Enterprise Data Silos
Business information remains distributed across SAP, non-SAP, cloud, and operational systems.
Part of the Concinnity Enterprise Intelligence PlatformSAP Enterprise Data & Analytics › SAP Datasphere
SAP Enterprise Data & Analytics
SAP Datasphere Consulting
Connect Enterprise Data Without Losing Business Context
Concinnity helps organizations connect SAP and non-SAP information, preserve business semantics, modernize SAP BW investments, and establish governed data products for analytics, planning, and AI.
SAP Applications
Non-SAP Systems
Cloud Data
SAP BW
Operational Data
External Data
↓
SAP Datasphere
Integration • Federation • Semantics • Governance • Data Products
↓
SAP Business Data Cloud
Analytics • Planning • AI • Intelligent Applications
↓
Trusted Enterprise Intelligence • Better Decisions
Concinnity Point of View
Trusted enterprise intelligence begins with trusted business meaning. Organizations create more value when integration, semantics, governance, and data products are designed together—not when data is copied into another disconnected repository.
At a glance
A business-context foundation for hybrid enterprise data
Best forOrganizations integrating SAP and non-SAP enterprise data
Business focusIntegration, semantics, governance, and reusable data products
StakeholdersCIO, CDO, Enterprise Architect, Data and Analytics Leaders
Technology landscapeSAP-centered and hybrid cloud environments
Typical outcomesTrusted data, simpler architecture, faster analytics, AI readiness
Consulting focusStrategy, architecture, BW modernization, implementation, adoption
Executive questions we help answer
Define the right role for SAP Datasphere in your enterprise architecture
01
Where should SAP Datasphere fit within our enterprise data architecture?
02
How should we modernize SAP BW while protecting critical business logic?
03
How can we connect SAP and non-SAP data without unnecessary duplication?
04
How do we preserve business definitions and semantics across platforms?
05
Which information domains should become governed data products?
06
How does SAP Datasphere complement SAP Business Data Cloud?
07
How can we improve governance, lineage, ownership, and metadata?
08
How do we prepare enterprise data for analytics, planning, and AI?
Business challenges
Common barriers to a trusted enterprise data foundation
Duplicate Data Pipelines
Multiple extraction and transformation processes increase cost, latency, and maintenance.
Legacy SAP BW Complexity
Accumulated objects, custom logic, and dependencies make modernization difficult.
Inconsistent Business Semantics
Different measures, hierarchies, and definitions create conflicting versions of truth.
Weak Data Governance
Ownership, quality, access, lineage, and stewardship are not consistently managed.
Limited Metadata Visibility
Teams struggle to understand available data, its meaning, and how it should be used.
Hybrid Integration Complexity
SAP and cloud data platforms need clear coexistence and integration patterns.
AI Readiness Gaps
AI initiatives lack trusted, contextual, governed, and reusable enterprise data.
Solution overview
What SAP Datasphere means for business and technology leaders
SAP Datasphere provides capabilities for integrating, cataloging, modeling, federating, virtualizing, and governing enterprise data while preserving business context. It plays a central role in SAP Business Data Cloud for connecting SAP and non-SAP data and developing custom data models and data products.
Concinnity helps clients translate those capabilities into a practical enterprise data architecture with clear business domains, reusable semantic models, governed data products, BW modernization pathways, and trusted consumption for analytics, planning, and AI.
Connect Distributed DataIntegrate or federate SAP and non-SAP information through governed patterns.
Preserve Business SemanticsRetain measures, hierarchies, relationships, and business meaning.
Deliver Reusable Data ProductsCreate owned, documented, quality-controlled information assets.
Enable Trusted ConsumptionSupport analytics, planning, applications, and AI from one contextual foundation.
Technology positioning
Where SAP Datasphere delivers the greatest value
CapabilityRole in the SolutionStrategic Value
Enterprise Data IntegrationCore
Connect SAP and non-SAP information through replication, federation, and transformation patterns.
Business SemanticsCore
Preserve business definitions, measures, relationships, and analytical context.
Governed Data ProductsCore
Package trusted data for reuse across domains, analytics, planning, and AI.
SAP BW ModernizationStrong Fit
Support phased modernization, coexistence, and preservation of valuable BW logic.
Analytics FoundationStrong Fit
Provide contextual data models for SAP Analytics Cloud and other consumption tools.
Planning EnablementSupports
Deliver governed dimensions, measures, and actuals for connected planning processes.
AI ReadinessEnables
Provide quality, semantics, lineage, and business context for enterprise AI initiatives.
Platform relationship
How SAP Datasphere and SAP Business Data Cloud work together
SAP Datasphere provides central integration, modeling, semantic, and data-management capabilities within the broader SAP Business Data Cloud offering.
Enterprise Data LandscapeSAP Applications • Non-SAP Systems • Cloud Platforms • External Data
↓
SAP DatasphereIntegration • Federation • Semantic Modeling • Governance • Custom Data Products
↓
SAP Business Data CloudManaged Data Products • Analytics • Planning • AI • Intelligent Applications
↓
Enterprise Intelligence & Business PerformanceTrusted KPIs • Scenarios • Predictions • Decisions • Value
Why this matters
Organizations can use SAP Datasphere to develop and govern the contextual enterprise data foundation that SAP Business Data Cloud, analytics, planning, and AI require.
Enterprise Architecture Blueprint
A connected architecture for SAP and hybrid enterprise data
Enterprise Source Systems
SAP S/4HANASAP SuccessFactorsSAP AribaSAP IBPSAP CXSAP BWCRM & ERPOperational & External Data
↓
SAP Datasphere
Data IntegrationFederationSemantic ModelsData CatalogGovernanceData ProductsVirtualization
↓
SAP Business Data Cloud & Enterprise Intelligence
Managed Data ProductsSAP Analytics CloudEnterprise PlanningExecutive DashboardsMachine LearningGenerative AI
↓
Business Outcomes
Trusted DataFaster AnalyticsBetter PlanningLower ComplexityAI ReadinessImproved Decisions
SAP BW modernization
Modernize at the right pace while protecting business continuity
SAP BW environments often contain years of valuable business logic, reporting content, and institutional knowledge. Concinnity helps organizations assess what to retain, redesign, migrate, coexist with, or retire.
Discuss Your BW Landscape01AssessInventory objects, workloads, dependencies, usage, and business criticality.
02SegmentClassify assets for retain, migrate, redesign, replace, coexist, or retire.
03PrioritizeSequence modernization around business value, risk, and technical readiness.
04ModernizeMove selected models and logic into governed cloud data products and semantic models.
05TransitionValidate continuity, adoption, controls, performance, and decommissioning.
Migration readiness checklist
Is your organization ready for a SAP Datasphere initiative?
✓
We maintain multiple reporting repositories or duplicated enterprise data models.
✓
Our SAP BW environment is becoming costly or difficult to evolve.
✓
Business definitions and KPIs differ across departments or platforms.
✓
Teams spend significant time reconciling data before analysis.
✓
We need clearer ownership, lineage, quality, access, and metadata.
✓
We operate a hybrid SAP, Microsoft, Databricks, Snowflake, or cloud landscape.
✓
We plan to expand enterprise planning, analytics, or AI use cases.
✓
We need a governed data-product strategy aligned to business domains.
Several items apply?
A structured Datasphere and BW modernization assessment can clarify target architecture, priority domains, migration sequencing, risk, and expected business value.
Concinnity delivery approach
A practical six-phase roadmap from strategy to adoption
01
Discover
Clarify priorities, use cases, stakeholders, and expected business outcomes.
Output: vision and value hypothesis02
Assess
Evaluate BW, source systems, integrations, models, governance, and maturity.
Output: current-state assessment03
Architect
Design target architecture, domains, data products, semantics, and migration path.
Output: roadmap and architecture04
Build
Implement integrations, spaces, models, governance, data products, and consumption.
Output: production capabilities05
Enable
Operationalize ownership, stewardship, adoption, training, and support processes.
Output: sustainable operating model06
Optimize
Improve performance, expand domains, measure value, and prepare for AI.
Output: continuous improvementCore capabilities
Build trusted enterprise data without sacrificing business meaning
Enterprise Data Integration
Connect SAP and non-SAP sources through appropriate replication, transformation, and access patterns.
Semantic Modeling
Preserve business definitions, measures, hierarchies, associations, and analytical context.
Data Federation
Access distributed data where appropriate while reducing unnecessary movement and duplication.
Data Virtualization
Create flexible consumption models across distributed enterprise information.
Governance & Catalog
Improve discovery, ownership, lineage, metadata, quality, and controlled access.
Governed Data Products
Deliver reusable domain-oriented data assets with clear contracts and accountability.
SAP BW Modernization
Support assessment, coexistence, phased migration, redesign, and investment protection.
Hybrid Connectivity
Establish practical integration patterns across SAP, Microsoft, Databricks, Snowflake, and cloud platforms.
Business value
Measure the impact across growth, efficiency, risk, and intelligence
Growth
Accelerate New Use Cases
Deliver trusted data faster for analytics, planning, products, and AI innovation.
Efficiency
Simplify Data Delivery
Reduce duplicate pipelines, manual reconciliation, and repeated semantic modeling.
Risk
Improve Governance
Strengthen ownership, quality, lineage, access, standards, and business continuity.
Intelligence
Increase Trust
Provide consistent business context for KPIs, dashboards, forecasts, and AI models.
Technology ecosystem
Designed for SAP-centered and hybrid data landscapes
SAP Applications
SAP S/4HANASAP SuccessFactorsSAP AribaSAP IBPSAP CXSAP Data & Analytics
SAP DatasphereSAP Business Data CloudSAP Analytics CloudSAP BW/4HANASAP HANA CloudCloud Data Platforms
Microsoft FabricDatabricksSnowflakeAzureAWSConsumption & AI
Power BIEnterprise PlanningMachine LearningGenerative AIOperational ApplicationsIllustrative engagement
Modernizing enterprise data while preserving SAP business logic
Global SAP Enterprise
Creating a governed SAP Datasphere foundation across SAP BW and hybrid cloud data
Challenge
Enterprise reporting depended on multiple BW environments, duplicated integrations, inconsistent semantics, and significant manual reconciliation.
Approach
Assessed the BW estate, defined priority domains and data products, designed coexistence patterns, and implemented contextual models for analytics and planning.
Business Impact
Improved trust, faster data delivery, reduced duplication, clearer governance, protected BW investments, and a scalable foundation for Business Data Cloud and AI.
Industry applications
Apply trusted enterprise data across your operating environment
Related frameworks
Connect SAP Datasphere to a broader enterprise methodology
Recommended next reading
Continue exploring the Concinnity Solutions Platform
Hybrid platform option
Explore Microsoft Fabric for SAP and enterprise analytics
Business solution
Connect this platform to Enterprise Intelligence
SAP Datasphere Assessment
Ready to build a trusted enterprise data foundation?
Concinnity can help assess your SAP BW and enterprise data landscape, define the role of SAP Datasphere, and create a practical modernization roadmap.
Schedule a Datasphere Assessment