Calls and conversations tables

Note:
Some columns were configured as decimals instead of integers. From March 2026 - May 2026 we are implementing a process to change these column types to integers. As a result, you may see duplicate columns with a suffix of __NEXT. For more details, see Numeric field type updates in the Gong data cloud .

Conversations

The CONVERSATIONS table contains a row for each conversation. A conversation can be an email, call, or meeting. The CONVERSATIONS table includes the following:

Column name	Type	Value on delete	Description
CONVERSATION_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The Gong conversation id. This ID does not have to be unique. An email conversation can have the same CONVERSATION_ID as a call conversation. However, two conversations of the same type cannot have the same CONVERSATION_ID.
CONVERSATION_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	NULL	The date and time the conversation occurred
CONVERSATION_KEY	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The primary key for the conversation. As there are different types of conversations, such as calls or emails, this value is unique for all conversation types.
CONVERSATION_TYPE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX)S3: Byte_array, UTF8 S3: Byte_array, UTF8	NULL	The type of the conversation. Options are: call email meeting
WORKSPACE_IDS	Snowflake: array (string) BigQuery: json Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The IDs of the workspaces the conversation is associated with
IS_DELETED	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	Unchanged	Indicates whether the conversation was deleted in Gong. Values are: False (default): conversation exists in Gong True: conversation was deleted in Gong
ETL_MODIFIED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	Unchanged	The date and time the data was modified
ROW_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID to identify the row in the table.

Calls

The CALLS table contains a row for each call in the system, including scheduled calls that have not yet taken place. The CALLS table includes the following:

Column name	Type	Value on delete	Description
BROWSER_DURATION_SEC	Snowflake: float BigQuery: float64 Databricks: float, double Redshift: real, float4, float8, double precision S3: Float	NULL	The amount of time in seconds the browser was shared during the call
CALL_SPOTLIGHT	Snowflake: variant BigQuery: json Databricks: string Redshift: varchar(MAX) S3: UTF8	NULL	A JSON which contains the call highlight data. Displayed in the Brief tab of the call page. See below for an example of the JSON.
CALL_SPOTLIGHT_BRIEF	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	A summary of the call. Displayed in the Brief tab of the call page.
CALL_SPOTLIGHT_KEY_POINTS	Snowflake: Array of varchars BigQuery: json Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The key points of the call. Displayed in the Brief tab of the call page.
CALL_SPOTLIGHT_NEXT_STEPS	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The steps that should be done when the call is completed. Displayed in the Brief tab of the call page.
CALL_SPOTLIGHT_AUTOMATIC_DISPOSITION	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The code of the outcome of the call as determined by Gong’s AI. Only populated for SDR calls One of the following: no_voicemail left_voicemail number_not_in_service line_is_busy follow_up meeting_booked bad_timing has_a_solution bad_persona wrong_number gave_referral bad_fit opt_out hung_up gatekeeper not_interested
CALL_SPOTLIGHT_OUTCOME	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	Not populated as of October 2024. Available in CALL_SPOTLIGHT_AUTOMATIC_DISPOSITION.
CALL_SPOTLIGHT_TYPE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The type of call the highlight is for. Options are: sdr_call long_sales_call
CALL_URL	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The URL for the call
CONVERSATION_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The Gong conversation id. This ID does not have to be unique. An email conversation can have the same CONVERSATION_ID as a call conversation. However, two conversations of the same type cannot have the same CONVERSATION_ID.
CONVERSATION_KEY	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The key for the conversation the call is associated with. (Unique)
DIRECTION	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	Indicates who made the call. Options are: INBOUND OUTBOUND CONFERENCE UNKNOWN
DISPOSITION	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The outcome of the call
EFFECTIVE_START_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	Unchanged	The actual start date of the call
IS_PRIVATE	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	NULL	True if the call is a private call
OWNER_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The owner of the call. (Foreign key, `users` table)
PHONE_NUMBER	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The phone number of the prospect
PLANNED_END_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	NULL	The date and time the call was planned to end.
PLANNED_START_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	NULL	The date and time the call was planned to start.
PRESENTATION_DURATION_SEC	Snowflake: float BigQuery: float64 Databricks: float, double Redshift: real, float4, float8, double precision S3: Float	NULL	The amount of time a presentation was shared during the call
QUESTION_COMPANY_COUNT	Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: decimal	NULL	The number of questions asked by people on the call from the company
QUESTION_NON_COMPANY_COUNT	Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: decimal	NULL	The number of questions asked by customers on the call
SCOPE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	Indicates whether the call is an internal call only. Options are: INTERNAL EXTERNAL UNKNOWN
SKIP_REASON	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	For calls that aren’t recorded, the skip code for the reason the call wasn’t recorded. See Skip codes for unrecorded calls
STATUS	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The status of the call recording, automatically assigned by Gong. You can filter reports based on the call status. Possible values: SCHEDULED PURGE_REQUESTED COMPLETED - The call was completed and processed by Gong ABORTED NOSHOW CANCELED PURGED - The call was purged from the system
SOURCE_SYSTEM	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The telephony system the call was made on
TITLE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The title of the call
WEBCAM_NON_COMPANY_DURATION_SEC	Snowflake: float BigQuery: float64 Databricks: float, double Redshift: real, float4, float8, double precision S3: Float	NULL	The amount of time in seconds the customer had their webcam on
WEBCAM_OWNER_DURATION_SEC	Snowflake: float BigQuery: float64 Databricks: float, double Redshift: real, float4, float8, double precision S3: Float	NULL	The amount of time in seconds the host had their webcam on
WORKSPACE_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The workspace the call is associated with
IS_DELETED	nowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	Unchanged	Indicates whether the call was deleted in Gong. Values are: False (default): call exists in Gong True: call was deleted in Gong
ETL_MODIFIED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	Unchanged	The date and time the data was modified
ROW_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID to identify the row in the table.

Call_Recordings

The CALL_RECORDINGS table contains a row for each recorded and processed call. The table includes details about the recording such as the start and end time. The CALL_RECORDINGS table includes the following:

Column name	Type	Value on delete	Description
CONVERSATION_KEY	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The key for the conversation the call is associated with. (Unique)
DURATION	Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal	NULL	The duration of the call (in seconds)
END_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	NULL	The actual date and time the call ended.
ETL_MODIFIED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	Unchanged	The date and time the data was modified
LANGUAGE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The code for the language the call was made in
MEDIA_TYPE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	Sets the media for the call. Options are: AUDIO VIDEO
IS_DELETED	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	Unchanged	Indicates whether the call recording was deleted in Gong. Values are: False (default): call recording exists in Gong True: call recording was deleted in Gong
START_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	NULL	The actual start date and time of the call.
ROW_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID to identify the row in the table.

Call_Transcripts

The CALL_TRANSCRIPTS table contains a row for each call. The transcript is a JSON with details about who said what and at what point in the conversation. You can see an example of the JSON received below the table.

The CALL_TRANSCRIPTS table includes the following:

Column name	Type	Value on delete	Description
CONVERSATION_KEY	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The key for the conversation the call is associated with. (Unique)
TRANSCRIPT	Snowflake: array (string) BigQuery: json Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	A JSON of the transcript of the entire call. The transcript includes speaker segments, so you can see who said what and when in the call.
WORKSPACE_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The workspace the call is associated with
IS_DELETED	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	Unchanged	Indicates whether the call transcript was deleted in Gong. Values are: False (default): call transcript exists in Gong True: call transcript was deleted in Gong
ETL_MODIFIED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	Unchanged	The date and time the call transcript was modified
ROW_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID to identify the row in the table.

The structure for the JSON is as follows:

[
                    {
                    "speakerId": "4968385411579794447",
                    "sentences": [
                    {
                    "startMs": 420,
                    "endMs": 10930,
                    "text": "Michael. Good to meet you!"
                    },
                    {
                    "startMs": 11780,
                    "endMs": 14900,
                    "text": "Did you just arrive here?"
                    }
                    ]
                    },
                    {
                    "speakerId": "4968385411579794447",
                    "sentences": [
                    {
                    "startMs": 172350,
                    "endMs": 172570,
                    "text": "Yeah, We arrived last week."
                    }
                    ]
                    }
                    ]

Trackers

Trackers are tools that identify when words, phrases or concepts are mentioned in calls, allowing you to know what your reps and customers are talking about. In addition to out-of-the-box trackers that come with Gong, you can set up your own trackers, according to your company’s business priorities, and what you want to capture insights around. See Trackers: Overview for more details.

The TRACKERS table includes both smart trackers and keyword trackers. A new row is added to the table for each tracker in the system.

The TRACKERS table includes the following:

Column name	Type	Value on delete	Description
KEYWORDS	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The list of keywords in the tracker (JSON array).
NAME	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The name of the tracker, such as Pricing.
TRACKER_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The unique tracker ID
TRACKER_TYPE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The tracker type: smart_tracker keyword_tracker
WORKSPACE_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The workspace the tracker is associated with
IS_DELETED	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	Unchanged	Indicates whether the tracker was deleted in Gong. Values are: False (default): tracker exists in Gong True: tracker was deleted in Gong
ETL_MODIFIED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	Unchanged	The date and time the data was modified
ROW_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID to identify the row in the table.

In the Snowflake database, a record is inserted for the tracker with all the keywords defined and in addition for each keyword in the keyword tracker. For example, if you have a tracker which is named pricing which includes the keywords, budget, price and discount, the tracker is entered to the database as follows:

tracker_id	name	keywords	type
t_1	Pricing	[budget, price, discount]	keyword_tracker
t_2	Pricing / budget	[budget]	keyword_tracker
t_3	Pricing / price	[price]	keyword_tracker
t_4	Pricing / discount	[discount]	keyword_tracker

Smart trackers are added to the table as follows:

tracker_id	name	keywords	type
t_6	My Smart Tracker	NULL	smart_tracker

Conversation_trackers

The CONVERSATION_TRACKERS table is used to associate conversations with trackers and contains the following fields:

Column name	Type	Value on delete	Description
CONVERSATION_KEY	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID for the conversation (foreign key)
COUNT	Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal	NULL	The number of times the tracker occurs.
TRACKER_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The tracker ID (foreign key)
WORKSPACE_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The workspace the tracker is associated with
IS_DELETED	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	Unchanged	Indicates whether the record was deleted in Gong. Values are: False (default): record exists in Gong True: record was deleted in
ETL_MODIFIED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	Unchanged	The date and time the data was modified
ROW_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID to identify the row in the table.

The following is an example of how the keyword trackers are added to the CONVERSATION_TRACKERS table. When the TRACKERS table has the following entries:

tracker_id	name	keywords	type
t_1	Pricing	[budget, price, discount]	keyword_tracker
t_2	Pricing / budget	[budget]	keyword_tracker
t_3	Pricing / price	[price]	keyword_tracker
t_4	Pricing / discount	[discount]	keyword_tracker
t_6	My Smart Tracker	NULL	smart_tracker

In a call where the following trackers are identified:

"Budget" found twice
“Price” found once
“My Smart Tracker” found five times

The CONVERSATION_TRACKERS table will have the following entries:

conversation_key	tracker_id	count
c_1	t_1 (Pricing)	3
c_1	t_2 (Pricing / budget)	2
c_1	t_3 (Pricing / price)	1
c_1	t_6 (My Smart Tracker)	5

The Pricing tracker (t_1) is counted three times in the conversation, as it includes mentions of the terms budget and price. The Pricing/budget (t_2) tracker is counted twice in the conversation, as this tracker only covers the term budget. The Pricing/price (t_3) tracker is counted once in the conversation, as this tracker only covers the term price.

Conversation_contexts

The CONVERSATION_CONTEXTS table enables associating a CRM object, such as an account, deal or lead, with a conversation. A conversation can be associated with multiple CRM objects. Each association is added as a new record in the CONVERSATION_CONTEXTS table.

The CONVERSATION_CONTEXTS table includes the following:

Column	Type	Value on delete	Description
CONVERSATION_KEY	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The key for the conversation
FIELDS_SNAPSHOT	Snowflake: varchar BigQuery: json Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	A snapshot of the object's fields, that are imported to Gong, at the time of the conversation, excluding those in the `mapped_fields_snapshot` field
MAPPED_FIELDS_SNAPSHOT	Snowflake: varchar BigQuery: json Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	Gong maps some fields in the CRM to other fields. For a list of mapped fields per CRM object see the table below
OBJECT_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID of the object in the CRM
OBJECT_TYPE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The object type. Options are (in lowercase): crm_account crm_opportunity crm_contact crm_lead
IS_DELETED	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	Unchanged	Indicates whether the conversation context was deleted in Gong. Values are: False (default): conversation context exists in Gong True: conversation context was deleted in Gong
ETL_MODIFIED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	Unchanged	The date and time the data was modified
ROW_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID to identify the row in the table.

The following table shows how CRM fields are mapped in Gong:

CRM object	Mapped fields in Gong
Account	name industry type
Opportunity (Deal)	owner name amount stage isStageClose isStageWon proababilityPercent forecastCategory
Lead	status

CRM object

Mapped fields in Gong

Account

name

industry

type

Opportunity (Deal)

owner

name

amount

stage

isStageClose

isStageWon

proababilityPercent

forecastCategory

Lead

status

Conversation_participants

The CONVERSATION_PARTICIPANTS table contains a row for each email recipient and a row for each call or meeting participant. The CONVERSATION_PARTICIPANTS table includes the following:

Column name	Type	Value on delete	Description
AFFILIATION	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The company the participant is affiliated with. Options are: unclassified: Gong couldn't determine the participant's affiliation company: the participant is affiliated with company that uses Gong non_company: the participant is not affiliated with the company
ASSOCIATED_OBJECT_TYPE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The object type of the participant in the CRM. Options are: Contact Lead
CONVERSATION_KEY	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The key for the conversation the call is associated with. (Unique)
EMAIL_ADDRESS	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The email address of the participant
FIELDS_SNAPSHOT	Snowflake: variant BigQuery: json Databricks: string Redshift: varchar(MAX)	NULL	A snapshot of the object's fields, that are imported to Gong, at the time of the conversation, excluding those in the `mapped_fields_snapshot` field
INVITEE_STATUS	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The invitees response to the meeting invitation. Null when conversation is not a meeting. Options are: accepted declined none tentative
MAPPED_FIELDS_SNAPSHOT	Snowflake: variant BigQuery: json Databricks: string Redshift: varchar(MAX) S3: UTF8	NULL	Gong maps some fields in the CRM to other fields. For a list of mapped fields per CRM object see mapped fields
NAME	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The name of the participant in the conversation
PHONE_NUMBER	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The phone number of the participant
SPEAKER_ID	Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal	NULL	The ID of the person speaking as listed in the call transcript. Transcripts are found in the `CALL_TRANSCRIPT` table.
TYPE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The participant type or role in the conversation. For emails options are: to cc bcc from sender reply_to For calls options are: Invitee Attendee For meetings options are: Organizer Required Optional Resource, such as meeting room Unknown
USER_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The participant's Gong user ID. Null if they are not a Gong user.
IS_DELETED	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	Unchanged	Indicates whether the participant was deleted in Gong. Values are: False (default): participant exists in Gong True: participant was deleted in Gong
ETL_MODIFIED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	Unchanged	The date and time the data was modified
ROW_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID to identify the row in the table.

Meetings

The MEETINGS table contains a row for each calendar meeting. Meetings may or may not have an associated call. When a meeting includes a call, the call_conversation_key contains the ID for the call. For details on meetings, see View meetings without scheduled recordings . The MEETINGS table includes the following:

Column name	Type	Value on delete	Description
CALL_CONVERSATION_KEY	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The conversation key of the call for the meeting. Null when there is no call associated with the meeting.
CALL_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The call ID
CONVERSATION_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The Gong conversation id. This ID does not have to be unique. A meeting can have the same CONVERSATION_ID as a call. However, two conversations of the same type cannot have the same CONVERSATION_ID.
CONVERSATION_KEY	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The primary key for the meeting in Snowflake. (Unique)
CREATED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	NULL	The date and time the meeting created
END_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	NULL	The date and time the meeting is schedule to end
IS_ALL_DAY	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	NULL	When true, indicates the meeting will last the whole day
IS_CANCELED	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	NULL	When true, indicates the meeting was cancelled
IS_INTERNAL	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	NULL	When true, indicates the meeting is internal
IS_RECURRING	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	NULL	When true, sets that this is a recurring meeting
MODIFIED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	NULL	The last date and time the meeting was modified
ORGANIZER_USER_ID	Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal	NULL	The Gong user ID of the person who organized the meeting
START_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	NULL	The date and time the meeting is scheduled to start
TITLE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The title of the meeting
WORKSPACE_IDS	Snowflake: array (string) BigQuery: json Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	A list of the workspace IDs the meeting is associated with
IS_DELETED	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	Unchanged	Indicates whether the meeting was deleted in Gong. Values are: False (default): meeting exists in Gong True: meeting was deleted in Gong
ETL_MODIFIED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	Unchanged	The date and time the data was modified
ROW_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID to identify the row in the table.

Emails

The EMAILS table contains a row for each email and the workspaces the email is associated with. The EMAILS table includes the following:

Column name	Type	Value on delete	Description
AUTO_SUBMITTED_TYPE	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	Indicates the type of email for auto generated emails. Options are: auto_generated: Indicates that a message was generated by an automatic process, and is not a direct response to another message. auto_replied: Indicates that a message was automatically generated as a direct response to another message. auto_notified: Indicates that a message was generated by a Sieve notification system.
CONVERSATION_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	The Gong conversation id. This ID does not have to be unique. An email conversation can have the same CONVERSATION_ID as a call conversation. However, two conversations of the same type cannot have the same CONVERSATION_ID.
CONVERSATION_KEY	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The primary key for the conversation in Snowflake. As there are different types of conversations, such as calls or emails, this value is unique for all conversation types.
DIRECTION	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	INBOUND or OUTBOUND. Whether the email originated from a customer (inbound) or is an email to the customer (outbound)
IS_AUTO_SUBMITTED	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	NULL	When true, indicates that the email is submitted automatically
IS_MEETING_INVITE	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	NULL	When true, indicates the email is an invitation for a meeting
OOO_RETURN_DATE	Snowflake: dateTime BigQuery: date Databricks: date Redshift: date S3: UTF8	NULL	Indicates the return date of an out of office email. NULL for non OOO emails.
SENT_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	NULL	The timestamp for when the email was sent
WORKSPACE_IDS	Snowflake: array (string) BigQuery: json Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	NULL	A list of the workspace IDs the email is associated with
IS_DELETED	Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean	Unchanged	Indicates whether the email was deleted in Gong. Values are: False (default): email exists in Gong True: email was deleted in Gong
ETL_MODIFIED_DATETIME	Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS	Unchanged	The date and time the data was modified
ROW_ID	Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8	Unchanged	The ID to identify the row in the table.