Schedule of services

What we do, in depth.

Four practice areas, all drawn from the same twenty years in one discipline. Depth first — architecture through to SQLScript, not a generalist who subcontracts the hard parts.

Data platform engineering and modernisation

The platform work: architecture, build and the performance engineering that keeps a large SAP estate usable as it grows. Layered EDW design, SQLScript and AMDP development that most consultancies subcontract out, and migration paths that don't stall halfway through.

Typical engagements

BW/4HANA and native HANA architecture and build, including layered EDW design
SQLScript and AMDP transformation development
Performance optimisation on large-volume datasets
Data acquisition from SAP (ECC, S/4HANA, SRM, CRM) and non-SAP sources via BODS and SLT
BW-to-BW/4HANA migration and upgrade paths, including the move toward SAP Datasphere
Hierarchy flattening, complex routine development, calculation view design with analytical privileges

Technologies

SAP BW/4HANA · SAP HANA (native) · SQLScript · AMDP · ABAP · BODS · SLT · SAP Datasphere

Analytics, reporting and adoption

Reporting only earns its keep if people use it after the consultants leave. This practice pairs SAP Analytics Cloud and BI tooling with the report rationalisation, KPI definitions and training that make the numbers trusted long after handover.

Typical engagements

SAP Analytics Cloud and embedded analytics implementation
Power BI and Tableau on SAP data
Requirements workshops and report rationalisation
Report catalogues and KPI definition
Self-service enablement and super-user programs
UAT, training and documented support handover

Technologies

SAP Analytics Cloud · Power BI · Tableau · Business Objects (WEBI, Crystal) · S/4HANA embedded analytics

SAP Business AI and generative AI enablement

Where SAP's AI layer meets an existing data estate. The practical scope: assessing whether a data estate is genuinely AI-ready — governed semantics, clean master data, documented KPIs — before the investment is made, then identifying viable first use cases.

This is an emerging practice area, backed by current certification study rather than a decade of AI delivery. The principal is working toward SAP Certified Associate: Generative AI Developer (C_AIG). We say so plainly — this is informed early adoption, not overstated experience.

Typical engagements

AI-readiness assessment of an existing data estate before investment
Identifying viable first use cases for SAP Business AI and Joule
Prototyping with Joule Studio and the Generative AI Hub on SAP BTP

Technologies

SAP Business AI · Joule · Joule Studio · SAP BTP · Generative AI Hub

Program delivery, governance and stakeholder management

Somebody has to own the risk register, the vendor coordination and the documentation nobody enjoys writing. This is governance and delivery management that lets technical work land inside a program, not just in a sandbox.

Typical engagements

BI governance framework design
Scoping, estimation and delivery management to timeline
Risk and issue management on behalf of program leadership
Stakeholder engagement from CIO to end user
Vendor and cross-team coordination (functional, BASIS, SAP support)
Mentoring and team leadership
Technical and functional documentation, WRICEFX specs, support handover

Coordinates with

Functional teams (FI/CO, MM, PP, SD) · BASIS · SAP support

Not sure which of these fits your estate? That's what the discovery call is for.

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