CRM & Sales
Salesforce schema
SightShark syncs Salesforce into a data warehouse you own. It creates 3 tables holding 93 fields, refreshed daily. Opportunities, leads and accounts.
3 tables / 93 fields / Provisional
Provisional
The table names below follow this site’s naming convention rather than a production sync, and the field names follow the documented Salesforce schema. Confirm both against your own dataset before you rely on them.
Tables and fields
Every table this connector creates. Field lists come from the production sync where we publish it, and otherwise from the documented schema, marked on the table.
salesforce_opportunities
9 fields
- opportunity_id
- account_id
- name
- stage
- amount
- probability
- close_date
- is_won
- lead_source
salesforce_leads
42 fields, documented schema
- id
- status_id
- city
- company
- converted_account_id
- converted_contact_id
- converted_date
- converted_opportunity_id
- country
- created_by_id
- created_date
- email_bounced_date
- email_bounced_reason
- first_name
- industry
- is_converted
- is_deleted
- is_unread_by_owner
- jigsaw_contact_id
- last_activity_date
- last_modified_by_id
- last_modified_date
- last_name
- last_referenced_date
- last_viewed_date
- latitude
- lead_source
- longitude
- master_record_id
- name
- number_of_employees
- owner_id
- phone
- photo_url
- salutation
- state
- status
- street
- system_modstamp
- title
- website
salesforce_accounts
42 fields, documented schema
- id
- account_source
- annual_revenue
- billing_city
- billing_country
- billing_geocode_accuracy
- billing_latitude
- billing_longitude
- billing_postal_code
- billing_state
- billing_street
- created_by_id
- created_date
- description
- industry
- is_deleted
- jigsaw
- jigsaw_company_id
- last_activity_date
- last_modified_by_id
- last_modified_date
- last_referenced_date
- last_viewed_date
- master_record_id
- name
- number_of_employees
- owner_id
- parent_id
- phone
- photo_url
- shipping_city
- shipping_country
- shipping_geocode_accuracy
- shipping_latitude
- shipping_longitude
- shipping_postal_code
- shipping_state
- shipping_street
- sic_desc
- system_modstamp
- type
- website
Where it lands
Into a warehouse you already own, in a region you pick. The modelling runs inside that project, so nothing leaves your cloud to be transformed and we keep no copy of your history.
- Google BigQuery
- Snowflake
- Databricks
- AWS Redshift
- Azure Synapse
Revenue lives in the CRM and spend lives in the ad platforms, so nobody can put cost and closed revenue in one table without exporting both by hand.
Questions people ask
What tables does SightShark create from Salesforce?
3 tables, including salesforce_opportunities, salesforce_leads, salesforce_accounts. salesforce_opportunities is one row per opportunity. Every one is listed on this page, with its fields.
Which Salesforce fields can I get?
The 93 fields on this page, table by table. Lists marked documented schema follow the published schema for Salesforce, and your own warehouse may carry a few more or fewer.
How often does Salesforce data refresh?
Daily. A sync adds to the tables rather than replacing them, so when a platform restates a figure for a day that has already closed, both the original number and the correction stay on record.
Can I join Salesforce data to my other platforms?
Yes. Every metric is modelled to one name, one type, one grain and one currency, so a query across Salesforce and another source needs no reconciling of field names first.
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A call with someone who can answer the schema questions.