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Hi everyone,I have created an SSAS Tabular model using data from Azure Databricks through an ODBC DSN. The model was deployed successfully without any issues.After deployment, I connected to the same model using SSMS. However, when I try to process (refresh) a partition of one of the tables, I receive the following error:Failed to save modifications to the server. Error returned:'On-Premise Gateway is required to access the data source. Please install a unified gateway for the server <server_name> or disable AlwaysUseGateway setting if it's enabled.Technical Details:RootActivityId: bf18614e-5328-43b3-8732-48560bb528adDate (UTC): 7/31/2026 9:10:59 AM'What I've already checked: Created the model using an ODBC DSN that connects to Azure Databricks. Successfully deployed the model. Verified that the AlwaysUseGateway setting is disabled (False). Restarted/redeployed after changing the setting, but the issue still persists. Has anyone encountered this issue before?I'm trying to u

I'm using CData Sync with a SQL Server source in a Standard job (incremental check column, no CDC or CT enabled). If a new column is added to a source table, will Sync automatically detect and add it to the destination on the next run? The Features page says schema changes are detected "in every run", but the SQL Server Source page only describes this behavior under CT/CDC. Does it work without CT/CDC enabled?

The CData Connect AI MCP integration lets you build an AI document agent that connects directly to Google Drive, reading actual document contents, reasoning across multiple files, and returning structured answers with source citations, without manual file searches or reformatting.In this article, you'll learn how to:Set up a Google Drive connection in CData Connect AI Enable Execute permissions for document content retrieval Convert .docx files to native Google Docs format for full content access Configure a Claude project with a system prompt to define agent behavior Validate the connection and run document queriesTo learn more, read:Connecting Google Drive to an AI Document Agent with CData Connect AI

We’re currently testing the S3 destination for various sources using CSV file format and would like to be able to do 2 things:Specify a subfolder per job or task Append the table name to the destination filefor example, if the S3 Connection is setup to a folder cdata/ i would like to be able to output the following structurecdata/ salesforce/ account/ account_20260722113426039_1.csv account_20260722113426039_2.csv contact/ contact_20260722113426039_1.csv servicenow/ task/ task_20260722113426039_1.csv ..etcThe closest I’ve been able to get is appending something to the table/folder name, and I can’t find any usable option to control the file name format. I’ve tried changing the batch naming convention in the connection settings but it had no affect.cdata salesforce_account 20260722113426039_1.csv 20260722113426039_2.csv ..etc Additionally - Ther’es no documentation on the “Advanced” features of the S3 destination other than “you probably won’t need it” --

Is there a way to introduce a delay between steps in a CData Sync Pipeline? We have a limitation from a source API and need to ensure we delay our API requests by 15 seconds between calls, hence looking to add this delay.