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Data warehouse ⇄ Analytics

BigQuery to Microsoft Power Bi integration — real-time data sync

Keep BigQuery and Microsoft Power Bi in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Why teams connect BigQuery and Microsoft Power Bi

Flow Microsoft Power Bi data into BigQuery in real time — no exports, no schedulers, no custom scripts.

Microsoft Power Bi is a read-only source: Stacksync reads its data in real time and delivers it into BigQuery, so BigQuery always reflects the current state of Microsoft Power Bi — without exports, scripts, or schedulers.

Microsoft Power Bi is where teams explore, visualize, and report; BigQuery is the store of record that holds the raw tables and full history behind those views. The two overlap wherever the same events, users, and metrics matter to both, and when the bridge between them is a nightly export or a hand-built extract, dashboards lag the warehouse and analysts spend the morning arguing over whose number is right.

Common use cases

  • 01 Pull Dataflow and Datasource definitions to document lineage between Power BI and its upstream warehouses in a governance database.
  • 02 Load dataset Refresh History into an operational database to alert on-call teams when scheduled refreshes fail or run long.
  • 03 Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
  • 04 Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools

Common sync patterns

One number both sides agree on

Metrics and aggregates stay aligned between the two systems, so a figure shown in Microsoft Power Bi matches the BigQuery table it was built from instead of drifting between refreshes.

Where BigQuery holds the source tables: live data in the reporting layer

Records maintained in BigQuery flow into Microsoft Power Bi as they change, so dashboards and reports read current rows rather than an overnight extract.

Where Microsoft Power Bi produces segments or scores: results back to the warehouse

Cohorts, segments, and computed metrics defined in Microsoft Power Bi write to BigQuery as tables the rest of the stack can query and join.

What you can sync between BigQuery and Microsoft Power Bi

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

BigQuery objects Microsoft Power Bi objects How this pairing syncs
Tables The syncable unit: only tables can be synced per the Stacksync docs. Datasets (Semantic Models) Tabular models behind reports; their rows are read with DAX via POST datasets/{id}/executeQueries, and datasource and refresh metadata via REST list endpoints. Tables is specific to BigQuery and Datasets (Semantic Models) to Microsoft Power Bi — each maps to any object or custom field on the other side.
Partitioned tables Synced like regular tables; partition columns map to target fields. Reports Report definitions and metadata read via GET /reports and per-workspace GET /groups/{id}/reports; enumerated to mirror the content inventory into a catalog. Partitioned tables is specific to BigQuery and Reports to Microsoft Power Bi — each maps to any object or custom field on the other side.
Clustered tables Supported; clustering is transparent to the sync. Dashboards and Tiles Dashboards and their pinned tiles read via GET /dashboards and /dashboards/{id}/tiles; inventoried to map dashboard content back to its source datasets. Clustered tables is specific to BigQuery and Dashboards and Tiles to Microsoft Power Bi — each maps to any object or custom field on the other side.
Datasets Organizational container — you pick which dataset’s tables to sync. Dataflows Power Query ETL definitions read via GET /groups/{id}/dataflows; used to document lineage from upstream sources into datasets. Datasets is specific to BigQuery and Dataflows to Microsoft Power Bi — each maps to any object or custom field on the other side.
Projects Connection scope: the service account grants access per project. Datasources and Gateways The connections behind datasets and dataflows and the on-premises gateways serving them, read via REST for lineage and dependency mapping. Projects is specific to BigQuery and Datasources and Gateways to Microsoft Power Bi — each maps to any object or custom field on the other side.

How changes propagate between BigQuery and Microsoft Power Bi

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

BigQuery Microsoft Power Bi Sub-second propagation

DetectionChanges in BigQuery are captured at the source via change data capture — no polling loop against its API. Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen").

DeliveryMicrosoft Power Bi does not accept inbound record writes, so this direction carries requests rather than records: Microsoft Power Bi's output flows back as field updates on the originating BigQuery records.

Microsoft Power Bi BigQuery Interval-based propagation

DetectionStacksync polls Microsoft Power Bi for changes on an incremental schedule, reading only records changed since the previous pass. Pull-based: no webhooks or change-data-capture.

DeliveryEach detected change is applied to BigQuery as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • BigQuery: Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes.
  • Microsoft Power Bi: Endpoints throttle per user and per app and return HTTP 429 with a Retry-After header. Execute Queries allows up to 120 requests per minute per user and caps a query at 100,000 rows (or 1,000,000 values) and 15 MB; admin scanner metadata APIs are limited to about 500 requests per hour with 16 concurrent.
What ships with BigQuery ⇄ Microsoft Power Bi

Connect BigQuery and Microsoft Power Bi for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every BigQuery–Microsoft Power Bi connection.

Real-time

Real-time sync

Changes in BigQuery or Microsoft Power Bi instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever BigQuery or Microsoft Power Bi data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single BigQuery or Microsoft Power Bi record.

Observability

Monitoring

Track your BigQuery ⇄ Microsoft Power Bi sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between BigQuery and Microsoft Power Bi.

How the BigQuery and Microsoft Power Bi connectors work

BigQuery

Integration surface
GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
Authentication
Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver
Change detection
Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in
Capabilities
read · write · CDC
Rate limits
Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
BigQuery setup guide

Microsoft Power Bi

Integration surface
Power BI REST API, including the Execute Queries (DAX) endpoint and admin scanner APIs; a read-write XMLA endpoint is available on Premium, Premium-Per-User, and Fabric capacity.
Authentication
Microsoft Entra ID (Azure AD) OAuth 2.0 bearer tokens. Supports delegated user tokens and app-only service principals; service principals must be enabled under the tenant's Developer settings and granted workspace access. Tenant-wide admin reads require the Tenant.Read.All scope.
Change detection
Pull-based: no webhooks or change-data-capture. Content is polled via REST list endpoints, dataset changes are inferred from Refresh History and the admin Activity Events audit log, and the scanner API's GetModifiedWorkspaces reports workspaces changed since a given time.
Capabilities
read
Rate limits
Endpoints throttle per user and per app and return HTTP 429 with a Retry-After header. Execute Queries allows up to 120 requests per minute per user and caps a query at 100,000 rows (or 1,000,000 values) and 15 MB; admin scanner metadata APIs are limited to about 500 requests per hour with 16 concurrent.
How it works

How to connect BigQuery to Microsoft Power Bi — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate BigQuery and Microsoft Power Bi with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    BigQuery connected
    Microsoft Power Bi connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the BigQuery and Microsoft Power Bi objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · BigQuery ⇄ Microsoft Power Bi
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    BigQuery Microsoft Power Bi
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

BigQuery and Microsoft Power Bi integration FAQ

SECURITY

Security teams trust Stacksync

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.

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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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 474 integrations available for BigQuery and Microsoft Power Bi.

Popular · 8 of 474
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