BigQuery
Read and write support varies by record
Record types covered in the setup guide
| Record types | Coverage and requirements |
|---|---|
| See connector requirements. Confirm field permissions and sync direction. |
Data warehouse / Business productivity · Two-way sync platform
BigQuery and Microsoft Dynamics 365 integration — two-way sync
Keep supported BigQuery and Microsoft Dynamics 365 records aligned with two-way sync. Give each team access to current data while controlling which system can update each field.
- Field mappings and sync direction under your control
- Inspect and resolve record errors in one dashboard
Two-way sync for supported objects
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Example workflow
Company reporting workflow
Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.
Starting eventA change involving the proposed company table in BigQuery or Microsoft Dynamics 365 Accounts needs a defined result in the other system.
Start with the proposed company table in BigQuery and Microsoft Dynamics 365 Accounts. Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve parent organizations, business units, and currency references before dependent transactions.
Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.
What to verifyUse two organizations with similar names and one with multiple business units. Verify that an update reaches the intended entity only.
Review records and field ownershipMapping essentials
Records and field ownership
Match records by stable IDs and assign an owner for each field. The record notes identify the coverage to check.
Download the mapping worksheetCSV · No email required
| BigQuery record | Microsoft Dynamics 365 record | Record matching | Field ownership |
|---|---|---|---|
| Proposed company tableProposed table; choose its name and schema.Reporting dataset | AccountsProposed record; confirm Stacksync object support. | Retain the source company ID and the destination customer/company ID. Separate legal entities, subsidiaries, and business units; a shared name or web domain is insufficient. | Assign ownership separately for relationship details and finance-controlled billing details. |
| Proposed contact tableProposed table; choose its name and schema.Reporting dataset | ContactsProposed record; confirm Stacksync object support. | Use a stable person/contact ID and an explicit cross-system lookup. Email can change and can be shared, so treat it as a matching clue rather than a universal key. | Keep consent and communication preferences under an agreed authority; a general contact update must not silently resubscribe someone. |
| Proposed deal or opportunity tableProposed table; choose its name and schema.Reporting dataset | OpportunitiesProposed record; confirm Stacksync object support. | Keep the opportunity/deal ID separate from any later order or invoice ID. | The sales process owns qualification and stage changes; downstream financial records have their own state and approval rules. |
Use writable fields from the connected accounts. Read values from read-only fields without writing changes back to them, and define deletion handling separately.
Why teams connect BigQuery and Microsoft Dynamics 365
Put your BigQuery and Microsoft Dynamics 365 data to work
Start with the work your team needs to complete: keep records up to date, make operational data available for reporting, or move data to a new system. Choose one BigQuery and Microsoft Dynamics 365 workflow to test, define what success looks like, and decide who handles failed updates.
Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools
Two-way sync of accounts and contacts with a Postgres or SQL database so engineers query SQL while sales works in Dynamics.
Keep opportunities and orders consistent with the ERP or billing system without manual re-entry.
What records can you sync?
Start with the records your workflow needs. Check each system’s read and write requirements before mapping fields.
Microsoft Dynamics 365
Read and write support varies by record
Record types covered in the setup guide
| Record types | Coverage and requirements |
|---|---|
| Requires account access and compatible change tracking. Confirm field permissions and sync direction. |
| Requires API exposure and compatible change tracking. Confirm field permissions and sync direction. |
Connection essentials
Review how each system connects, detects changes, and permits access to your records.
View setup requirements and limits| Connection requirement | BigQuery | Microsoft Dynamics 365 |
|---|---|---|
| Integration interface | GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs | REST API (Dataverse Web API, OData v4); Finance & Operations apps expose a separate OData data-entity surface |
| Authentication | Dedicated Google Cloud service account and JSON key | Microsoft OAuth sign-in |
| Change detection | The setup provisions notification services using Eventarc and Cloud Run in the customer Google Cloud project. | Incremental sync uses Dynamics Change Tracking; custom entities need Track Changes enabled. |
| Read access | Available for supported records | Available for supported records |
| Write access | Available for supported records | Available for supported records |
Enterprise controls
Security and control for your integrations
Explore security controlsCompliance and data transfers
As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.
- SOC 2 Type II
- ISO 27001
- HIPAA BAA
- GDPR
- CCPA
- DPF US-EU-UK-CH
SSO & SCIM
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Alerts
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Secure connection options
Securely connects to your systems with:
Record-level recovery
Inspect sync errors and use retry and revert controls to resolve failed updates.
Read the recovery guideImplementation
Technical reference
Review setup, record relationships, testing, and recovery for your implementation.
Authentication, permissions and API limits
Connection requirements and limits
BigQuery
- Integration interface
- GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
- Authentication
- Dedicated Google Cloud service account and JSON key; enable the APIs and grant the roles in the authorization guide.
- Change detection
- The setup provisions notification services using Eventarc and Cloud Run in the customer Google Cloud project.
- Read access
- Available for supported records
- Write access
- Available for supported records
Setup requirements
- Enable BigQuery, Cloud Run, Cloud Resource Manager, and Eventarc APIs in the target project.
- Create a dedicated service account with the roles in the authorization guide and supply its credentials through Stacksync.
Limitations to check
- Only tables are supported in the saved guide; ordinary and materialized views are excluded.
- Google Cloud quotas and the selected write method affect capacity; validate the current project limits before a large backfill.
Technical documentation
Documentation reviewed 2026-09-15. Check the linked guides for current account and record requirements.
Microsoft Dynamics 365
- Integration interface
- REST API (Dataverse Web API, OData v4); Finance & Operations apps expose a separate OData data-entity surface
- Authentication
- Microsoft OAuth sign-in: user provides the D365 environment URL, signs in with Microsoft credentials, and accepts the Stacksync app (permissions to read CRM data and interact with OData entities)
- Change detection
- Incremental sync uses Dynamics Change Tracking; custom entities need Track Changes enabled.
- Read access
- Available for supported records
- Write access
- Available for supported records
Setup requirements
- Provide the Dynamics CRM environment URL and authorize the Stacksync app with Microsoft sign-in.
- For custom entities, enable Track Changes in Power Apps/Dataverse before validating incremental updates.
Limitations to check
- Custom-entity change tracking must be enabled before incremental changes can be captured.
Technical documentation
- Authorize Dynamics 365 CRM
- Dynamics 365 CRM
- Enable Changes Detection Capture (CDC) for Custom Entities
Documentation reviewed 2026-09-15. Check the linked guides for current account and record requirements.
Prepare BigQuery and Microsoft Dynamics 365 access
Set up both accounts before testing the mapping. Use test records where available, and identify the account administrator who can approve access and help resolve setup errors.
BigQuery setup checklist
- Enable BigQuery, Cloud Run, Cloud Resource Manager, and Eventarc APIs in the target project.
- Create a dedicated service account with the roles in the authorization guide and supply its credentials through Stacksync.
Setup guides: Authorize BigQuery
Microsoft Dynamics 365 setup checklist
- Provide the Dynamics CRM environment URL and authorize the Stacksync app with Microsoft sign-in.
- For custom entities, enable Track Changes in Power Apps/Dataverse before validating incremental updates.
Setup guides: Authorize Dynamics 365 CRM
Prepare to go live
Record the fields each system can update, the first-load cutoff, both record IDs, the expected update delay, and who handles errors. Complete the tests before production before expanding to more records.
Use the BigQuery and Microsoft Dynamics 365 planning worksheet to capture these decisions. Record the access owner in the worksheet and enter credentials only in the connection setup.
Record identity and field ownership
Keep each record tied to its source ID. Use the references below to choose field owners and preserve relationships between records.
Download the mapping worksheet · CSV, no email required
Reporting dataset
Proposed company table in BigQuery (choose its name) / Accounts
Plan a company dataset while preserving its source meaning.
Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.
- BigQuery
- Your database schema
- Microsoft Dynamics 365
- Object support to establish
- Record identity
- Retain the source company ID and the destination customer/company ID. Separate legal entities, subsidiaries, and business units; a shared name or web domain is insufficient.
- Field ownership
- Assign ownership separately for relationship details and finance-controlled billing details.
Fields to include
- Source record ID
- Legal or display name
- Business-unit reference
- Lifecycle status
- Record dependencies
- Resolve parent organizations, business units, and currency references before dependent transactions.
- Validation
- Use two organizations with similar names and one with multiple business units. Verify that an update reaches the intended entity only.
- Recovery
- Repair the cross-system ID relationship before retrying dependent records; do not merge companies solely to remove a sync error.
References: Microsoft Dynamics 365: Accounts documentation
Reporting dataset
Proposed contact table in BigQuery (choose its name) / Contacts
Plan a contact dataset while preserving its source meaning.
Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.
- BigQuery
- Your database schema
- Microsoft Dynamics 365
- Object support to establish
- Record identity
- Use a stable person/contact ID and an explicit cross-system lookup. Email can change and can be shared, so treat it as a matching clue rather than a universal key.
- Field ownership
- Keep consent and communication preferences under an agreed authority; a general contact update must not silently resubscribe someone.
Fields to include
- Source person ID
- Display name
- Email address
- Organization reference
- Consent state
- Record dependencies
- Resolve the organization relationship and any owner or consent references required by the destination.
- Validation
- Test an email change, two records sharing an email, and a person associated with multiple organizations.
- Recovery
- Hold ambiguous matches for review and reconcile the person ID before retrying; preserve the consent decision already recorded by its owner.
References: Microsoft Dynamics 365: Contacts documentation
Reporting dataset
Proposed deal or opportunity table in BigQuery (choose its name) / Opportunities
Plan a deal or opportunity dataset while preserving its source meaning.
Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.
- BigQuery
- Your database schema
- Microsoft Dynamics 365
- Object support to establish
- Record identity
- Keep the opportunity/deal ID separate from any later order or invoice ID.
- Field ownership
- The sales process owns qualification and stage changes; downstream financial records have their own state and approval rules.
Fields to include
- Source deal ID
- Stage
- Amount and currency
- Expected close date
- Company reference
- Record dependencies
- Map the customer and sales pipeline before the opportunity; map stage values deliberately.
- Validation
- Test a reopened won deal, a stage with no destination equivalent, and an amount using a different currency.
- Recovery
- Suspend downstream creation for a rejected deal and review whether an order already exists before retrying.
References: Microsoft Dynamics 365: Opportunities documentation
Reporting dataset
Proposed prospect or lead table in BigQuery (choose its name) / Leads
Plan a prospect or lead dataset while preserving its source meaning.
Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.
- BigQuery
- Your database schema
- Microsoft Dynamics 365
- Object support to establish
- Record identity
- Retain the lead ID and record its relationship to any converted contact or company.
- Field ownership
- Choose which system may qualify or convert the lead; do not infer identical lifecycle stages.
Fields to include
- Source lead ID
- Qualification status
- Owner reference
- Conversion reference
- Record dependencies
- Resolve owner and campaign references and decide how conversion changes the identity relationship.
- Validation
- Convert a test lead after the first load and verify that it does not create a duplicate person or orphan its activity.
- Recovery
- Repair the lead-to-contact conversion link before replaying later updates.
References: Microsoft Dynamics 365: Leads documentation
Reporting dataset
Proposed product or catalog item table in BigQuery (choose its name) / Products
Plan a product or catalog item dataset while preserving its source meaning.
Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.
- BigQuery
- Your database schema
- Microsoft Dynamics 365
- Object support to establish
- Record identity
- Distinguish the product ID, variant ID, SKU, and price-list entry; they are not interchangeable keys.
- Field ownership
- Assign ownership for catalog content, price, and stock separately.
Fields to include
- Source product ID
- SKU or variant reference
- Description
- Unit of measure
- Price-list reference
- Record dependencies
- Resolve units, variants, categories, and applicable price lists before order lines.
- Validation
- Test two variants of one product, a changed SKU, and a price that applies to only one market or currency.
- Recovery
- Repair the variant or price-list reference before retrying affected order lines; preserve existing transaction prices.
References: Microsoft Dynamics 365: Products documentation
Reporting dataset
Proposed customer invoice table in BigQuery (choose its name) / Quotes, Orders & Invoices
Plan a customer invoice dataset while preserving its source meaning.
Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.
- BigQuery
- Your database schema
- Microsoft Dynamics 365
- Object support to establish
- Record identity
- Retain the invoice ID, issuer/legal entity, and original order reference; invoice numbers alone may overlap.
- Field ownership
- The financial system owns posting and accounting treatment. A posted invoice may need a credit or adjustment process instead of an overwrite.
Fields to include
- Source invoice ID
- Customer or supplier reference
- Line totals
- Currency
- Posting/payment status
- Record dependencies
- Resolve the customer or supplier, account codes, tax, currency, and accounting period before posting.
- Validation
- Test a posted invoice, a partial payment, tax rounding, and a closed accounting period. Compare financial totals within the same entity and currency.
- Recovery
- Determine whether a transaction posted before retrying. Follow the approved adjustment process for posted records.
References: Microsoft Dynamics 365: Quotes, Orders & Invoices documentation
Compare integration approaches
Use BigQuery Proposed company table in BigQuery (choose its name) and Microsoft Dynamics 365 Accounts for the first pilot. Verify its identity and permitted direction, then add dependent records only when the acceptance checks pass.
Stacksync managed sync
- Best fit
- Two-way sync for supported objects. Choose the records, writable fields, and permissions for your workflow.
- Operating responsibility
- Fits ongoing record synchronization when the required operations are supported. Add workflow steps for approvals or business actions that go beyond copying fields.
- Before you choose
- Check record matching: Retain the source company ID and the destination customer/company ID. Separate legal entities, subsidiaries, and business units; a shared name or web domain is insufficient. Verify field coverage, deletion handling, and how changes are detected.
Native vendor integration
- Best fit
- A vendor-built integration may fit if it supports your BigQuery and Microsoft Dynamics 365 record types.
- Operating responsibility
- Can reduce setup for a supported workflow. You may need another method for records or business steps it does not cover.
- Before you choose
- First check whether either vendor offers this integration. If available, verify Proposed company table in BigQuery (choose its name) / Accounts, update direction, account tier, and related-record handling.
Custom API or workflow
- Best fit
- Consider when BigQuery and Microsoft Dynamics 365 need a transformation, approval, or action outside a direct record sync.
- Operating responsibility
- Provides control over business steps; the team owns credentials, version changes, error queues, and reconciliation.
- Before you choose
- Verify endpoint permissions, pagination, quotas, duplicate detection, and failure recovery.
File or scheduled snapshot
- Best fit
- Consider for a one-time BigQuery / Microsoft Dynamics 365 migration or a reporting need with an explicit freshness window.
- Operating responsibility
- Can simplify a bounded transfer; later changes and deletion history require another extraction or a separately designed incremental process.
- Before you choose
- Record the extraction cutoff, source IDs, encoding, date/number formats, and reconciliation totals.
Workflow scenarios and expected results
Company reporting workflow
Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.
Starting event: A change to the selected Proposed company table in BigQuery (choose its name) or Accounts record needs a defined result in the other system.
- Start with BigQuery Proposed company table in BigQuery (choose its name) and Microsoft Dynamics 365 Accounts. Use the record-matching and field-ownership rules from your mapping worksheet.
- Resolve parent organizations, business units, and currency references before dependent transactions.
- Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.
Expected result: Use two organizations with similar names and one with multiple business units. Verify that an update reaches the intended entity only.
If it fails: Repair the cross-system ID relationship before retrying dependent records; do not merge companies solely to remove a sync error.
Contact reporting workflow
Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.
Starting event: A change to the selected Proposed contact table in BigQuery (choose its name) or Contacts record needs a defined result in the other system.
- Start with BigQuery Proposed contact table in BigQuery (choose its name) and Microsoft Dynamics 365 Contacts. Use the record-matching and field-ownership rules from your mapping worksheet.
- Resolve the organization relationship and any owner or consent references required by the destination.
- Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.
Expected result: Test an email change, two records sharing an email, and a person associated with multiple organizations.
If it fails: Hold ambiguous matches for review and reconcile the person ID before retrying; preserve the consent decision already recorded by its owner.
Deal or opportunity reporting workflow
Object-specific availability and field permissions determine this mapping. Use the restrictions shown for each record type.
Starting event: A change to the selected Proposed deal or opportunity table in BigQuery (choose its name) or Opportunities record needs a defined result in the other system.
- Start with BigQuery Proposed deal or opportunity table in BigQuery (choose its name) and Microsoft Dynamics 365 Opportunities. Use the record-matching and field-ownership rules from your mapping worksheet.
- Map the customer and sales pipeline before the opportunity; map stage values deliberately.
- Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.
Expected result: Test a reopened won deal, a stage with no destination equivalent, and an amount using a different currency.
If it fails: Suspend downstream creation for a rejected deal and review whether an order already exists before retrying.
Define an explicit handoff between BigQuery and Microsoft Dynamics 365
Validate the selected objects and operations even where connector-level direction is documented.
Starting event: A business event involving a selected business dataset needs a defined response involving Accounts or Contacts.
- Document what the source event means and which destination record or action should respond. A similar name does not establish a shared entity.
- Retain separate IDs and choose whether the destination is a report, a new work item, or a change to an existing record.
- Assign an approval owner and a duplicate-detection rule before running an action. Use a custom workflow only after its endpoint support is confirmed.
Expected result: An example input has an unambiguous destination and expected result; repeated delivery produces only the intended change.
If it fails: Resolve missing identity or ambiguous business meaning before retrying; route unsupported operations to the implementation owner.
Initial load and acceptance testing
Keep both record IDs with the expected and actual result. Reconcile the same filters and time window in each system.
Proposed company table in BigQuery (choose its name) / Accounts
Test case
Use two organizations with similar names and one with multiple business units. Verify that an update reaches the intended entity only.
Expected result
The expected company relationship is preserved with no duplicate action or unintended write.
Proposed contact table in BigQuery (choose its name) / Contacts
Test case
Test an email change, two records sharing an email, and a person associated with multiple organizations.
Expected result
The expected contact relationship is preserved with no duplicate action or unintended write.
Proposed deal or opportunity table in BigQuery (choose its name) / Opportunities
Test case
Test a reopened won deal, a stage with no destination equivalent, and an amount using a different currency.
Expected result
The expected deal or opportunity relationship is preserved with no duplicate action or unintended write.
Proposed prospect or lead table in BigQuery (choose its name) / Leads
Test case
Convert a test lead after the first load and verify that it does not create a duplicate person or orphan its activity.
Expected result
The expected prospect or lead relationship is preserved with no duplicate action or unintended write.
Direction and permissions
Test case
Check that each connected account can read and write the chosen objects. Exercise both directions with a test record before enabling production changes.
Expected result
Only an approved, supported direction and permitted fields are written.
Freshness and reconciliation
Test case
Measure source and destination times for the selected records under normal load and a burst. Reconcile IDs and values using the same filters and cutoff.
Expected result
The process meets its agreed freshness target and reconciliation has no unexplained differences.
Failed updates, retries and recovery
Start with the failed record and the destination error, then inspect the source value, field requirements, and access.
Rejected or repeated company change
Investigate
Inspect BigQuery Proposed company table in BigQuery (choose its name) and Microsoft Dynamics 365 Accounts, their IDs, and the destination error.
Next action
Repair the cross-system ID relationship before retrying dependent records; do not merge companies solely to remove a sync error.
Rejected or repeated contact change
Investigate
Inspect BigQuery Proposed contact table in BigQuery (choose its name) and Microsoft Dynamics 365 Contacts, their IDs, and the destination error.
Next action
Hold ambiguous matches for review and reconcile the person ID before retrying; preserve the consent decision already recorded by its owner.
Rejected or repeated deal or opportunity change
Investigate
Inspect BigQuery Proposed deal or opportunity table in BigQuery (choose its name) and Microsoft Dynamics 365 Opportunities, their IDs, and the destination error.
Next action
Suspend downstream creation for a rejected deal and review whether an order already exists before retrying.
A record type or update is unavailable
Investigate
Check the BigQuery and Microsoft Dynamics 365 connector guides, account permissions, and any operations marked On Request.
Next action
Ask the integration team to confirm a supported way to handle that record. Verify whether it needs connector configuration or a separate workflow step.
Source and destination disagree after a retry
Investigate
Compare current source values, destination validation, identity mappings, and any side effects already completed.
Next action
Stacksync issue retry reads the current source state. Decide the intended state before retrying or reverting; reconcile downstream effects separately.
Read the Stacksync issues dashboard guide for retry and revert behavior.
Change detection and update delivery
How updates move between BigQuery and Microsoft Dynamics 365
See how each system detects changes and which updates the other system can receive. Each direction has its own permissions and record requirements.
BigQuery Microsoft Dynamics 365 Timing depends on the connected systems
Detect changesThe setup provisions notification services using Eventarc and Cloud Run in the customer Google Cloud project.
Apply updatesSelected writable fields update in Microsoft Dynamics 365. Its permissions and validation rules still apply; rejected records can be inspected in the Issues dashboard.
Microsoft Dynamics 365 BigQuery Timing depends on the connected systems
Detect changesIncremental sync uses Dynamics Change Tracking; custom entities need Track Changes enabled.
Apply updatesSelected writable fields update in BigQuery. Its permissions and validation rules still apply; rejected records can be inspected in the Issues dashboard.
Update timing and record limits
- Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.
- Google Cloud quotas and the selected write method affect capacity; validate the current project limits before a large backfill.
- Custom-entity change tracking must be enabled before incremental changes can be captured.
FAQ
BigQuery and Microsoft Dynamics 365 integration FAQ
-
Stacksync connects BigQuery and Microsoft Dynamics 365 with two-way sync for supported records. Authorize the accounts, select the record types, and map compatible fields. Both connectors support reading and writing; object permissions determine the available fields. Use the Issues dashboard to inspect and resolve rejected updates.
-
Stacksync supports two-way sync between writable records in both systems. The chosen objects and fields must permit updates in both directions. Read-only fields can supply values but cannot receive updates. Stacksync can read database views; it does not write back to the view.
-
Prepare both accounts, the selected object schemas, stable source and destination IDs, and the expected outcome. Enable BigQuery, Cloud Run, Cloud Resource Manager, and Eventarc APIs in the target project. Provide the Dynamics CRM environment URL and authorize the Stacksync app with Microsoft sign-in. Use the pair worksheet to record ownership and acceptance criteria.
-
Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.
-
No. Stacksync documents that pre-existing duplicates are not merged automatically when two-way sync begins. Review the initial dataset and matching plan before enabling it; an empty destination can simplify the first load.
-
Start with one business entity and a stable record ID. Map a small set of editable fields with compatible types, test required values and relationships, then expand after the pilot passes.
-
Check the destination error, field constraints, permissions, and current source value. The Stacksync issues dashboard supports retry and revert; retry reads current source values, so verify the intended record state before acting.
-
Use the current Stacksync pricing page and confirm the supported implementation with the team. Scope the required objects, record volume, update frequency, initial load, and support needs when comparing a managed connector with native or custom development.
-
Start by reviewing Proposed company table in BigQuery (choose its name) in BigQuery and Accounts in Microsoft Dynamics 365. Check how these records relate in your workflow, then confirm the actual fields and supported operations. Test record matching and one failed or repeated update before adding more records.
-
Use BigQuery Proposed company table in BigQuery (choose its name) and Microsoft Dynamics 365 Accounts for the first pilot. Verify its identity and permitted direction, then add dependent records only when the acceptance checks pass.
Integration directory
Related integrations
Review documented support, sync direction, and setup requirements on each pair page. Search all 549 integrations listed for BigQuery and Microsoft Dynamics 365.
Next step
See your workflow in Stacksync
Walk through your BigQuery and Microsoft Dynamics 365 records, field mappings, and requirements with an integration engineer.
