SAP + Snowflake Integration
Automate SAP Snowflake integration for master data, orders, and finance workflows without any code required.
Faster month-end close with automated Invoice and GL sync
Sales visibility from Contacts and Orders in Snowflake
Reduce reconciliation time using automated settlement and reports
Today
Disconnected systems, manual handoffs, missed SLAs
- Companies struggle with disconnected SAP processes and fragmented analytics, leading to manual handoffs, data silos, and missed SLAs.
- Finance teams rekey Invoices and GL entries, sales teams reconcile Contacts and Leads, operations manage Orders and Deliveries offline, and support delays Ticket updates.
- These manual steps cause reporting errors, delayed forecasts, and audit gaps, increasing operational costs and reducing trust across teams reliant on accurate SAP master and transactional records.
- IT spends cycles on brittle scripts and manual extracts daily instead.
With Koodisi
Automated Sync with Koodisi
- Koodisi automates SAP to Snowflake pipelines so HR, finance, sales, and analytics teams stop relying on manual exports.
- Using Koodisi's no-code REST Client, you sync SAP Contacts, Vendors, Orders, Invoices, PurchaseOrders, and GL entries into Snowflake tables and stage areas.
- You can also push transformed customer segments, reconciliation results, and SLA events back to SAP work orders or service Tickets.
- Teams gain faster reporting, single-source truth, fewer reconciliations, and clear audit trails for compliance and forecasting, reduced costs, and visibility.
The sync
What moves, in both directions
SAP and Snowflake stay in step because the sync runs both ways.
Contacts, Vendors, Orders, Invoices, PurchaseOrders, GL entries, Material masters, Delivery records
Customer segments, Reconciliation reports, Forecasts, SLA events, Pricing updates, Analytical scores, Backpopulated Tickets
Automated SAP Snowflake sync speeds decision making, improves data accuracy, reduces reconciliation time, enforces audit trails, and provides traceable lineage so finance, sales, and operations deliver faster closes, better forecasts, and measurable compliance with fewer manual steps every business unit.
Use cases
What teams automate with this integration
The work that moves between SAP and Snowflake today, and what Koodisi takes over.
Finance close automation with SAP Orders
- Trigger: When SAP posts Invoices and GL entries at period end.
- Koodisi captures Invoice and GL record batches, maps fields to Snowflake schemas, and loads them into finance tables.
- Outcome: The finance team runs consolidated P&L and balance sheet reports in Snowflake without manual CSVs.
- Reconciliations between AR, AP, and GL run automatically, exceptions flag Tickets in SAP for accounting review.
- Lineage, timestamps, SLA alerts, and auto-created Tickets speed investigations and drive accountability for finance teams.
Sales analytics from SAP Contacts and Orders
- Trigger: New or updated SAP Contacts and Orders.
- Koodisi pulls Contact, Lead, and Order records, maps customer IDs, and streams them into Snowflake for enrichment.
- Outcome: The sales operations team builds unified customer views and revenue forecasts in BI tools.
- Pipeline stages and order statuses are available in Snowflake for quota planning.
- When segmentation changes occur, Koodisi writes back pricing updates and Tags to SAP Contacts, ensuring CRM and ERP stay synchronized for sales campaigns and commissions.
- Dashboards refresh hourly and alerts notify reps when high-value leads change and owners.
Support ticket reconciliation and SLA tracking
- Trigger: Service Tickets updated in SAP service module or inbound incidents.
- Koodisi extracts Ticket fields, customer references, and related Orders, then deposits them into Snowflake for analytics and SLA measurement.
- Outcome: Support managers monitor first response times, resolution rates, and recurring issue patterns in Snowflake dashboards.
- Escalation rules can create follow-up Tickets or update SAP case notes automatically.
- This reduces missed SLAs, shortens resolution cycles, and gives product and operations teams actionable insights to prioritize fixes.
- Automated reporting, root cause tagging, and prioritized backlogs improve customer satisfaction and retention significantly.
Data warehouse ingestion for analytics pipelines
- Trigger: Scheduled or event-driven extracts from SAP master and transaction tables.
- Koodisi pulls Material masters, BOMs, Orders, Invoices, and Vendor records, transforms field names and data types, and writes incremental loads into Snowflake.
- Outcome: BI and data science teams access clean, queryable datasets for forecasting, inventory optimization, and cost analysis.
- Transformation triggers can start downstream ELT jobs.
- Automated schema checks, change capture, and load audits reduce data drift, accelerate model training, and ensure data teams trust the warehouse.
- Faster ingestion enables real-time dashboards and supports ad hoc exploration by analysts.
The workflow
What this looks like when it runs
- Koodisi sits between SAP and Snowflake as a business-facing integration layer that reacts to trigger events and moves records where teams need them.
- When an Invoice posts, a Contact is updated, or an Order status changes in SAP, Koodisi detects the event, maps the relevant fields to the Snowflake schema, and delivers the data to the appropriate tables.
- Mapping is visual and business-driven so teams define transforms without code.
- Koodisi monitors each transfer, surfaces validation errors, retries failed batches, and creates audit records for compliance.
- If exceptions remain, Koodisi can open Tickets or notify owners.
- The platform uses Koodisi's no-code REST Client for both SAP and Snowflake to authenticate, batch, and deliver payloads, so ops teams run integrations, view logs, and adjust mappings without developer support.
- Reporting, lineage, and SLA dashboards show status by load, business unit, and dataset so leaders measure reliability and prioritize improvements across the enterprise seamlessly.
Invoice → Snowflake financial table
- 1Step 1 description — SAP posts an Invoice which triggers the workflow
- 2Step 2 description — Koodisi retrieves Invoice and GL lines using the REST Client
- 3Step 3 description — Koodisi maps fields and loads records into Snowflake finance tables
- 4Step 4 description — System notifies accounting and creates a Ticket for exceptions
Contact → Snowflake and back to SAP
- 1Step 1 New or updated Contact in SAP triggers extraction
- 2Step 2 Koodisi normalizes and enriches contact data then writes to Snowflake
- 3Step 3 Analytics updates create customer segment tags in Snowflake
- 4Step 4 Koodisi writes segment and pricing updates back to SAP Contacts
Governance
Automated, but still under control
Every run is authorised, recorded, and observable — the part that decides whether automation survives an audit.
Scoped permissions
Role-based access decides who can publish or run the SAP and Snowflake workflows, and who can only watch them.
Every run recorded
Each execution writes an audit trail — what triggered it, what changed, and what the downstream system returned.
Credentials in Key Vault
SAP and Snowflake credentials are stored and retrieved from Key Vault, never pasted into workflow steps.
Traced end to end
OpenTelemetry logs, metrics, and traces show where a run slowed down or failed, rather than reporting one aggregate status.
Routing rules stay readable
Which records sync, and which need approval first, live in a decision table your team can review and change without editing the workflow.
Sensitive fields masked
Personal and commercial values can be masked in logs so an operational record does not become a copy of your customer database.
Ship integrations faster. Operate them without chaos.
Less time on auth, retries, and deployment scripts. More time on the integrations your customers are asking for.
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