Big Data Analytics
Bring SAP and non-SAP data together for faster, more reliable reporting, forecasting and planning. We build analytics on SAP HANA, SAP S/4HANA embedded analytics and modern data platforms.
Getting value from the data you already have
Companies running SAP produce large amounts of data in finance, supply chain, sales and customer systems. Much of it goes unused, because it sits in separate systems and reports run overnight in batches.
We build analytics platforms that combine SAP S/4HANA with your other data, so people get current, consistent figures and can start forecasting rather than only looking back.
Common problems
- Data spread across SAP and older systems
- Reports that are a day old because of batch ETL jobs
- Business users who cannot see KPIs when they need them
- Master data that differs between departments
- Forecasting tools that nobody uses
The result is slower decisions and missed chances to improve.
What we build
We design analytics around your business processes, not around isolated dashboards. That means:
- Shared data models for SAP and non-SAP data, with governed pipelines
- Real-time processing on SAP S/4HANA and SAP HANA
- Forecasting models for finance and supply chain
- Reports that refresh in minutes instead of overnight
- Clear data ownership and governance so numbers can be trusted
Examples
- Finance: margin and profitability tracking on SAP HANA models
- Supply chain: demand forecasts using history plus external data
- Procurement: supplier risk scoring and spend analysis
- Sales: revenue forecasting with machine learning
- Operations: finding process bottlenecks from event data
Moving beyond batch reporting
Many SAP customers still rely on overnight BI reports. The newer approach combines:
- Event-driven pipelines, so data updates as transactions happen
- A lakehouse that holds SAP data next to external and AI data sets, for example on Microsoft Fabric
- In-memory analytics on SAP HANA for fast queries
- Embedded analytics in SAP S/4HANA, so figures appear inside the transaction
Together these give faster decisions, better forecasts and less waiting on IT for reports. Good data governance also improves data quality, which makes every forecast more reliable.
How reporting data flows
- 1SourcesSAP S/4HANA, CRM, files and external data.
- 2IntegrateGoverned pipelines into one data model.
- 3ModelShared definitions, so every team gets the same numbers.
- 4ReportDashboards and embedded analytics for business users.
- 5ForecastPredictive models once the foundation is trusted.
Why ITRadiant for analytics
We know SAP data from the inside, which saves a lot of time when building reliable reports.
- SAP data models: we know the tables, CDS views and business logic behind the numbers
- One version of the truth: we fix master data and definitions so departments report the same figures
- Built for business users: reports and dashboards that people can use without asking IT
- From reporting to forecasting: a clear path to predictive models once the data foundation is solid
Frequently asked questions
What is big data analytics?
Analyzing large and varied data sets to find patterns and trends that help people make better decisions.
How does analytics work with SAP systems?
Data from SAP S/4HANA is modeled and combined with other sources, then shown in reports, dashboards or embedded analytics. SAP HANA allows fast queries on current data.
What does predictive analytics add?
It uses statistical and machine learning models on historical and current data to forecast demand, revenue or risk, so you can act earlier.
Why does real-time data matter?
It lets people react to problems and changes as they happen, instead of finding out from the next day’s report.
How does a data platform improve performance?
It brings data together in one governed place, so reports are consistent, faster to build and easier to trust.
Waiting too long for reliable reports?
Tell us which numbers your teams struggle to get. We will suggest how to bring the data together and what it would take.
