SAP BW 7.5 mainstream maintenance ends December 31, 2027. For organizations that have relied on Business Warehouse for reporting and analytics—some for over two decades—this deadline marks a critical inflection point. But migrating away from SAP BW isn’t as simple as moving data; it means translating years of embedded business logic, rebuilding extraction mechanisms, and planning for a future that may also include S/4HANA.
This FAQ addresses the questions we hear most often from data teams navigating this transition, from timeline planning through architecture decisions to how Coalesce can compress multi-year migration projects into months.
Timeline & planning
When does SAP BW support end?
SAP BW 7.5 mainstream maintenance ends December 31, 2027. Extended maintenance is available through 2030 at an additional cost (a two percentage point premium on existing maintenance fees), but provides only critical fixes—no new features, security updates, or product innovation. SAP BW/4HANA follows a different timeline and will be maintained through at least 2040, aligned with the S/4HANA roadmap.
What happens to BEx reporting tools?
BEx Excel-dependent tools (BEx Analyzer, BEx Workbooks, and BEx Broadcaster/Pre-calculation Server) entered customer-specific maintenance on October 15, 2025, following Microsoft’s end of support for Office 2016 and 2019. Under customer-specific maintenance, SAP provides limited support with no guaranteed response times or SLAs. BEx Query Designer and BEx Web Application Designer remain supported until 2027 (mainstream) or 2030 (extended maintenance), as they don’t depend on Excel.
How long does an SAP BW to Snowflake migration typically take?
Migration timelines vary significantly based on system complexity, but the business logic translation is typically the longest phase. Organizations using manual approaches often face multi-year projects due to the effort required to reverse-engineer undocumented ABAP code. Companies using automated transformation tools like Coalesce have compressed these timelines to months by eliminating manual code translation and automating pipeline creation with AI-powered assistance.
Should we wait for our S/4HANA migration before migrating away from SAP BW?
No. Waiting creates what’s called the “double migration dilemma”—your analytics migration becomes dependent on your ERP migration timeline, delaying both projects. The recommended approach uses a medallion architecture (bronze/silver/gold layers) that treats ECC and future S/4HANA as separate data sources. You can migrate from SAP BW immediately, and when S/4HANA goes live, it simply becomes a second source integrated at the silver layer—without rebuilding reports or business logic.
Migration challenges
What are the biggest challenges in SAP BW migration?
Four primary challenges define most SAP BW migration projects:
- Business logic translation: SAP BW contains thousands of lines of ABAP code accumulated over 15-20 years. Snowflake doesn’t execute ABAP, so this logic must be converted to SQL. Manual reverse-engineering of undocumented legacy code introduces significant human error risk—if numbers don’t match historical reports, business users won’t trust the new system.
- Data extraction complexity: SAP has built-in mechanisms for moving data from ERP to BW, including CDC (change data capture), delta loads, and deletion handling. Bypassing BW means rebuilding these capabilities, typically using third-party ETL tools with native SAP connectors.
- The double migration dilemma: Many organizations are planning both a BW migration and a future S/4HANA migration. Building a Snowflake data warehouse on current ECC table structures creates a foundation that becomes deprecated when S/4HANA goes live.
- Security and governance: SAP has a granular authorization model where users see only data for their authorized company codes or organizational units. This row-level security must be replicated in Snowflake to avoid exposing sensitive HR, financial, or operational data.
How do I convert ABAP transformation logic to SQL?
Direct ABAP-to-SQL conversion isn’t possible in a single step. The typical approach involves: (1) documenting existing transformation logic from BW objects, (2) using AI tools like ChatGPT to generate equivalent SQL as a starting point, (3) validating and refining the SQL in a transformation platform. Coalesce’s Copilot can then take this SQL—whether generated or harvested from legacy systems—and automatically build documented, maintainable data pipelines with full column-level lineage, proper staging layers, and standardized patterns.
What happens to my SAP BW business logic during migration?
Without automation, critical business context embedded in legacy code is at risk. Custom ABAP routines, start/end routines, and transformation rules often lack documentation after years of modifications by different developers. Manual reverse-engineering is time-consuming and error-prone. Coalesce addresses this by using AI (powered by Claude) to interpret SAP metadata, translate technical German table and column names into business-friendly terms, and automate pipeline creation—preserving logic while creating maintainable, documented code.
How do I extract data from SAP for migration?
The recommended approach is bypassing SAP BW entirely and extracting directly from your source ERP system (ECC or S/4HANA). Options include:
- Third-party ETL tools: Solutions like Fivetran, Matillion, or Qlik have native SAP connectors that read raw data and handle CDC by reading SAP log files—no custom development required.
- CDS Views (S/4HANA only): Core Data Services views are part of SAP’s Virtual Data Model and provide pre-joined, business-ready data. Instead of joining multiple cryptic tables, you extract the final view directly.
- Direct table extraction: For simpler scenarios, raw table extraction with transformation handled downstream in Snowflake.
Going direct to the source improves performance (eliminating BW as a latency layer) and avoids building new dependencies on a sunsetting platform.
Architecture & approach
What is the best target architecture for SAP BW migration?
The medallion architecture (bronze/silver/gold layers) is the recommended approach for SAP BW migrations because it solves multiple challenges simultaneously:
- Bronze layer: Ingests raw data exactly as it exists in the source system, preserving full audit history.
- Silver layer: Harmonizes and transforms data, applying business logic. Critically, this layer handles integration of multiple sources—both current ECC data and future S/4HANA data can be mapped and harmonized here.
- Gold layer: Delivers business-ready data models (star schemas, flat/wide tables, or Data Vault structures) optimized for downstream consumption by BI tools and applications.
This architecture provides auditability (raw data preserved), agility (changes isolated to appropriate layers), and future-proofing (new sources added without rebuilding downstream assets).
How does the medallion architecture solve the double migration dilemma?
The medallion architecture decouples your analytics migration from your ERP migration by treating them as separate data sources rather than sequential dependencies. Here’s how it works:
- Start immediately: Ingest ECC data into the bronze layer in raw format.
- Build transformation logic: Create silver layer transformations that apply your business rules.
- Deliver to business: Build gold layer models consumed by dashboards and reports.
- Add S/4HANA later: When HANA goes live, add it as a second bronze source. The silver layer handles field mapping between old and new structures, key translation, and timeline continuity.
Business users see one continuous data timeline—the complexity of dual sources is abstracted away in the silver layer.
Can I use Data Vault methodology for SAP migration?
Yes, Data Vault is particularly well-suited for SAP migrations. Its hub-and-satellite structure handles the dual-source scenario elegantly: when your S/4HANA source comes online, it becomes another satellite attached to existing hubs rather than requiring a rebuild. Coalesce and Scalefree (a Data Vault consulting specialist) have partnered to develop “Data Vault for Coalesce,” a package specifically designed to automate Data Vault pattern implementation for migrations like SAP BW to Snowflake.
What tools do I need for a complete SAP BW to Snowflake migration?
A typical SAP BW to Snowflake migration stack includes:
- Extraction layer: Third-party ETL tool with native SAP connectors (handles CDC, delta loads, and data movement)
- Cloud data platform: Snowflake (target data warehouse)
- Transformation layer: Coalesce (automates pipeline building, business logic translation, and documentation)
- BI/Reporting layer: Your choice of visualization tool (Power BI, Tableau, Sigma, etc.) connecting to Snowflake gold layer tables
Coalesce specifically handles the transformation challenge—taking raw SAP data landed in Snowflake and building the bronze-to-gold pipeline with proper staging, business logic, and presentation layers.
Coalesce capabilities
How does Coalesce help with SAP BW migration?
Coalesce accelerates SAP BW migration through AI-powered automation across several dimensions:
- Metadata translation: Copilot automatically converts cryptic SAP table names (like MARA, MARC, MAKT) and column names into business-friendly English, using Claude AI which is extensively trained on SAP terminology.
- Mass pipeline creation: A single prompt can generate stage tables for dozens of source tables simultaneously, each with properly renamed columns and documentation.
- Automatic join logic: Copilot understands SAP table relationships and can join tables (like materials and material descriptions) without manual specification of join keys.
- SQL reverse-engineering: Existing SQL scripts—whether harvested from legacy systems or generated by AI—can be converted into visual, documented pipelines with full column-level lineage.
- Standardized templates: Node types enforce consistent patterns (staging, dimensions, facts) across your team, eliminating “spaghetti code” and ensuring maintainability.
- Git-native workflow: All pipeline metadata is stored as YAML, enabling proper version control, code review, and CI/CD deployment to UAT and production.
Can Coalesce translate SAP metadata in languages other than English?
Yes. Coalesce’s Copilot has been tested with multiple languages including German and French, producing equivalent results to English. This is particularly relevant for SAP environments where table and column names often use German abbreviations. The underlying AI (Claude) understands SAP terminology across languages and can translate technical names into business-friendly terms in your preferred language.
What can Coalesce Copilot do specifically for SAP data?
Based on demonstrated capabilities, Coalesce Copilot can:
- Add stage tables with business-friendly names: Prompt it to create staging layers for your SAP sources, and it will generate tables with translated column names and auto-generated documentation.
- Create hash keys for business key management: Request hash keys on specific tables, and Copilot identifies the appropriate business key columns and generates the concatenated hash transformation.
- Join SAP tables intelligently: Ask it to join materials (MARA) with material descriptions (MAKT), and it determines the correct join logic without explicit specification.
- Build fact tables with merge logic: Request a fact table, and Copilot creates the appropriate node type with business key selection and incremental load patterns.
- Reverse-engineer complex SQL: Paste a multi-CTE SQL script with window functions, aggregations, and filters, and Copilot breaks it into discrete pipeline stages with preserved lineage.
- Generate documentation automatically: Every object created includes table descriptions and column documentation based on SAP metadata context.
Does Coalesce work with Snowflake for SAP migrations?
Yes, Coalesce supports Snowflake. It generates Snowflake-native SQL and supports Snowflake-specific features including:
- Dynamic tables for automated refresh
- Tasks and streams for incremental processing
- Standard tables and views
- Proper DDL and DML separation
All code executes natively in Snowflake—Coalesce is the development and orchestration layer, while Snowflake handles compute and storage. This means you get Snowflake’s full scalability, separation of storage and compute, and usage-based pricing for your migrated SAP data.
What is Coalesce Catalog and how does it help with SAP migration?
Coalesce offers two products: Transform (for building pipelines) and Catalog (for data governance and discovery). While Transform handles the migration build, Catalog provides:
- Holistic visibility: See your entire data landscape from sources through to reports (Power BI, Sigma, etc.)
- Impact analysis: Understand who uses which data assets before making changes
- KPI management: Define and track business metrics across your migrated data
- Existing SQL discovery: Catalog can surface existing SQL from your environment, potentially useful for understanding legacy logic during migration
For SAP migrations, Catalog helps ensure governance continuity—you can track data lineage from original SAP sources through transformation to final business consumption.
Getting started
How do I evaluate Coalesce for our SAP BW migration?
Coalesce offers hands-on labs where you can experiment with Copilot capabilities using SAP-like data scenarios. During these labs, you can:
- Connect to sample SAP tables migrated to Snowflake
- Use Copilot to create staging layers with translated column names
- Build transformations and fact tables
- Experience the Git-based deployment workflow
Contact Coalesce to schedule a demo session tailored to your migration scenario.
What does a typical SAP BW migration project look like with Coalesce?
A typical engagement follows this pattern:
- Assessment: Identify which SAP BW objects are actively used and need migration (vs. legacy objects that can be retired)
- Architecture design: Define medallion layer structure, Data Vault approach if applicable, and target data models
- Extraction setup: Configure ETL tool with SAP connectors for source data movement to Snowflake
- Transformation build: Use Coalesce to build bronze-to-gold pipelines, leveraging Copilot for acceleration
- Validation: Compare outputs against historical BW reports to verify business logic accuracy
- Deployment: Promote pipelines through UAT to production using Git workflows
- Cutover: Transition users from BW-based reports to Snowflake-based reports
Last updated: January 2026. Timeline information based on official SAP maintenance announcements. Contact Coalesce or SAP directly for the most current support dates