Service: SAP

SAP analytics services

Your SAP system holds the most trusted numbers in the business, yet month end still runs on spreadsheet exports. We build the semantic models, dashboards and planning that make SAP data usable, in SAP Analytics Cloud, Datasphere and BW/4HANA or in the lakehouse and BI tools you already use, with business meaning kept intact on the way out.

Discuss SAP analytics Data analytics and dashboards

Key highlights

We deliver S/4HANA embedded analytics, SAP Analytics Cloud, SAP Datasphere, SAP Business Data Cloud and BW/4HANA work, and feeds into Snowflake, Databricks and Power BI.
Operational reporting usually belongs in S/4HANA embedded analytics on CDS views; cross system and historical analysis belongs in a warehouse.
SAP Business Data Cloud brings together SAP Datasphere, SAP Analytics Cloud and SAP BW, with SAP Databricks as a component.
We keep SAP business semantics, such as currencies, units, hierarchies and fiscal calendars, intact when data leaves SAP.
AI agents draft CDS views, data models, transformation code and data tests; senior engineers review every model.

SAP reporting problems we solve

The data in SAP is usually right. The problem is getting it to the people who need it, in a form they trust, without exporting it by hand.

Month end close on spreadsheets. Controllers export line items, rebuild hierarchies in Excel and reconcile by hand because the reports they need were never built.

Numbers that differ by system. Revenue in the BI tool does not match revenue in SAP because currency conversion, fiscal periods or cost centre hierarchies were rebuilt differently outside SAP.

A BW system nobody wants to touch. Years of BW queries and process chains, many unused, some critical, and a decision about BW/4HANA, Datasphere or Business Data Cloud waiting to be made.

SAP data cut off from the lakehouse. The data team works in Snowflake or Databricks, but SAP tables arrive late, without business context, or through extraction methods nobody has checked against SAP's terms.

Planning in disconnected files. Budgets and forecasts live in spreadsheets emailed between departments, then are keyed back into SAP or never compared with actuals at all.

Dashboards nobody opens. Reports built from a requirements list rather than the decisions people make each week, so usage drops after the launch email.

Scope

What our SAP analytics service covers

The right layer for each question: embedded for operational, warehouse for cross system, lakehouse when the wider data team needs it.

S/4HANA embedded analytics

Custom CDS views and analytical queries on top of SAP standard views, exposed in SAP Fiori analytical apps and to SAP Analytics Cloud for real time operational reporting.

SAP Analytics Cloud

Dashboards and stories for finance, sales and operations, plus planning models for budgets and forecasts that compare plan against SAP actuals in one place.

SAP Datasphere and Business Data Cloud

Data models that combine SAP and non SAP sources with business semantics preserved, built in SAP Datasphere and within SAP Business Data Cloud where you have adopted it.

SAP BW/4HANA

New models, query and process chain fixes, performance tuning and clean up of unused objects in BW/4HANA, and a documented path for BW customers considering Datasphere or Business Data Cloud.

Snowflake, Databricks and Power BI

SAP data delivered to Snowflake, Databricks or Power BI through extraction methods SAP supports for your licence, with currencies, units and hierarchies modelled correctly and reconciled to SAP.

AI on SAP data

Natural language questions over governed SAP models, anomaly detection on financial and supply chain data, and forecasting, built only on data that has already been reconciled.

How we deliver

From the first trusted report to a full data platform

01
Decision and data audit
We map the decisions each role makes, the reports they use today and the SAP sources behind them. Output: target architecture, tool choice and a prioritised list of reports.
02
Model the core
CDS views or Datasphere models for the first subject area, usually finance or sales, reconciled line by line against SAP before anyone sees a dashboard.
03
Build and adopt
Dashboards and planning models built with the people who will use them, released in short cycles with usage tracked after launch.
04
Scale
Further subject areas, non SAP sources, lakehouse feeds and AI use cases on top of models the business already trusts.

Governance for SAP data

Analytics copies SAP data into more places. Access rules, licensing terms and personal data have to travel with it.

SAP authorisation inheritance Row level security Data lineage Reconciliation to SAP SAP licensing terms for data extraction GDPR and UK GDPR SOX reporting support

Users see only what SAP lets them see. Where reports run on SAP models, SAP authorisations apply directly. Where data leaves SAP, we rebuild company code, cost centre and sales organisation restrictions as row level security and test them.

Extraction methods are checked against your licence. SAP sets rules on how its data may be extracted by third party tools. We use methods SAP supports for your licence and edition and flag any approach you should confirm with SAP.

Every number reconciles. Financial models are reconciled to SAP balances at each load, with automated data tests that stop a broken load before it reaches a dashboard.

SAP analytics stack

SAP analytics products where they fit, and the open data stack where your data team already works.

CDS views and ABAP CDS SAP Fiori analytical apps SAP Analytics Cloud SAP Datasphere SAP Business Data Cloud SAP BW/4HANA SAP HANA Snowflake Databricks Power BI dbt Python

FAQ

Common questions

Should we use SAP Analytics Cloud or Power BI?

Use SAP Analytics Cloud when most data is SAP and you want planning and live connections to S/4HANA; use Power BI when it is already your company standard and SAP is one of many sources. Many companies run both. We recommend based on your users, data and licences.

What should BW customers do now?

Keep running BW/4HANA where it works, and plan new modelling with SAP's direction in mind. SAP positions SAP Datasphere and SAP Business Data Cloud as its strategic data offering, so we document which BW models to keep, move or retire, and in what order.

How much does an SAP analytics project cost?

It depends on the number of subject areas, source systems and reports, so we estimate rather than publish a price. A discovery call leads to a written scope, timeline and estimate within 48 hours. Engagement models are on the pricing page.

How long does it take to get the first reports live?

Typically 6 to 10 weeks for a first subject area such as finance or sales, including modelling, reconciliation and dashboards. Larger platforms are delivered in phases after that.

Who owns the SAP licences?

You do. SAP Analytics Cloud, Datasphere, Business Data Cloud and BW/4HANA are licensed directly from SAP. RG INSYS is not an SAP partner or reseller and charges only for the work.

Where is the team and how is AI used safely?

The team is in India with at least 4 hours of overlap with your working day. AI agents draft models, transformations and tests on metadata and sample or synthetic data; a senior engineer reviews every change, and production business data is not sent to external AI services.

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