The four destinations
| Path | What it is | What you keep | What you rebuild | Lock-in | Suits |
|---|---|---|---|---|---|
| BW/4HANA | The successor BW product | Modeling paradigm, much of the object structure, team skills | Legacy objects not supported in BW/4, some transformation logic | High, within the SAP stack | SAP-dominant reporting, deep BW skills in house, modest analytics ambition |
| SAP Business Data Cloud | SAP’s managed data fabric with curated data products | SAP semantics, governance, data product definitions | The warehouse layer itself, and BW-specific modeling | Moderate to high | You want SAP-curated data with an open path outward |
| SAP Datasphere | SAP’s cloud data warehouse | SAP semantics and connectivity | BW modeling, most transformation logic | Moderate | You want to stay SAP-native but leave BW’s modeling behind |
| Snowflake | Independent cloud data platform | Nothing structurally. This is a rebuild | Modeling, transformation logic, semantic layer, security model | Low | Substantial non-SAP data, broad analytics and AI ambitions, an engineering team |
Where we think Snowflake wins
Snowflake is the right destination when SAP is a major source of your analytics but not the whole of it. That describes most of the manufacturers, distributors and healthcare organizations we work with. SAP holds finance, supply chain and orders, while the questions the business wants answered also involve CRM, IoT, web, claims or third-party market data.
In that situation, staying inside the SAP estate means either federating everything back into SAP or running two analytics platforms. Both cost more over five years than a single independent platform with SAP as one well-governed source. Snowflake also separates your analytics roadmap from your ERP roadmap, which matters if an S/4HANA program is going to occupy your SAP team for the next two years.
The zero-copy sharing SAP and Snowflake now support removes what used to be the strongest objection, that leaving the SAP estate meant fighting SAP to get the data.
Where Snowflake is the wrong answer
We would rather say this here than in month three of an engagement.
Stay with BW/4HANA when your reporting is overwhelmingly SAP-sourced, your analytics requirements are stable and largely financial, and your team’s skills are deeply BW-centric with no appetite or budget to rebuild them. The migration is genuinely smaller because the paradigm carries over. Buying an independent platform to run SAP-only finance reporting means paying for options you have no plan to use.
Look at Datasphere when you want out of BW’s modeling constraints but have a strong governance or commercial reason to stay SAP-native: a group standard, an existing commitment, or a landscape where SAP semantics really are the business model.
Treat BDC as the connective layer rather than as the competitor to Snowflake. The question worth asking is whether BDC belongs in your ingestion path, and the answer is often yes regardless of which destination you choose.
What decides it
Three questions settle most of it, in this order.
First, what proportion of your analytics needs data that SAP does not hold? Above roughly a third, an independent platform starts to win on total cost, and the gap widens over time.
Second, what can your team realistically operate? A platform your people cannot run leaves you permanently dependent on consultants. In some organizations this is a genuine argument for BW/4HANA, and we make it when it applies.
Third, what else is running? A concurrent S/4HANA program changes sequencing, capacity and sometimes the answer itself.
None of these can be settled from a slide. They come out of looking at what the estate contains and who reads its output, which is what the BW Estate Assessment is for.