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SAP

Engineering Enterprise SAP Data Foundations.

Unolabs modernises SAP BW estates into governed enterprise data foundations. With mainstream maintenance for SAP BW 7.5 ending in December 2027, we engineer the pragmatic path forward — BW/4HANA conversion, SAP Datasphere migration, and SAP-to-cloud architectures that unify operational visibility and preserve the reporting logic your business depends on.

ARCHITECTURE FLOWSAP INTELLIGENCE
SAP DATA ESTATE

SAP SOURCES

Operational extraction + semantic modelling

INTELLIGENCE ARCHITECTURE

BW LANDSCAPE AUDIT

Governed modernisation + target-state alignment

INTELLIGENCE OUTCOME

ENTERPRISE INTELLIGENCE

Operational visibility + unified decision systems

Expertise in Enterprise Ecosystems
Azure
AWS
Databricks
Snowflake
SAP
MS Fabric
SAP BW/4HANA · SAP Datasphere
Snowflake · Databricks · Azure
Modernisation Readiness Audit
Definition

What is SAP BW Modernisation & Datasphere Migration?

SAP BW modernisation is the structured migration of legacy SAP Business Warehouse estates to current platforms — BW/4HANA, SAP Datasphere, or hybrid SAP-plus-cloud architectures. It matters now because mainstream maintenance for SAP BW 7.5 ends in December 2027, and the work spans object rationalisation, semantic redesign, and re-platforming of the reporting logic the business depends on.

For the CIO

A priced, dated position on BW before 2027

Mainstream maintenance for BW 7.5 ends in December 2027, BW skills are getting scarcer, and the estate is not shrinking while you wait. This engagement turns the deadline into a decision: an object and usage audit, a rationalised migration scope, and a sequenced path to BW/4HANA, Datasphere, or hybrid — weighed against staying on extended maintenance. Deferral stays on the table, but as a costed choice rather than a default.

Data Foundation Failure

Why enterprise SAP BW initiatives fail

Fragmented Reporting Ecosystems

Disconnected reporting systems across business units that produce conflicting versions of the truth and prevent coordinated decision-making.

Disconnected SAP and Non-SAP Systems

Siloed SAP environments that cannot easily integrate with cloud platforms, preventing cross-domain analytics and AI-native activation.

Excessive Warehouse Complexity

Decades of custom extractors, transformations, and layers that make the warehouse brittle, slow, and prohibitively expensive to maintain.

Inconsistent Semantic Layers

Business definitions for KPIs like revenue, margin, and inventory that vary between reports, destroying executive trust in data.

Poor Master Data Governance

Inconsistent master data that propagates through the warehouse, leading to manual reconciliation and unreliable operational reporting.

Legacy BW Performance Bottlenecks

Outdated architecture that cannot handle modern data volumes or real-time query demands, frustrating business users and delaying decisions.

Strategic Impact

Business Outcomes Enabled by SAP BW Modernisation

Faster Enterprise Analytics Delivery

Compress the time from operational signal to executive insight by eliminating legacy extraction bottlenecks and optimising warehouse performance.

Improved Operational Visibility

Establish a transparent, real-time view of finance, supply chain, and procurement operations through unified SAP intelligence architecture.

Reduced Reporting Fragmentation

Consolidate disconnected reporting silos into a governed, single source of truth that ensures consistency across every business unit.

Real-Time Intelligence Access

Enable sub-second access to critical enterprise data by modernising legacy BW landscapes into high-performance HANA-optimised ecosystems.

Improved Enterprise Data Governance

Implement governed semantic layers and master data stewardship models that ensure every report is backed by certified, trusted data.

Reduced Warehouse Complexity

Simplify the data estate by retiring redundant InfoProviders, extractors, and custom logic in favour of lean, modern architecture.

Data Architecture Design

How SAP BW Modernisation & Datasphere Migration delivery works

The view below shows how work moves through the delivery flow — from inputs, through governed controls, to operational outputs.

Engineering Flowchart

SAP Warehouse Modernisation Flow

Read left to right: source systems enter, Unolabs applies engineering treatment and control gates, then production assets are served to users, applications, or AI.
Input

Source Layer

01
SAP Sources

ECC, S/4HANA, and legacy BW objects are analysed and extracted via ODP and CDS connectors.

ODP + CDS
Treatment

Engineering Layer

02
Intelligence Core

Legacy objects are transformed into HANA-optimised structures, BW/4HANA models, or Datasphere products.

BW/4HANA + SQL
03
Semantic Layer

KPI definitions, hierarchies, and security policies are applied to ensure a single version of truth.

Semantic Model
Output

Activation Layer

04
Enterprise Intelligence

Certified data products are exposed to SAC, Power BI, and operational cockpits for decision-making.

BI + Cockpits
What enters

SAP Sources

What Unolabs does

Intelligence Core -> Semantic Layer

What exits

Enterprise Intelligence

Control Points

Extract -> Modernise -> Govern -> Activate

Access

Identity, RBAC, purpose, and least privilege.

Quality

Freshness, completeness, validity, and anomaly checks.

Lineage

Source, transformation, owner, and consumer traceability.

Operations

Monitoring, retry, alerting, runbooks, and evidence.

Our Approach

How Unolabs engineers SAP BW Modernisation & Datasphere Migration

01

BW Landscape Audit

We review objects, extractors, transformations, query usage, performance, dependencies, and retirement candidates to define a lean modernisation roadmap.

02

Target Architecture Design

We design the target intelligence foundation—deciding what stays in SAP, what moves to cloud, and how semantic definitions stay consistent.

03

Dimensional Modelling

We engineer high-performance models for finance, sales, procurement, and operations with clear granularity and certified measures.

04

Performance Engineering

We optimise queries, HANA views, partitions, and workload placement to deliver the sub-second response times executives demand.

05

SAP Datasphere Integration

We extend SAP data into cloud-native analytics ecosystems, enabling cross-system intelligence without duplicating data.

06

Semantic Layer Governance

We establish governed KPI taxonomies and data stewardship models that eliminate conflicting reporting across the enterprise.

Strategic Assessment

Enterprise Data Warehouse Maturity Model

Where does your organisation sit on the path to autonomous operations? Use this model to identify your current stage and the critical engineering gaps preventing progression.

Level 1

Fragmented Reporting

Isolated, manual reporting from disconnected SAP systems with no unified warehouse strategy or governed KPI definitions.

Level 2

Standardised Reporting

Core enterprise reports standardised on legacy BW, but lacking real-time visibility or cross-system integration.

Level 3

Governed SAP Warehouse

Modernised BW/4HANA or Datasphere architecture with governed semantic layers and structured data foundations.

Level 4

Real-Time Enterprise Intelligence

Live SAP data integrated with cloud lakehouses, powering operational cockpits and real-time executive decision-making.

Level 5

Autonomous Data Foundations

Self-optimising intelligence ecosystems where SAP data feeds agentic workflows and predictive operational models automatically.

Industry Benchmarking

Query Response Time
Typical Pattern
Minutes
Our Design Target
Sub-Second
Reporting Fragmentation
Typical Pattern
High / Siloed
Our Design Target
Unified / Governed
Modernisation Speed
Typical Pattern
12–18 Months
Our Design Target
12–16 Weeks (First Subject Area)

Transformation Progression

1

Modernisation Audit

Assessment of current BW landscape, object inventory, extraction debt, and performance bottlenecks.

2

Architecture Design

Designing the target-state SAP intelligence architecture, semantic layer, and cloud integration strategy.

3

Warehouse Modernisation

Migrating to BW/4HANA, Datasphere, or hybrid cloud architectures with optimised dimensional models.

4

Intelligence Activation

Enabling real-time reporting, operational cockpits, and governed self-service for business users.

5

Continuous Optimisation

Ongoing tuning of performance, governance, and data products to sustain enterprise intelligence excellence.

Vertical Expertise

Warehouse Modernisation Patterns

Finance & Controlling

Universal Journal integration, real-time financial close intelligence, and governed margin analysis.

Supply Chain & Logistics

Real-time inventory visibility, demand sensing integration, and supply chain observability ecosystems.

Sales & Distribution

Unified customer intelligence, order-to-cash visibility, and cross-channel sales analytics.

Manufacturing Operations

Production performance monitoring, OEE intelligence, and quality management observability.

Procurement & Spend

Spend analytics standardisation, vendor performance intelligence, and procurement risk visibility.

Hybrid Cloud Integration

Extending SAP BW into Snowflake, Databricks, and Azure for cross-system enterprise intelligence.

In Depth

What this means in practice

Not Everything Should Move

We classify workloads so SAP-native strengths remain while cloud platforms handle massive scale, AI-native workloads, and cross-system analytics.

Semantic Integrity is Priority

Revenue, margin, and spend measures are documented and governed before any reports are rebuilt, ensuring modernisation drives trust, not confusion.

Performance is Designed, Not Added

Query speed comes from structural model design, partitioning strategy, and workload placement—not just adding HANA compute power.

Dynamic Data Flow

SAP Warehouse Modernisation Flow

The warehouse modernisation flow shows how legacy SAP operational data is assessed, transformed, and activated into governed enterprise intelligence ecosystems.

SAP BW Modernisation & Datasphere MigrationData Flow Architecture
1
Extract

SAP Sources

ECC, S/4HANA, and legacy BW objects are analysed and extracted via ODP and CDS connectors.

ODP + CDS
2
Modernise

Intelligence Core

Legacy objects are transformed into HANA-optimised structures, BW/4HANA models, or Datasphere products.

BW/4HANA + SQL
3
Govern

Semantic Layer

KPI definitions, hierarchies, and security policies are applied to ensure a single version of truth.

Semantic Model
4
Activate

Enterprise Intelligence

Certified data products are exposed to SAC, Power BI, and operational cockpits for decision-making.

BI + Cockpits
Lineage tracked
Policy enforced
Outputs reusable
Migration Treatment Diagram

How legacy data is assessed, cleansed, moved, validated, and cut over

Migration pages now show the complete treatment path instead of only describing the migration. The view below makes each control point visible.

Assess
01

Profile legacy data

Schema, volume, custom fields, missing keys, duplicates, data quality, dependencies, and business criticality are scored before movement.

Cleanse
02

Treat source defects

Duplicates, invalid values, orphan records, obsolete history, and inconsistent master data are corrected or routed for stewardship.

Map
03

Convert to target model

Source fields are mapped to S/4HANA, cloud, warehouse, or lakehouse targets with transformations and control rules.

Move
04

Run migration waves

Extraction, transformation, loading, retries, and exception handling run through repeatable factory pipelines.

Reconcile
05

Prove source-target parity

Counts, totals, hashes, reports, financial values, and operational outputs are compared before signoff.

Cutover
06

Switch with evidence

Readiness gates, rollback rules, business approvals, and hypercare dashboards guide the final production move.

Migration evidence package

Every wave produces validation logs, reconciliation output, exception reports, owner signoff, rollback checkpoints, and cutover evidence for SAP BW Modernisation & Datasphere Migration.

Flowchart

SAP BW Modernisation & Datasphere Migration: from input to operational asset

The flowchart turns the service into a delivery sequence so buyers can see the real work, not just the promise.

1

Business Input

Faster Enterprise Analytics Delivery

2

Architecture Decision

BW Landscape Audit

3

Data Treatment

Intelligence Core

4

Controls Applied

Semantic Layer

5

Operational Output

Enterprise Intelligence

Deliverables

Visible work products, not vague advice

Each deliverable is designed to be used by executives, architects, engineers, data owners, and operations teams after the engagement ends.

SAP BW modernisation architecture
Enterprise warehouse transformation roadmap
SAP BW/4HANA modernisation framework
Enterprise semantic data models
Governed reporting architecture
SAP Datasphere integration strategy
Operational intelligence frameworks
Enterprise observability systems
Roadmap

The delivery path

1

Understand Context

Inventory systems, stakeholders, technical debt, and business constraints to define the modernisation baseline.

2

Align Goals

Connect board-level transformation goals to measurable data intelligence outcomes and operational requirements.

3

Build Architecture

Design and implement the resilient data and platform foundations required to operate intelligence at enterprise scale.

4

Operationalise AI

Deploy production-grade agentic loops and intelligent workflows into core mission-critical business processes.

5

Optimise Outcomes

Continuously measure value and refine intelligence systems through operational feedback and architectural hardening.

Outcomes

What changes after the work

Faster enterprise analytics delivery

Improved operational visibility

Reduced reporting fragmentation

Real-time intelligence access

Improved enterprise data governance

Reduced warehouse complexity

Accelerated analytics modernisation

Scalable enterprise intelligence architecture

FAQ

Frequently Asked Questions

When does SAP BW support end?

Mainstream maintenance for SAP BW 7.5 ends on December 31, 2027, with extended maintenance available through 2030 at a premium. Systems keep running after those dates, but without fixes, security patches, or legal-change support — a posture most audit and security functions will not accept for statutory reporting systems.

Is SAP Datasphere a direct replacement for SAP BW?

No. Datasphere — now part of SAP Business Data Cloud, SAP's strategic data platform direction — is SAP's cloud data-warehousing and business-data-fabric service, but it is architecturally different from BW: modelling, authorisations, and front-end integration all work differently. SAP BW Bridge can carry BW data models and ABAP staging logic across as a transition path; queries and the authorisation concept must be redesigned for the target.

How long does a BW-to-Datasphere migration take?

It depends on rationalised scope, not raw system size. A small, well-used estate can move in a few quarters; large mixed estates typically run staged programmes across one to two years, sequenced around source-system changes such as an S/4HANA conversion. A credible estimate requires an object inventory and usage audit first.

Can we stay on SAP BW until 2030?

Yes — under extended maintenance, at premium cost. That is a legitimate sequencing move if an S/4HANA conversion needs to stabilise source systems first. But it defers the migration rather than avoiding it, while the scope and the scarcity of BW skills keep growing. Deferral should be a priced, dated decision, not a default.

Engagement Mechanics

How an engagement starts

A 45-minute scoping call with an SAP data architect — bring your BW inventory, however rough; leave with a defensible read on your 2027 position and a proposed audit scope.

What you bring
A BW platform owner and 1-2 key report consumers for interviews
System access for object inventory and usage analysis
Sight of your S/4HANA timeline so sequencing is realistic

Bring your BW inventory. Leave with a defensible 2027 position.