Question 1

What can Polytomic pull from Gong into Redshift?

Accepted Answer

Calls with their metadata, participants, context, topics, trackers and tracker occurrences, and interaction data. Separately: transcripts, keyword tracker definitions, scorecards and their answers, users, workspaces, library folders and their contents, and Engage flows. Trackers are often the most immediately useful table, because a tracker hit is a structured signal you can count and join, where a transcript is text you have to do something with first.

Question 2

How do long transcripts land in Redshift?

Accepted Answer

Text columns are created as VARCHAR(MAX), which is the widest Redshift offers. Values beyond roughly 65,500 bytes are truncated with a marker appended and a record warning raised, rather than failing the run. For most calls this is not reached, but a long multi party call can approach it, so if you intend to do text analysis on complete transcripts it is worth checking for truncation markers rather than assuming every row is whole.

Question 3

Are reads incremental?

Accepted Answer

Optionally, and only for calls and transcripts. Those use a time watermark with a rolling seven day lookback, which catches records arriving late relative to when the call happened. Be clear about what this is not: it is not update complete change capture, and changes landing outside the window can be missed. If completeness matters, run a periodic full ETL read alongside the incremental schedule rather than assuming the watermark covers everything.

Question 4

Are deletes captured?

Accepted Answer

No. There is no delete event or tombstone mechanism for Gong, so a call removed in Gong will not be marked as removed by an incremental run. Treat Gong as snapshot based for reconciliation and rely on periodic full reads to clear records that are no longer present. This is why the incremental calls and transcripts path should not be described as delete aware, even though it is genuinely incremental.

Question 5

Why replicate Gong into a data warehouse?

Accepted Answer

Because conversation data is raw material rather than a finished answer. Customers describe wanting Gong in the data warehouse first so they can shape it, join it to account and opportunity records, and only then push a result somewhere useful. ETL makes transcripts and tracker hits queryable next to CRM data, so a question like which objections precede a lost deal turns into SQL rather than listening to calls.

Sync Gong to Redshift

Sync Gong to Redshift with Polytomic

Calls, transcripts and trackers

Rolling lookback on incremental

Snapshot for reconciliation

Or sync Redshift to Gong

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