@grazianodelucaa2a Here's some additional information Getting Started with Sprinklr APIs from Steve Dzilvelis! 

Hi Graziano! 

Here are the key integration methods available for exporting Sprinklr data to Google Data Platform:

• Google Cloud Storage (GCS) Connector: Sprinklr offers a connector that allows you to integrate with and access data stored in Google Cloud Storage directly from the Sprinklr platform. This is particularly useful for managing large datasets and ensuring seamless workflows between Sprinklr and GCS.

• Scheduled Exports to GCP: You can configure scheduled exports to automatically send Sprinklr data to Google Cloud Platform (GCP) as an external storage option. This means you can store your exports seamlessly on the client side in your GCP environment without manual intervention.

• Data Connector Export Module: Sprinklr has a Unified Data Connector feature that enables you to migrate data to and from Sprinklr. You can use this module to export data from Sprinklr to various external systems, which could include preparing data for ingestion into a data warehouse like Google BigQuery.

• Reporting APIs: For programmatic data export, you can leverage Sprinklr's Reporting APIs to fetch data from dashboards and widgets. This method allows for more control and customization over the data extraction process.

• Data Studio Integration: While primarily for data visualization, the Sprinklr Data Studio connector allows you to connect Sprinklr as a data source to create reports and gain insights from your social accounts. This can be a useful starting point for exploring and analyzing your data before moving it to a data warehouse.
  
  
  
  Here's an overview of the methods to export Sprinklr data to your Google Data Platform, along with their pros and cons, especially considering your Salesforce integration:
  
  
  1. Sprinklr's Built-in Export Features:
  
  
  
  • Description: Sprinklr offers various ways to export data directly from its platform, primarily through its reporting dashboards and widgets.
  
  
  • Pros:
    
    
    • User-friendly interface.
    
    
    • Allows customization of export formats (PDF, Excel, PNG, CSV).
    
    
    • Supports scheduling automated exports.
    
    
    • Can export different levels of data, including dashboard-level and widget-level data.
    
    
    • Offers options for storing exports in external storage like Google Cloud Platform (GCP), FTP, or SFTP.
    
    
    
  
  
  • Cons:
    
    
    • Primarily focused on reporting and dashboard data, not necessarily raw entity data.
    
    
    • Limited in the amount of data that can be exported at once (e.g., 100,000 rows limit for Excel exports).
    
    
    • May require manual effort to extract and process data for integration with your Google Data Platform.
    
    
    • May not support real-time data export.
    
    
    • Some users have reported issues with slow export times.
    
    
    
  
  
  
  2. Sprinklr's Reporting APIs:
  
  
  
  • Description: Sprinklr provides APIs that allow you to fetch data from its reporting dashboards and widgets programmatically.
  
  
  • Pros:
    
    
    • Enables automated data extraction and integration with your Google Data Platform.
    
    
    • Allows for more flexibility and control over the data being exported.
    
    
    • Supports real-time data export.
    
    
    
  
  
  • Cons:
    
    
    • Requires technical expertise to implement and manage the API integration.
    
    
    • May require use case approval from social providers.
    
    
    • Page size limitations may apply.
    
    
    • May require ongoing maintenance to ensure the API integration remains functional.
    
    
    
  
  
  
  3. Sprinklr's Data Connector Export Module:
  
  
  
  • Description: The Data Connector Export Module allows you to export raw entity data, entity reports, and templates to external storage locations like Amazon S3 and SFTP.
  
  
  • Pros:
    
    
    • Provides real-time data export capabilities.
    
    
    • Supports exporting raw entity data.
    
    
    • Offers a user-friendly interface for configuring, managing, and scheduling export settings.
    
    
    
  
  
  • Cons:
    
    
    • May require additional configuration to integrate with your Google Data Platform.
    
    
    • Currently, only supports S3 and SFTP as destination types, not directly GCP.
    
    
    
  
  
  
  4. Third-Party ETL (Extract, Transform, Load) Tools:
  
  
  
  • Description: Third-party ETL tools like Rivery can extract data from Sprinklr and load it into your Google Data Platform.
  
  
  • Pros:
    
    
    • Offers pre-built connectors for Sprinklr and Google Cloud Storage.
    
    
    • Simplifies the data integration process.
    
    
    • May offer features like data transformation and monitoring.
    
    
    
  
  
  • Cons:
    
    
    • May require additional costs for the ETL tool.
    
    
    • May require technical expertise to set up and manage the ETL process.
    
    
    
  
  
  
  Considering Your Salesforce Integration:
  
  
  Since your Salesforce CRM is already connected to your Google Data Platform, you could also leverage this existing connection:
  
  
  
  • Sprinklr + Salesforce Integration: Sprinklr integrates with Salesforce Service Cloud to unify customer interactions and streamline workflows.
  
  
  • Pros:
    
    
    • Leverages your existing Salesforce integration with your Google Data Platform.
    
    
    • Provides a holistic view of customer data by combining Sprinklr data with Salesforce data.
    
    
    • Enables data-driven decision-making.
    
    
    
  
  
  • Cons:
    
    
    • May not include all desired Sprinklr Service entities in the data exported through Salesforce.
    
    
    • May require additional effort to ensure data consistency between Sprinklr and Salesforce.
    
    
    
  
  
  
  Recommendation:
  
  
  The best approach will depend on your specific needs and requirements. Consider the following factors:
  
  
  
  • Data volume and velocity: If you need to export large volumes of data frequently, the Reporting APIs or the Data Connector Export Module might be better options.
  
  
  • Technical expertise: If you have limited technical expertise, the built-in export features or a third-party ETL tool might be more suitable.
  
  
  • Budget: Third-party ETL tools may involve additional costs.
  
  
  • Data governance: Consider your data governance policies and ensure that the chosen method aligns with them.
  
  
  • Future needs: Choose a solution that can scale with your evolving needs.