Mastering Genesys Cloud architect Data Tables API

Genesys Cloud Data Tables: A Practical Guide

Genesys Cloud Data Tables provide a simple yet effective way to store and manage structured data. They can be created and managed via the Genesys Cloud portal or programmatically using the API. At Noralogix, we leverage our expertise in integrating and optimizing Genesys Cloud solutions, including the use of data tables.

Creating a Data Table in Genesys Cloud

A data table can be created directly from the Genesys Cloud portal:

• Navigate to Genesys Cloud -> Admin -> Data Tables (under the Architect section).
• Define a Reference Key Column (mandatory).
• Add multiple columns with supported data types: Boolean, Integer, Decimal, and String.

Managing Data Tables

Once created, data tables can be managed in multiple ways:

• Manual Management: Add, edit, and remove rows via the Genesys Cloud portal.
• Automated Management: Use the API for integration with external systems and automation.

Uploading Data via API

The most efficient way to populate a data table is through the API using a CSV file. The CSV must match the column structure defined in Genesys Cloud, with a required key column.

Steps to Import Data via API

1. Create an Import Job

   • Make a POST request to:

     /api/v2/flows/datatables/{datatableId}/import/jobs
     

   • Response includes:
     • UploadURI: The URI for uploading the CSV file.
     • Id: The Import Job ID.

2. Upload CSV File

   • Use the UploadURI to send the CSV file as MultipartFormDataContent.

3. Check Import Job Status

   • Make a GET request to:

     /api/v2/flows/datatables/{datatableId}/import/jobs/{importJobId}
     

   • The response includes the job status and potential errors (ErrorInformation, Status, Message).

Recommended Tools for Development

At Noralogix, we primarily use C# for development. The CsvHelper package is our preferred tool for handling CSV files efficiently.

• CsvHelper NuGet Package: CsvHelper
• Easily maps your data model to the API’s required structure.

Limitations and Alternative Solutions

One limitation of Genesys Cloud Data Tables is the inability to modify table structures once created and rate limits. For greater flexibility, we recommend Azure Table Storage:

• Supports additional data types.
• Allows modification of table schema.
• Scales efficiently for enterprise-level applications.

For more information on Azure Table Storage for Genesys Cloud, watch this YouTube video.

Conclusion

Genesys Cloud Data Tables offer a straightforward way to manage data within the platform. However, for more advanced requirements, integrating Azure Table Storage provides enhanced flexibility. At Noralogix, we specialize in optimizing these solutions for our clients to ensure seamless integration and data management.