Bridging Legacy Data Models and SAP Datasphere with SphereAhead

By Anish Menon • Principal Architect

SAP Datasphere migration is one of the most challenging aspects of modernizing enterprise data landscapes. While migrating legacy HANA Calculation Views, SQL Views, Stored Procedures, and ABAP CDS Views, teams often spend significant time understanding existing logic before rebuilding it.

To simplify this process, we developed SphereAhead, a tool that analyzes legacy artifacts and generates SAP Datasphere-ready outputs and rebuild guidance. 

This blog is a walkthrough of the problem it tries to solve, how the tool works today, and how it is intentionally designed to evolve alongside SAP Datasphere.

THE PROBLEM

Whenever I came across a legacy object like a HANA calculation view or a SQL view or even a CDS view – things i would ask myself is

  1. What should i convert this object into in Datasphere.
  2. Then the major time consuming problem would be to understand the logic behind each of these objects as they would be buried deep in code. 
  3. Then I would make a list of actions that need to be carried out to achieve this.
  4. Also estimate the time that it would take for me to do all of the above.

A lot of this is assumption or guessing rather than a clear framework and a lot of time and energy is invested on this. 

Hence moving to SAP Datasphere is not just about migrating individual objects. We do not have a one‑click path from existing models to new ones. The artifacts need to be understood as to how they are designed, why they are designed and then rebuilt accordingly in Datasphere. Then we would also need to manually write down the logic in the Datasphere artifact.

The Philosophy

SphereAhead was created to address exactly this gap. It acts as a practical bridge between legacy data models and SAP Datasphere by:

  • Making dependencies and structure explicit,
  • Translating technical artifacts into human‑readable guidance, and
  • Generating Datasphere‑ready artifacts that accelerate the rebuild process.

The goal is confident redevelopment in a faster manner.

WHAT SPHEREAHEAD CAN INGEST TODAY

SphereAhead understands four major artifact types end-to-end.

1

HANA Calculation Views

  • Parses .hdbcalculationview XML
  • Extracts:
    • Projection / Join / Aggregation / Union nodes
    • Filters, join conditions, mappings
    • Measures, calculated measures, attributes
2

SQL Views

  • Parses .hdbview or plain SQL
  • Detects:
    • Source tables/views
    • Aggregations, GROUP BY, HAVING
    • Filters and join complexity
3

Stored Procedures

  • Parses HANA SQL / SQLScript procedures
  • Detects:
    • Read/write dependencies
    • Temporary tables and CTAS patterns
    • Calls to other procedures
4

ABAP CDS Views

  • Parses CDS source text
  • Detects:
    • Extraction enablement
    • CDC annotations
    • Parameters (and their impact)

Human Output: Auto Generated Rebuild Guides (DOCX)

SphereAhead generates rebuild guides. Each DOCX includes:

  • Context and assumptions
  • Source objects and parameters
  • Step‑by‑step rebuild instructions in Datasphere
  • Validation checklist
  • Known gaps / manual actions

Machine Output: Datasphere Ready Artifacts

SphereAhead can generate importable artifacts in multiple formats:

Neutral CSN

  • Template‑free & Tenant‑independent.

Native CSN (Template‑Based)

  • Uses tenant‑exported Datasphere artifacts

Replication Flows (ABAP CDS)

  • Clones Replication Flow templates
  • Injects:
    • Source CDS
    • Load type (Initial / Delta)
    • Target tables
  • Optionally links to Analytic Models

All outputs are bundled into ZIP packages with a manifest ready to import.

A TOOL DESIGNED TO EVOLVE

SphereAhead is intentionally not a finished migration product.

Datasphere itself is evolving rapidly — and any serious tooling around it must evolve alongside it. From day one, the goal has been to build a strong semantic foundation first, then expand capabilities safely and incrementally. Here are a few directions actively being explored, on experimental basis, if possible.

1 Native Analytic Model Generation
2 Graphical View Generation
3 Toward Automated Object Creation

FINAL THOUGHTS

Modernizing legacy data models for SAP Datasphere is not a copy‑and‑paste exercise. It requires understanding how existing logic works and how they translate into a new modeling paradigm.
SphereAhead was built to make this work more transparent, more predictable, and more repeatable.
That journey is ongoing  and very intentional.
To know more, please feel free to reach out to us at sales@bpterp.com or visit: Sphereahead – Blueprint Technologies

HAPPY MODELING! 

Anish Menon

Principal Architect – Analytics

Anish is an Architect at Blueprint Technologies. He works alongside cross-functional delivery teams and business leaders to architect end-to-end data pipelines and actionable analytics solutions leveraging SAP Datasphere, SAC, and enterprise data platforms.