From Setup to First Query: Set up zero-copy access from SAP Business Data Cloud to Google BigQuery in seven steps, with step-by-step screenshots.
Unifying Enterprise Context: The Power of SAP and Google Cloud Synergy
SAP systems run the core of the enterprise, including finance, supply chain, HR, and customer experience, through end-to-end processes like Order-to-Cash, Procure-to-Pay, Plan-to-Produce, Record-to-Report, and Hire-to-Retire. To make fast, data-driven decisions and put AI to work, organizations want to combine native SAP business semantics with Google Cloud data and AI capabilities.
Historically, connecting these platforms required data replication pipelines, which added complexity, latency, and challenges in maintaining native SAP business context and hierarchies.
To simplify this, Google Cloud and SAP co-engineered SAP Business Data Cloud (BDC) Connect for Google BigQuery — now generally available.
Using a zero-copy architecture powered by open-source Delta Sharing with built-in access controls, this integration lets you query live SAP BDC data products directly from BigQuery — and vice versa — without building replication pipelines. This helps bring the scale of BigQuery to your SAP data while keeping governance in place and data fresh.
Official Resources & Key Documentation
Before diving into the configuration steps, bookmark these official resources to reference during your rollout:
Google Cloud Blog: SAP and Google Cloud launch BDC Connect for BigQuery
Google Documentation: About SAP Business Data Cloud integration | Lakehouse Docs
SAP Community: Announcing GA of SAP BDC Connect for Google BigQuery
Google Cloud docs: Set up cross-cloud connection for SAP BDC
SAP Help: Obtaining Access to Data Products through SAP Business Data Cloud Connect
Keep these open in a tab. The rest of this post walks through each configuration step.
Roles & Responsibilities: Team Alignment Matrix
You’ll need three people (or one person wearing three hats):
- BigQuery Administrator: Handles BigQuery Enterprise Plus capacity setup, sets up the Lakehouse catalog, and executes queries on shared tables through the Google Cloud Console.
- SAP Administrator: Deploys the BDC Connect instance, links the Google Cloud Service Account, and generates the activation link (connector endpoint and invitation code) in SAP for Me.
- SAP BDC User: Finds data products in the SAP BDC catalog, requests access, and installs them to the BDC Connect instance for BigQuery (Step 7).
Prerequisites & System Readiness
Before you begin the step-by-step walkthrough, verify that you have completed these preparation steps on both platforms.
- Tenant deployment: Ensure your SAP BDC environment is active on a supported cloud platform (such as Google Cloud or AWS).
- Ensure your SAP administrator has access to your SAP BDC environment to configure the BDC Connect application
- You must have appropriate IAM permissions in Google Cloud to create and manage Lakehouse Catalogs: BigLake Admin (roles/biglake.admin) or BigQuery Admin (roles/bigquery.admin).
- The target Google Cloud project must use BigQuery Enterprise Plus Edition.
Step-by-Step Screenshot-Guided Walkthrough
- Phase 1: Google Cloud Environment Preparation (Steps 1–3) — Configure BigQuery Enterprise Plus capacity, assign your project to the reservation, and initiate the Lakehouse Delta Sharing catalog.
- Phase 2: SAP BDC Provisioning & Mutual Handshake (Steps 4–6) — Provision the connector in SAP for Me, exchange credentials to enroll the catalog, and link the connection into the SAP landscape formation.
- Phase 3: Data Federation & Live BigQuery Analytics (Step 7) — Share SAP data products from the SAP BDC Catalog & Marketplace and execute zero-copy SQL queries directly within BigQuery Studio.
Step 1: [BigQuery Admin | Google Cloud] Enable BigQuery Enterprise Plus Capacity
1. Access the BigQuery interface via the Google Cloud Console.
2. Navigate through the sidebar to Administration > Workload management > Capacity management.
3. Click Create Reservation.
Administration → Workload management → Capacity Management. Click Create Reservation to start.
4. Reservation Name: Assign a unique identifier, such as gcp-sap-bdc-connect-bq (the name used in this walkthrough).
5. Location: Choose the specific region hosting your datasets; this must align with your Lakehouse catalog setting.
6. Edition: Pick Enterprise Plus from the available options.
- Why Enterprise Plus? BDC Connect queries require BigQuery Enterprise Plus edition. With baseline slots set to 0 and autoscaling on (below), you pay for autoscaled slots while queries run instead of paying for idle baseline capacity.
7. Slots:
- Configure Baseline slots to 0: This avoids paying for idle baseline capacity.
- Turn on Auto Scaling so BigQuery adds slots only while queries are running, up to the maximum you set. For this demo we used Extra Small (50 slots) as the maximum, which is enough for a few test queries. For production, size the maximum to your own workloads as part of your sizing exercise. The BigQuery slot estimator can help.
8. Finalize the configuration by clicking Save.
Your new reservation now appears under Capacity management:
The new Enterprise Plus reservation, ready for an assignment.
Step 2: [BigQuery Admin | Google Cloud] Assign Your Project to the Reservation
- Navigate to the Capacity management page.
From the reservation’s Actions menu, choose Create assignment.
2. Select your newly created reservation ID, then click the More actions menu (three dots) under the Actions column.
3. Click + Create Assignment.
4. For Rule type, select Job Routing (Assignment).
5. Select a resource: Choose the Project, Folder, or Organization that will be running the BigQuery jobs.
6. Job type: Select Query (this routes query jobs to the Enterprise Plus reservation). You can also add assignments for Pipeline or Background jobs if required.
A Job Routing rule for your project with job type QUERY. The Rule Summary shows where the jobs go.
7. Click Continue.
8. Reservation: Select the Enterprise Plus reservation created in the previous step (e.g., “gcp-sap-bdc-connect-bq”).
9. Click Continue. Your project will appear under your reservation (in this walkthrough, the reservation name and project ID share the name gcp-sap-bdc-connect-bq).
Your project now sits under the reservation, so its queries use Enterprise Plus capacity.
Verification: Once assigned, query jobs run within that project use Enterprise Plus capacity. You can verify this by checking the Job Information in the BigQuery Job History; it should list the reservation name and edition.
Step 3: [BigQuery Admin | Google Cloud] Create the Lakehouse Delta Sharing Catalog
A Delta Sharing catalog in Lakehouse serves as your gateway to federating with the remote SAP BDC catalog.
1. Enable the BigLake API.
2. Review the roles required to enable APIs, then select Enable the API.
3. In the Google Cloud console, open the Lakehouse page: Go to Lakehouse
4. In the navigation menu, click Runtime catalog.
5. Click Create catalog and select Federated catalog.
Lakehouse → Runtime catalog → Create catalog → Federated catalog.
6. In the Catalog configuration section, enter the following:
a. For Federated catalog source, select SAP (Business Data Cloud).
b. For Catalog name (in Lakehouse), enter a name for your catalog.
c. For Data location, select the same Lakehouse region as reservation.
Choose SAP (Business Data Cloud) as the source, name the catalog, and pick its region.
Click Continue. The next screen, Connection details, asks for a Connector endpoint and an Invitation code. You don’t have these yet. Your SAP admin generates them in Step 4, and you’ll come back here to enter them in Step 5. For now, continue past this screen.
Copy this service account. Your SAP administrator needs it in Step 4.
7. Click Continue.
8. Retrieve the Google Cloud Service Account ID displayed on the page and provide this ID to your SAP administrator.
Why this matters: This service account is how SAP BDC recognizes and trusts BigQuery. When your SAP administrator registers this ID during BDC Connect provisioning, SAP BDC authorizes BigQuery to query Delta Sharing endpoints directly without needing static credentials, passwords, or shared secret keys.
Step 4: [SAP Admin | SAP for Me] Configure the BDC Connect Instance
Your SAP administrator must sign in to SAP for Me and provision a new instance of the BDC Connect application:
- Go to Portfolio & Products and select Business Data Cloud.
In SAP for Me, open Portfolio & Products and select your Business Data Cloud package.
2. Under Business Data Cloud, click Application.
3. Locate SAP Business Data Cloud Connect and click Start Provisioning.
On the Applications tab, find SAP BDC Connect and click Start Provisioning.
4. Enter the Display Name.
5. Select or create a Resource Group.
Give the solution a name and choose where it lives, then click Next Step.
6. Allocate BDC Capacity Units (CUs). How many you need depends entirely on your SAP BDC sizing exercise. Estimate your expected workloads with SAP’s Capacity Unit Cost Estimator, then assign quota to match. We used 10 CUs for this demo, which may not be a production recommendation.
Assign Capacity Units to SAP BDC Connect. We used 10 for this demo.
7. In the External System Instance Identifier field, provide the Google Cloud service account ID you copied in Step 3.
8. Choose a Region. Ensure this matches the region where your SAP BDC tenant is located (the BDC Core region).
Paste the Google Cloud service account and choose the region of your SAP BDC tenant.
9. Click Review, verify the details, and then click Finish.
10. Upon selecting Finish, a notification prompt entitled Creating solution will appear:
Your provisioning request for the 'GCP BDC Demo' solution has started and its resources are being set up in the selected resource group. The provisioning process can take a few moments to complete.
The new Solution resource will achieve the Ready status when all tenants are successfully provisioned, and integrations are fully established.
11. Navigate to the Resources view to monitor deployment progress for provisioned components.
While provisioning runs, the status shows Processing. View Notifications shows the progress.
After completion, go to the tenant details view. Hold the pointer over the View Tenant Notifications button to get the Activation Link, which contains the SAP Connector Endpoint and the SAP Invitation Code.
The tenant notification holds the activation URL, with both the endpoint and the invitation code.
Provide the following activation parameters to your BigQuery administrator to complete the connection handshake:
Deconstructing the Handshake URL
When enrolling the catalog in the Google Cloud Console, split the activation URL into its two core parameters:
- Connector Endpoint: The base URL preceding ?code= (e.g., https://d1xxxx-xxx-xxxxx-xxx-xxxxxx.sharing.xx.xxxx-xxxx.hanaxxxx.ondemand.com).
- Invitation Code: The alphanumeric token following ?code= (e.g., 11exxx-xxxx-xxxx-xxxxx-xxxxxx6).
Separating these parameters accurately helps prevent handshake authentication errors during catalog enrollment. The most common setup mistake is pasting the whole URL into the endpoint field.
The status of this connection in SAP BDC remains “Processing” until the enrollment steps in BigQuery are complete.
Both the solution and the connector stay in Processing until you finish enrollment in BigQuery.
Step 5: [BigQuery Admin | Google Cloud] Complete the Handshake & Enroll Catalog
To finalize the authentication handshake between SAP BDC and the Google Cloud Console, enroll the catalog using the values from your SAP admin.
1. Navigate to the Lakehouse page in Google Cloud Console. If the session timed out or was closed, re-open it via the main menu by selecting Runtime catalog.
2. Open the Catalog details page by selecting your targeted SAP Delta Sharing catalog.
3. Locate the top banner and click Enroll catalog.
4. Fill in the required information under Connection details:
- Connector endpoint: Paste the URL supplied by your SAP administrator.
- Invitation code: Enter the authentication code provided by your SAP administrator.
Paste the endpoint and invitation code into Connection details, then click Save.
5. Click Save.
This completes the authentication handshake between SAP BDC and Google Cloud. The two platforms now trust each other.
Before sharing SAP BDC data products with Google BigQuery using the SAP BDC connection, complete one final setup and configuration step within SAP BDC to finalize system integration and permit data access.
Step 6: [SAP Admin | SAP BDC Landscape] Link BDC Connection to System Formation
Once enrollment finishes, the connection status in SAP BDC changes from “Processing” to “Ready.”
Why Formation Linking is Essential: In SAP BDC, components operate inside isolated security boundaries. Deploying a connector instance establishes the runtime, but it cannot access your enterprise SAP tenant data products until it is formally bound into your Customer Landscape System Formation.
After enrollment, both the solution and the connector show Ready.
1. Add the newly created instance (bdc-connect-854cc5e7) directly into your designated system formation.
2. Navigate to the Customer Landscape overview tab.
3. Locate your specific target BDC tenant and select Include System.
On Customer Landscape, open your BDC formation and click Include Systems.
4. Choose your established BDC connection from the list, click Next to review the system assignment details, and confirm by selecting Include.
Select your BDC Connect instance to include it in the formation.
5. The system initiates automated background synchronization across systems; once this workflow finishes, the fully configured integration appears within your assigned formation.
6. Following successful setup, the instance bdc-connect-854cc5e7 becomes fully visible and active in SAP BDC, enabling direct live data product sharing with Google BigQuery. If it doesn’t appear, sync the BDC formation and check again.
Step 7: [SAP BDC User & BigQuery Analyst] Share a Data Product and Query It in BigQuery
This is where everything comes together. The connection is in place, so now you decide which SAP data BigQuery can see. We’ll share one data product, Maintenance Order, and then query it from BigQuery Studio. In our demo, the SAP side took only a few minutes.
7a. Confirm the connector is in your landscape
In SAP BDC, open System Landscape. You should see your connector (bdc-connect-854cc5e7 in our case) listed in your formation with the type SAP BDC Connect for Google BigQuery. If it’s there, Step 6 worked and you’re ready to share.
The BDC Connect instance is listed in the formation. That’s your green light.
7b. Find the data product
Open Catalog & Marketplace → Search and switch to the Data Products tab.
Catalog & Marketplace → Search, on the Data Products tab.
Search for Maintenance Order. You’ll probably see more than one result, because the same data product can come from different source systems. Check the system name on each card and pick the one from the source system connected to your formation.
7c. Choose BigQuery as the target
Click the cart icon at the top right to open the Request Cart. Under Target System, click Select System.
Open the Request Cart and pick a target system before adding anything.
Search for your connector and select it.
Typing the last few characters of the instance name helps you find it quickly.
Tip: If you see “Some systems are unavailable for selection,” don’t worry. It refers to other systems in the formation. Your connector just needs to appear in the list.
7d. Add the data product and send the request
With the target set, click Supported Data Products so you only see products this connector can receive. Then click the cart icon on the Maintenance Order card, check that it appears in the Request Cart, and click Proceed.
Target system set and Maintenance Order in the cart. Next, click Proceed.
In the Request Access dialog, add a short comment (it’s required, so something like “SAP demo share” is fine), tick the terms-and-conditions box, and click Send. The end date is optional.
Add a comment, accept the terms, and click Send.
7e. Confirm the share is installed
A notification should appear shortly saying the data product is installed to your connector and ready to use.
Access Request Approved” means the share is live.
In our demo tenant, approval came through in seconds. In your landscape, the request may wait for the data product owner to approve it, so check with your SAP administrator if nothing arrives.
To double-check, click on the Notification or open Catalog & Marketplace → Data Product Access and select the Agreements tab. Maintenance Order should show Installed with status Current. If it hasn’t been installed yet, open the agreement and click Install. The data product does not appear in BigQuery until this is done.
The agreement details confirm the data product is installed on the BigQuery connector.
That’s everything on the SAP side. Over to BigQuery.
7f. Find the data in BigQuery Studio
In the Google Cloud console, open BigQuery → Studio. In the Explorer, expand your project and click Datasets. The shared data product appears as a new dataset with its source shown as SAP. You don’t need to import or load anything. If it isn’t there yet, give it a minute and click Refresh.
The SAP data product appears as a dataset, with Source shown as SAP.
The dataset name may look long. It’s built from your catalog, the data product (share), and its schema: catalog.share.schema. Open it and you’ll see that one data product contains a whole set of related tables, such as the order header, operations, partners, and status texts, organized just as they are in SAP.
One data product, many tables, all queryable in place.
On the Details tab, the catalog info shows Source: SAP and Type: Delta Sharing. That confirms BigQuery is reading the data from SAP through Delta Sharing, not from a replicated copy.
Type: Delta Sharing confirms the data is read in place, with no replication.
Click a table, such as maintenanceorder, to see its schema. The field names are the SAP business names your teams already know.
SAP field names and data types, preserved as-is.
7g. Run your first query
Click Query (or open a new query tab). Start with a simple SELECT to see the data, then try a more focused question, such as the 50 most recent preventive maintenance orders (PM01). Replace <source_system> with the dataset name you see in your Explorer:
SELECT *
FROM `gcp-sap-bdc-connect-bq.bdc-con-bq-catalog.maintenanceorder_v1_<source_system>.maintenanceorder.maintenanceorder`
LIMIT 1000;
- Preventive maintenance orders (PM01), most recent first
SELECT
MaintenanceOrder,
MaintenanceOrderType,
MaintenanceOrderDesc,
MaintOrdBasicStartDate,
MaintOrdBasicEndDate
FROM `gcp-sap-bdc-connect-bq.bdc-con-bq-catalog.maintenanceorder_v1_<source_system>.maintenanceorder.maintenanceorder`
WHERE MaintenanceOrderType = 'PM01'
ORDER BY MaintOrdBasicStartDate DESC
LIMIT 50;
Both queries read live data straight from SAP BDC, so you don’t need to schedule copies or keep pipelines running. Here’s the first query running in BigQuery Studio:
Live SAP maintenance orders, queried from BigQuery. Some values are masked in this screenshot.
Summary
In seven steps you connected SAP Business Data Cloud to BigQuery, without building a single pipeline:
- On Google Cloud, you set up Enterprise Plus capacity and created a Lakehouse Delta Sharing catalog.
- In SAP for Me, you provisioned BDC Connect and generated the activation link. Back in Google Cloud, you enrolled the catalog to complete the handshake, and then added the connector to your SAP BDC formation.
- Then your SAP BDC user installed the Maintenance Order data product, and it appeared in BigQuery as a dataset you could query right away, with native SAP field names intact.
The result: your analysts can work with up-to-date SAP data where it lives, governed by SAP at the source and by IAM on the Google Cloud side, with no copies to schedule or maintain.
Good to know before production
Before you move to production, review the current limitations in the Google Cloud documentation (Limitations and considerations) and the SAP BDC Connect documentation on SAP Help. They cover access control, supported data product names, metadata refresh and caching, and data residency, and they change as the product evolves.
Appendix: Key Concepts and Terms
- Lakehouse: The Google Cloud service that manages catalogs and metadata for open table formats such as Apache Iceberg, so engines like BigQuery can query data where it lives, including across clouds.
- Federated Delta Lake Catalog: A Lakehouse catalog type that connects to SAP BDC using the open Delta Sharing protocol. This is the catalog you create in Step 3.
- Federated Catalog: How BigQuery keeps SAP BDC metadata current. It asks the remote SAP BDC catalog for its shares, schemas, and tables, so you don’t copy or maintain that metadata by hand.
- Connection: The part of the Lakehouse catalog that links and authenticates BigQuery and SAP BDC, using the connector endpoint and invitation code from Steps 4 and 5.
SAP BDC data appears in BigQuery in a five-level hierarchy that follows the Delta Sharing protocol:
PROJECT_ID.CATALOG_ID.SHARE_NAME.SCHEMA_NAME.TABLE_NAME
The queries in Step 7g use exactly this path.
- Catalog ID: The Lakehouse catalog resource in your Google Cloud project, and the top-level container for everything shared from one SAP BDC Connector (bdc-con-bq-catalog in this walkthrough).
- Share (SAP Data Product): A logical group of tables shared for consumption, such as Maintenance Order. Each data product maps to a Delta Sharing share, the first level under the catalog.
- Schema (Delta Schema): The second level, inside a share. It groups related tables.
- Table (SAP Table): The data object inside a schema, such as maintenanceorder. This is what you query in BigQuery.
- SAP BDC Connector: The SAP BDC configuration that authorizes access from a specific Google Cloud project, through the service account you registered in Step 4.
Parishudh Marupurolu
NorthEASTAm SAP And Google
Google Cloud
#abap