Connect SAP analytics planning to S/4HANA implementation evidence
Use the S/4HANA on AWS article to review how SAP data, HANA sizing, reporting dependencies and post-go-live optimisation shape analytics outcomes.
Read the S/4HANA article
_____our services…
We will focus on cost efficiency, resilience, and future scalability across the following:
We don’t just build dashboards. We design decision systems that bring together planning, reporting, AI, and predictive insight — whether you’re working inside SAP or extending beyond it. Our approach empowers businesses to move faster, reduce cost, and get more value from their SAP data than ever before.
Reporting, dashboarding, planning, predictive — all in one model
Use Databricks as a cloud-native replacement for HANA/BW, enabling large-scale
Extract data directly from SAP tables, bypassing BW and eliminating licensing overhead
Combine SAP-native tools with cloud-scale platforms like Snowflake, Power BI, or Data360
Designed to evolve with user needs, business priorities, and data growth
Pay too much for BW licenses? Struggling with your SAP reporting? There are lots of options available to you. Including bypassing BW itself and extracting the data directly from SAP base tables
High-level vision, sequencing, and alignment of SAP analytics tools (SAC, BTP, Datasphere, BW/4) to business objectives, use cases, and platform direction.
Configuration and rollout of SAP Analytics Cloud (SAC) dashboards and models, including security, connectivity, and training.
Strategy and design advisory across SAP’s analytics platforms — supporting migrations, architecture decisions, and use case mapping.
Enablement of modern reporting by bypassing legacy BW models, pulling directly from SAP ECC/S/4HANA tables to reduce licensing and latency.
Build of pipelines and models to connect SAP data with Databricks, enabling advanced analytics, ML workloads, and non-SAP visualisation layers.
Continuous improvement of existing SAP analytics tools (SAC/BO) — including performance tuning, UX refinement, and feature extension.
Ongoing design validation, data source extension, functional improvements, and insight refinement to ensure SAP analytics tools remain relevant and impactful over time.
SAP analytics planning should connect data sources, BW or HANA dependencies, reporting users, integration patterns, security, refresh cycles and cloud platform choices. The aim is to protect business reporting while creating room for better analytics.
Check BW, HANA, reporting tools, data extraction patterns, custom reports, security roles, refresh windows, performance issues, downstream consumers and the business decisions that depend on each dataset.
SAP analytics often depends on the same systems being migrated or modernised. If reporting dependencies are missed, cutover and post-migration validation become harder and business teams may lose confidence in the new platform.
Cloudwrxs starts with business reporting needs and technical dependencies, then aligns SAP analytics, cloud data services, integration and operational controls to create a practical delivery route.