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* Data Cloud
This section details the tables and columns available in the Gong data cloud. See What's new in Gong Data Cloud for details of what's been added to the 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:
|
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:
|
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 the call spotlight and 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 all the spotlight data for the call. 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 |
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 |
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 |
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:
|
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 spotlight is for. Options are:
|
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:
|
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, |
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:
|
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:
|
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:
|
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:
|
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates whether the call recording was deleted in Gong. Values are:
|
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:
|
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."
}
]
}
]Users
The USERS table contains data about each user in the system including licensing details. Use the manager_id field to build organizational hierarchy. We also maintain history in this table using SCD type 2.0, so you can see for example, previous job titles or permissions. When one of the values is changed, the VALID_TO_DATETIME is set to the current date and a new row is added with both the new and unchanged values. The VALID_FROM_DATETIME in the new row is set to the current date and the VALID_TO_DATETIME is set to NULL.
The USERS table includes the following:
Column | Type | Value on delete | Description |
|---|---|---|---|
ACTIVE | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | NULL | Sets whether the user is active. Users are not deleted from the system, they become inactive |
EMAIL_ADDRESS | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The user's email address |
FIRST_NAME | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The user's first name |
LAST_NAME | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The user's last name |
LICENSED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | NULL | Indicates whether the user has a paid license |
LOCALE | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The user's locale |
MANAGER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The id of the employee's manager |
TIME_ZONE | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The timezone the user is in (TZ format, such as America/New_York) |
USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The ID of the user in Gong (unique). |
SHOULD_IMPORT_TELEPHONY_CALLS | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | NULL | Indicates whether the user's calls recorded by an external telephony system should be automatically recorded and imported into Gong |
SHOULD_RECORD_WEB_CONFERENCE_CALLS | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | NULL | Indicates whether the user's web conference calls should be automatically recorded |
SHOULD_SYNC_EMAILS | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | NULL | Indicates whether the user's emails should be automatically imported to Gong |
TITLE | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The employee's job title |
VALID_FROM_DATE_TIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | Unchanged | (SCD type 2.0) The date this record was created |
VALID_TO_DATE_TIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | Unchanged | (SCD type 2.0) The date this record was changed. A null value indicates this is the current record for the user. |
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates whether the user was deleted in Gong. Values are:
|
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 changed |
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. |
User_crm_ids
In some cases, one email address can be associated with multiple CRM IDs. In order to ensure that each Gong user is associated with the correct CRM ID, we store all CRM IDs associated with the user, so that one Gong user can be associated with multiple CRM user IDs.
The USER_CRM_IDS table includes the following:
Column | Type | Value on delete | Description |
|---|---|---|---|
CRM_USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The Gong user's ID in the CRM |
USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The ID of the user in Gong (unique). |
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates whether the user’s CRM ID was deleted in Gong. Values are:
|
ETL_MODIFIED_DATETIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | Unchanged | The date and time the CRM 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. |
User_conversation_gong_activities
The USER_CONVERSATION_GONG_ACTIVITIES table stores details of which user performed which activity on a call. For each activity a user performs in the application, a new row is added with the user and call ids, the date of the activity and the type of the activity.
The USER_CONVERSATION_GONG_ACTIVITIES table includes the following:
Column | Type | Value to delete | Description |
|---|---|---|---|
CONVERSATION_KEY | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The ID of the conversation the user made the activity on (from the conversations table) |
GONG_ACTIVITY_DATETIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | Unchanged | The date and time of the activity |
GONG_ACTIVITY_TYPE | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The activity type. Options are:
|
USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The ID of the user who had the activity (from the users table) |
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. |
Interaction_stats
The INTERACTION_STATS table contains statistics about how a rep manages their calls. Each row includes statistics for a single call, such as the rep's talk ratio, and interactivity. For a full explanation of how these metrics are calculated, see Analyze team performance.
The INTERACTION_STATS 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 ID of the call in the conversations table |
CALL_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The call ID |
CALL_OWNER | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Gong user ID of the person who owns the call |
INTERACTIVITY | Snowflake: float BigQuery: float64 Databricks: float, double Redshift: real, float4, float8, double precision S3: float | NULL | Indicates the number of times the conversation switched between the rep and the customer. The value is based on a calculation which normalizes the number of times the conversations switched size to a 60 minute conversation. |
LONGEST_CUSTOMER STORY | Snowflake: float BigQuery: float64 Databricks: float, double Redshift: real, float4, float8, double precision S3: float | NULL | The longest amount of time at any one time the customer spoke in the call |
LONGEST_MONOLOGUE | Snowflake: float BigQuery: float64 Databricks: float, double Redshift: real, float4, float8, double precision S3: float | NULL | The longest amount of time the user spoke at one time in the call in seconds |
PATIENCE | Snowflake: float BigQuery: float64 Databricks: float, double Redshift: real, float4, float8, double precision S3: float | NULL | The average amount of time the rep waited before speaking after the customer finished speaking, in seconds |
QUESTION_RATE | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | The average number of questions the rep asked in the call |
TALK_RATIO | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | The percentage of time the user spoke in the call |
USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The ID of the user who participated in the call (from the users table) |
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates that the stats were deleted in Gong. The stats are also deleted in Snowflake when a conversation is deleted. Values are:
|
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. |
Workspaces
The WORKSPACES table contains a list of the workspaces in your org and includes the following:
Column name | Type | Value on delete | Description |
|---|---|---|---|
NAME | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The name of the workspace |
WORKSPACE_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The workspace ID |
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 |
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates whether the workspace was deleted in Gong. Values are:
|
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. |
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:
|
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:
|
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:
|
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 | 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 ??? |
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):
|
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates whether the conversation context was deleted in Gong. Values are:
|
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 |
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:
|
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:
|
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. |
Gong_usage
The GONG_USAGE table contains information on how team members use Gong on a daily basis. Each row contains the number of times a unique action was done on a specified day. So for example, if a team member listens to 6 calls in one day, but listens to one call twice, the CALLS_LISTENED_TO column will be 5. If a team member listens to the same call on two different days, this results in two records in this table.
Metrics on how many unique calls a team member listened to in a specific time period is available by downloading the Feature utilization report,
The table includes the following fields:
Column name | Type | Value on delete | Description |
|---|---|---|---|
ACCOUNTS_ASKED_ANYTHING | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of accounts for which the person asked at least one question on the USAGE_DATE. Asking multiple questions about the same account counts as one account. |
ADDED_PEOPLE_TO_FLOWS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of times the user added a person to a flow in Engage |
AI_EMAILS_GENERATED | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of times the person clicked Generate follow-up email on the USAGE_DATE. Includes all clicks, regardless of where the option appears. |
ASKED_ANYTHING_ABOUT_A_CALL | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of questions the user asked anything about a call |
ASKED_ANYTHING_ABOUT_A_DEAL_OR_ACCOUNT | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of questions the user asked anything about a deal or account |
CALL_SCORECARDS_GIVEN | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Only shows data if the user is a manager. Number of scorecards the user filled in. |
CALLED_WITH_GONG_DIALER | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of calls the user made with the Gong dialer |
CALLS_ASKED_ANYTHING | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of calls for which the person asked at least one question on the USAGE_DATE. Asking multiple questions about the same call counts as one call. |
CALLS_LISTENED_TO | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of calls the user listened to in Gong |
COMMENTED_ON_CALLS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of comments the user made on calls |
COMPLETED_TO_DOS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of Engage to-dos completed |
CONDUCTED_FOLLOW_UP_STEPS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of follow-up steps such as inline edits, the user did on a deal |
CONTACTS_ASKED_ANYTHING | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of contacts for which the person asked at least one question on the USAGE_DATE. Asking multiple questions about the same contact counts as one contact. |
DEALS_ASKED_ANYTHING | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of deals for which the person asked at least one question on the USAGE_DATE. Asking multiple questions about the same deal counts as one deal. |
INSPECTED_DEALS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of deals the user looked at in detail (opened the deal panel) |
INTERACTED_WITH_CALL_SPOTLIGHT (deprecated) | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Returns 0 |
MINUTES_LISTENED_TO_CALLS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of minutes the user listened to calls in Gong |
PLAYBOOK_FIELDS_AI_SUGGESTIONS_USED | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of times the person validated an AI suggestion in a Playbook field on a deal board on the USAGE_DATE. |
PLAYBOOK_FIELDS_MANUAL_UPDATES | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of Playbook fields the person manually updated on the USAGE_DATE. Multiple updates to the same field count as one. |
RECORDED_CALLS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of calls recorded in Gong for this user |
REVIEWED_CALLS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of calls the user reviewed |
REVIEWED_DEAL_ANALYTICS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of times the user viewed one of the deal analytics reports (win/loss, deal drivers) |
REVIEWED_FORECAST | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of times the user did an action in the Forecast page, not including loading the page |
REVIEWED_PIPELINE | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of times the user clicked on anything in the deal page |
SENT_EMAILS_VIA_GONG | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of emails the user sent via the Gong email composer |
SHARED_CALLS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of calls the user shared either internally or externally |
SUBMITTED_FORECASTS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of times the user submitted or updated a forecast |
THEME_REPORTS_GENERATED | Coming soon | ||
THEME_REPORTS_VIEWED | Coming soon | ||
USED_FORECAST_ANALYTICS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of times the user performed an action in the Forecast analytics page, not including loading the page |
USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The user’s Gong ID |
USER_NAME | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The user’s full name |
USAGE_DATE | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | NULL | The date the usage data is for |
VIEWED_ACCOUNTS_WITH_BRIEFS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of accounts for which the person viewed a brief on the USAGE_DATE. Viewing the same brief multiple times counts as one account. |
VIEWED_ANALYTIC_REPORTS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of times the user viewed a report in Insights |
VIEWED_CALLS_WITH_BRIEFS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of calls for which the person viewed a brief on the USAGE_DATE. Viewing the same brief multiple times counts as one call. |
VIEWED_CALL_SPOTLIGHT (deprecated) | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Returns 0 |
VIEWED_CONTACTS_WITH_BRIEFS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of contacts for which the person viewed a brief on the USAGE_DATE. Viewing the same brief multiple times counts as one contact. |
VIEWED_DEAL_BOARD_WITH_PLAYBOOK | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of deal boards that include a playbook the person viewed on the USAGE_DATE. Viewing the same deal board multiple times counts as one. |
VIEWED_DEALS_WITH_BRIEFS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of deals for which the person viewed a brief on the USAGE_DATE. Viewing the same brief multiple times counts as one deal. |
VIEWED_INITIATIVE_BOARDS | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: FIXED_LEN_BYTE_ARRAY, Decimal | NULL | Number of times the user viewed an initiative board |
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates whether the record was deleted in Gong. Values are:
|
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:
|
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. |
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:
|
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:
|
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 |
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:
|
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 |
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:
For calls options are:
For meetings options are:
|
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:
|
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. |
Comments
The COMMENTS table contains a row for each public comment made on a call. The COMMENTS table includes the following:
Column name | Type | Value on delete | Description |
|---|---|---|---|
COMMENT_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The Id of the comment |
COMMENT | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The comment |
COMMENT_TYPE | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | The type of comment | |
CONVERSATION_KEY | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The unique identifier for the call the comment is associated with. (Unique) |
CREATED_DATETIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | NULL | The date and time the comment was made |
MENTIONS | Snowflake: variant BigQuery: json Databricks: string Redshift: varchar(MAX) S3: UTF8 | NULL | A list of users tagged in the comment. Ids are separated with a comma |
REPLY_TO_COMMENT_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | ID of the original comment this comment is replying to. |
TAGS | Snowflake: variant BigQuery: json Databricks: string Redshift: varchar(MAX) S3: UTF8 | NULL | A list of tags set for the comment. Tags are phases prefixed with a #. Each tag in the list is separated with a comma |
TIME_IN_CALL_SEC | Snowflake: float BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: Float | NULL | The time in the call the comment was made, in seconds. |
USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Gong user ID for the person who made the comment. |
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates whether the comment was deleted in Gong. Values are:
|
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. |
Forecast_submissions
The FORECAST_SUBMISSIONS table contains the most current team and individual forecasts submissions. To see previous submissions use the FORECAST_SUBMISSIONS_HISTORY table.
Note:
This table shows manual user submissions. As forecasts in Gong may also include automated submissions, you may see forecast submissions in Gong which are not exported to Snowflake.
The table contains the following fields:
Column name | Type | Value on delete | Description |
|---|---|---|---|
FORECAST_AMOUNT_UNIT | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The unit the forecast was made in |
FORECAST_CATEGORY_NAME | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The forecast category according to the values defined in the forecast board |
IS_TEAM | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | NULL | When true, the forecast is a team forecast |
LINE_OF_BUSINESS | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The name of the line of business the forecast is for |
LINE_OF_BUSINESS_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The Gong ID for the line of business |
NOTES | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | Notes the Gong user made on the forecast submission |
PERIOD_NUMBER | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The number representing the period the forecast is for. For example, if the forecast is for Q3, this value is 3. If the forecast is for August, this value is 8. |
PERIOD_TYPE | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The period the forecast covers. Options are:
|
PERIOD_YEAR | Snowflake: integer BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric | NULL | The fiscal year the forecast covers |
SUBMIT_DATE | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | NULL | The date the forecast was submitted |
SUBMIT_BY_USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Gong user id of the user who submitted the forecast |
SUBMISSION_TYPE | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The type of forecast submission. Options are:
|
USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The user Id of the Gong user the forecast is for. If a manager submits a forecast for their team member, the USER_ID is the user Id of the team member. If the forecast is a team forecast, this is the team manager's user Id. |
VALUE | Snowflake: float BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: Float | NULL | The forecast value |
WEEK | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: INT_64 | NULL | The week during the quarter that the forecast was submitted |
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates whether the forecast was deleted in Gong. Values are:
|
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. |
Forecast_submissions_history
The FORECAST_SUBMISSIONS_HISTORY table contains current and previous team and individual forecasts submissions. Use the SUBMIT_DATE to determine which is the most recent submission.
Note:
This table shows manual user submissions. As forecasts in Gong may also include automated submissions, you may see forecast submissions in Gong which are not exported to Snowflake.
The table contains the following fields:
Column name | Type | Value on delete | Description |
|---|---|---|---|
FORECAST_AMOUNT_UNIT | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The unit the forecast was made in |
FORECAST_CATEGORY_NAME | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The forecast category according to the values defined in the forecast board |
IS_TEAM | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | NULL | When true, the forecast is a team forecast |
LINE_OF_BUSINESS | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The name of the line of business the forecast is for |
LINE_OF_BUSINESS_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The Gong ID for the line of business |
NOTES | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | Notes the Gong user made on the forecast submission |
PERIOD_NUMBER | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The number representing the period the forecast is for. For example, if the forecast is for Q3, this value is 3. If the forecast is for August, this value is 8. |
PERIOD_TYPE | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The period the forecast covers. Options are:
|
PERIOD_YEAR | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: decimal | NULL | The fiscal year the forecast covers |
SUBMIT_DATE | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | NULL | The date the forecast was submitted |
SUBMIT_BY_USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Gong user id of the user who submitted the forecast |
USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The user Id of the Gong user the forecast is for. If a manager submits a forecast for their team member, the USER_ID is the user Id of the team member. If the forecast is a team forecast, this is the team manager's user Id. |
VALUE | Snowflake: float BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: Float | NULL | The forecast value |
WEEK | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: Decimal | NULL | The week during the quarter that the forecast was submitted |
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates whether the forecast was deleted in Gong. Values are:
|
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. |
Forecast_targets
The FORECAST_TARGETS table contains targets set for each team or for specific users. The table contains the following fields:
Column name | Type | Value on delete | Description |
|---|---|---|---|
IS_TEAM | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | NULL | When true, the target is a team target |
LINE_OF_BUSINESS | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The name of the line of business the forecast is for |
LINE_OF_BUSINESS_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The Gong ID for the line of business |
PERIOD_NUMBER | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: Decimal | NULL | The number representing the period the forecast is for. For example, if the forecast is for Q3, this value is 3. If the forecast is for August, this value is 8. |
PERIOD_TYPE | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The period the forecast covers. Options are:
|
PERIOD_YEAR | Snowflake: integer BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric | NULL | The fiscal year the forecast covers |
SUBMIT_DATE | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | NULL | The date the forecast was submitted |
SUBMIT_BY_USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Gong user id of the user who submitted the forecast |
TARGET_AMOUNT_UNIT | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The currency code the forecast is submitted in |
USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The user Id of the Gong user the forecast is for. If a manager submits a forecast for their team member, the USER_ID is the user Id of the team member. If the forecast is a team forecast, this is the team manager's user Id. |
VALUE | Snowflake: float BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: Float | NULL | The forecast value |
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates whether the forecast target was deleted in Gong. Values are:
|
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. |
Deal_likelihood_scores
The DEAL_LIKELIHOOD_SCORES table shows a ranking Gong gives to each deal. This is a score that indicates the relative deal health according to the company's historical closed-won and closed-lost deal scores. It is calculated daily, and the new score added to the table, providing history of how the deal likelihood changed.
As the table is a standalone table, to get the details of the deal, retreive the deal details from the CRM according to the CRM_DEAL_ID. The table contains the following fields:
Column name | Type | Description |
|---|---|---|
CRM_DEAL_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | The Id of the deal in the CRM that the deal likelihood score is for. Use this field to get the deal details from the CRM. |
LAST_UPDATED | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | The date the score was last calculated |
SCORE | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: decimal | The numerical score for the deal likelihood |
SCORE_CATEGORY | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | The category for the deal likelihood score. Values are: 1-29: Low 30-75: Fair 76-99: High |
ETL_MODIFIED_DATETIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | The date and time the data was modified |
ROW_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | The ID to identify the row in the table |
Scorecard_questions
The SCORECARD_QUESTIONS table contains a row for each question in a scorecard. The row includes the scorecard data such as the scorecard name and the date it was created. The answers for the questions are stored in the SCORECARD_ANSWERS table. The table contains the following fields:
Column name | Type | Value on delete | Description |
|---|---|---|---|
IS_DELETED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates whether the scorecard or the question were deleted |
QUESTION_CREATED_DATETIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | NULL | The date and time the question was defined |
QUESTION_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The Id of a question included in the scorecard |
QUESTION_IS_OVERALL_SCORE | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | NULL | Indicates whether the question enables providing an overall assessment of the call |
QUESTION_MAX_RANGE | Snowflake: integer BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric | NULL | For questions with a numerical score, the maximum number that can be chosen |
QUESTION_MIN_RANGE | Snowflake: integer BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric | NULL | For questions with a numerical score, the minimum number that can be chosen |
QUESTION_MODIFIED_BY_USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Id of the user who modified the question |
QUESTION_MODIFIED_DATETIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | NULL | The date and time the question was last modified |
QUESTION_RESPONSE_OPTIONS | Snowflake: variant BigQuery: json Databricks: string Redshift: varchar(MAX) S3: UTF8 | NULL | The possible options in a multiple choice question |
QUESTION_TEXT | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The text of the question |
QUESTION_TYPE | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The type of question. Options are:
|
SCORECARD_CREATED_DATETIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | NULL | The date and time the scorecard was created |
SCORECARD_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The scorecard Id |
SCORECARD_IS_ENABLED | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | NULL | Indicates whether the scorecard is enabled or not |
SCORECARD_MODIFIED_BY_USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Id of the Gong user who last modified the scorecard |
SCORECARD_MODIFIED_DATETIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | NULL | The date and time the scorecard was last modified |
SCORECARD_NAME | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The scorecard title |
WORKSPACE_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Id of the workspace the scorecard is associated with |
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. |
Scorecard_answers
The SCORECARD_ANSWERS table contains a row for each answer given in the scorecard. The row includes scorecard details, the question details and the answer given. The table contains the following fields:
Column name | Type | Value on delete | Description |
|---|---|---|---|
ACCESSIBLE_TO | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The users who have permissions to view the scorecard. Options are:
|
ANSWER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The ID for the answer |
ANSWER_CREATED_DATETIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | NULL | The date and time the answer was created |
ANSWER_MODIFIED_DATETIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | The date and time the answer was last modified | |
ANSWER_NOT_APPLICABLE | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | Unchanged | Indicates if the answer is not applicable |
ANSWER_SELECTED_OPTIONS | Snowflake: variant BigQuery: json Databricks: string Redshift: varchar(MAX) S3: UTF8 | NULL | The options selected in a multiple choice question |
ANSWER_SCORE | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: decimal | NULL | The score given to the question |
ANSWER_TEXT | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The text of the answer |
CONVERSATION_KEY | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The key for the conversation the scorecard is being filled in for |
GAVE_SCORECARD_USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Id of the user who filled in the scorecard |
LAST_PUBLISHED_DATETIME | Snowflake: timestamp_tz BigQuery: timestamp Databricks: timestamp Redshift: timestamp, timestamptz S3: INT64, TIMETAMP_MICROS | NULL | The date and time the answer was last published |
QUESTION_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Id of the question |
QUESTION_IS_OVERALL_SCORE | Snowflake: boolean BigQuery: bool Databricks: boolean Redshift: boolean S3: Boolean | NULL | Indicates whether the question enables providing an overall assessment of the call |
QUESTION_MAX_RANGE | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: decimal | NULL | For questions with a numerical score, the maximum number that can be chosen |
QUESTION_MIN_RANGE | Snowflake: number BigQuery: decimal, numeric Databricks: decimal, dec, numeric Redshift: decimal, numeric S3: decimal | NULL | For questions with a numerical score, the minimum number that can be chosen |
QUESTION_RESPONSE_OPTIONS | Snowflake: variant BigQuery: json Databricks: string Redshift: varchar(MAX) S3: UTF8 | NULL | The possible options in a multiple choice question |
QUESTION_TEXT | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The text of the question |
QUESTION_TYPE | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The type of question. Options are:
|
RECEIVED_SCORECARD_USER_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Id of the user who the scorecard was for |
SCORECARD_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | Unchanged | The scorecard Id. FK from the SCORECARD_QUESTIONS table. |
SCORECARD_NAME | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The name of the scorecard |
WORKSPACE_ID | Snowflake: varchar BigQuery: string Databricks: string Redshift: varchar(MAX) S3: Byte_array, UTF8 | NULL | The Id of the workspace the scorecard is associated with |
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 changed |
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. |
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