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Easily send Pinterest data to Microsoft SQL Server

Automatically fetch your Pinterest data and send it to Microsoft SQL Server with Adverity.

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Automate your entire data pipeline with Adverity

  1. Step 1Centralize your Pinterest data in Microsoft SQL ServerEasily extract your Pinterest data and automatically send to Microsoft SQL Server in just a few clicks.
  2. Step 2Combine Pinterest data with data from multiple sourcesIntegrate Pinterest data to more than 600 other data sources in our API library.
  3. Step 3Automated data standardizationUse no-code data transformations to automatically standardize your Pinterest data before sending to Microsoft SQL Server.
  4. Step 4Create a single source of truthBuild a single source of truth in Microsoft SQL Server with accurate data you can trust.

What is Pinterest?

‘433 million people using Pinterest every month.’ - https://business.pinterest.com/en-gb/

With Pinterest you can create boards full of content that speaks to your target audience, allowing them to pin and engage with what they are most interested in. You can then use this data to create targeted ads that enhance the user's experience on the platform.

More about the Pinterest connector

Other destinations for Pinterest

Looker StudioMicrosoft ExcelPower BIDatabricksGoogle BigQuerySnowflakeTableauSQL Database (MySQL/Oracle)Azure BlobAdobe AnalyticsGoogle SheetsFireboltAdobe Experience PlatformGoogle AnalyticsAzure SynapseMicrosoft OneDrive

Other sources for Microsoft SQL Server

Google BigQueryInstagram Business (Meta)Amazon AdvertisingFacebook Ads (Meta)Walmart MarketplaceGoogle AdsGoogle Analytics (GA4)YouTube AnalyticsLinkedIn AdsGoogle Display & Video 360 (DV360)TikTok AdsShopifyGoogle Search ConsoleGoogle Search Ads 360Microsoft AdsAmazon DSPFacebook Page Insights (Meta)Twitter Ads (X Ads)Apple Search AdsGoogle Campaign ManagerGoogle DriveCriteo Marketing SolutionsAmazon Marketing CloudSnapchatAwin Advertiser

Want to connect Pinterest to Microsoft SQL Server?

Connect your warehouse and see it work on your own data.

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