your Google Vertex AI account to Microsoft SQL Server on Latenode, follow these steps:
Can I analyze customer feedback and store sentiment in SQL?
Yes, you can. Latenode's visual editor simplifies connecting Google Vertex AI for sentiment analysis with Microsoft SQL Server for data storage. Automate insights effortlessly.
What types of tasks can I perform by integrating Google Vertex AI with Microsoft SQL Server?
Integrating Google Vertex AI with Microsoft SQL Server allows you to perform various tasks, including:
How do I handle large datasets when using Google Vertex AI on Latenode?
Latenode allows you to process data in chunks, optimizing performance for Google Vertex AI and Microsoft SQL Server integrations, even with large datasets.
Are there any limitations to the Google Vertex AI and Microsoft SQL Server integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: