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SAP

Engineering Enterprise Operational Intelligence Ecosystems.

Unolabs engineers enterprise operational intelligence ecosystems for modern executive decision-making. We move beyond generic reporting to build governed, scalable, and resilient intelligence layers across SAP BusinessObjects, Analytics Cloud, and Datasphere that accelerate operational responsiveness.

ARCHITECTURE FLOWOPERATIONAL INTELLIGENCE
INTELLIGENCE ESTATE

BOBJ, BW, SAC, EXCEL

Reporting fragmentation + operational analytics sprawl

INTELLIGENCE ARCHITECTURE

EXECUTIVE INTELLIGENCE DESIGN

Governed metrics + semantic consistency

DECISION OUTCOME

EXECUTIVE DECISIONING

Operational visibility + decision acceleration

Expertise in Enterprise Ecosystems
Azure
AWS
Databricks
Snowflake
SAP
MS Fabric
10-14 week BI modernization sprint
80% manual report reduction target
Certified SAP intelligence layer
Operational Intelligence Failure

Why enterprise operational intelligence initiatives fail

Fragmented Reporting Estates

Disconnected analytics tools and siloed reporting efforts that prevent a unified view of enterprise performance.

Inconsistent KPI Governance

Conflicting metric definitions and weak data ownership leading to low executive trust in reporting.

Disconnected Ecosystems

Silos between SAP and non-SAP data that prevent cross-functional visibility and operational intelligence.

Manual Reporting Friction

Reliance on manual exports, emails, and reconciliations that stall decision speed and increase risk.

Strategic Impact

Business Outcomes Enabled by Operational Intelligence

Accelerated Decision Speed

Establish the real-time visibility and governed data foundations required to compress decision cycles from weeks to minutes.

Improved Operational Resilience

Replace manual, brittle reporting with automated, resilient intelligence ecosystems that maintain performance under enterprise pressure.

Unified Enterprise Visibility

Break down silos between SAP and non-SAP domains to provide a single, trusted version of truth for global executive stakeholders.

Reduced Governance Risk

Enforce consistent metric definitions and access controls across the entire estate, eliminating the risk of conflicting or uncertified data.

Data Architecture Design

How the systems, controls, and outputs talk to each other

Each service page includes a visible architecture view. It shows where data enters, how Unolabs treats it, which controls are applied, and where the final asset is consumed.

Engineering Flowchart

Operational Intelligence 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
BOBJ, BW, SAC, Excel

Reports, universes, queries, and extracts are cataloged, scored, and prioritized for modernization.

Usage scan
Treatment

Engineering Layer

02
Governed Semantic Layer

Duplicate reports and conflicting definitions are consolidated into a certified enterprise semantic layer.

Semantic API
03
Dashboards & Self-Service

Priority intelligence experiences are rebuilt for SAC, Power BI, or Datasphere with RBAC.

BI Ecosystem
Output

Activation Layer

04
Executive Decisioning

Trusted assets power operational cockpits, predictive models, and agentic reasoning workflows.

Decision Tier
What enters

BOBJ, BW, SAC, Excel

What Unolabs does

Governed Semantic Layer -> Dashboards & Self-Service

What exits

Executive Decisioning

Control Points

Inventory -> Rationalize -> Modernize -> 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 the work is engineered

01

Intelligence Architecture

We design the foundations for governed operations, ensuring every metric, dimension, and report is trusted and visible.

02

Semantic Standardization

We implement enterprise-wide business logic that ensures consistency across SAC, Power BI, and legacy environments.

03

Modernization Acceleration

We transition legacy BusinessObjects estates to modern analytics ecosystems without losing historical context or governance.

04

Operational Observability

We add logs, lineage, and performance telemetry so teams can manage the health of the entire intelligence estate.

Strategic Assessment

Enterprise Reporting Maturity Model

Where does your organization 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 systems

Isolated silos with manual exports and inconsistent metric definitions.

Level 2

Departmental BI operations

Established reporting within functions but lacking enterprise-wide governance.

Level 3

Governed enterprise reporting

Standardized controls, certified datasets, and unified KPI definitions across the estate.

Level 4

Real-time operational intelligence

Low-latency visibility into core business events with automated alerting.

Level 5

Autonomous decision ecosystems

Agentic orchestration and self-optimizing intelligence delivery at global scale.

Industry Benchmarking

Report Rationalization
Industry Avg
15%
Market Leaders
75%+
Decision Latency
Industry Avg
Days/Weeks
Market Leaders
Seconds/Minutes
Governance Coverage
Industry Avg
Low
Market Leaders
Comprehensive

Transformation Progression

1

Intelligence Audit

Assessment of report usage, metric drift, and modernization blockers to define a maturity baseline.

2

Semantic Redesign

Rationalizing measures, dimensions, and universes into a governed enterprise semantic layer.

3

Platform Modernization

Migrating legacy BusinessObjects workloads to SAC, Power BI, or Datasphere with built-in controls.

4

Operational Activation

Deploying real-time cockpits and operational observability for executive decision-makers.

5

Autonomous Scaling

Enabling agentic retrieval and self-service intelligence across the entire enterprise estate.

Vertical Expertise

Industry Reporting Intelligence Patterns

Utilities

Operational infrastructure visibility ecosystems

Banking & BFS

Governed financial intelligence and risk systems

Retail & CPG

Commerce intelligence and operational visibility

Manufacturing

Operational telemetry and production intelligence

Healthcare

Clinical reporting and governance ecosystems

In Depth

What this means in practice

Intelligence Over Reporting

We do not build dashboards. We build intelligence ecosystems that accelerate executive decision-making and improve operational resilience.

Semantic Consistency First

Intelligence only helps when measures are trusted. We redesign the semantic definition layer before rebuilding a single visual.

Governed Self-Service

Business users get flexibility through certified datasets, governed access patterns, and clear publishing rules.

Dynamic Data Flow

Operational Intelligence Flow

This flow shows how fragmented reporting signals are industrialized into trusted executive assets through governed architecture.

SAP BI & Business ObjectsData Flow Architecture
1
Inventory

BOBJ, BW, SAC, Excel

Reports, universes, queries, and extracts are cataloged, scored, and prioritized for modernization.

Usage scan
2
Rationalize

Governed Semantic Layer

Duplicate reports and conflicting definitions are consolidated into a certified enterprise semantic layer.

Semantic API
3
Modernize

Dashboards & Self-Service

Priority intelligence experiences are rebuilt for SAC, Power BI, or Datasphere with RBAC.

BI Ecosystem
4
Activate

Executive Decisioning

Trusted assets power operational cockpits, predictive models, and agentic reasoning workflows.

Decision Tier
Lineage tracked
Policy enforced
Outputs reusable
Flowchart

Execution flow 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

Accelerated Decision Speed

2

Architecture Decision

Intelligence Architecture

3

Data Treatment

Governed Semantic Layer

4

Controls Applied

Dashboards & Self-Service

5

Operational Output

Executive Decisioning

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.

Enterprise reporting architecture
SAP BI modernization framework
KPI governance operating models
Enterprise semantic reporting layers
Executive intelligence ecosystems
Operational reporting observability
Business Objects modernization strategy
Enterprise analytics governance systems
Roadmap

The delivery path

1

Understand Context

Inventory systems, stakeholders, technical debt, and business constraints to define the modernization 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 semantic, retrieval, and orchestration layers required for autonomous scale.

4

Operationalize AI

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

5

Optimize Outcomes

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

Outcomes

What changes after the work

Faster executive decision-making

This outcome is tracked through the architecture, delivery assets, operating model, and data-flow controls created during the engagement.

Improved operational visibility

This outcome is tracked through the architecture, delivery assets, operating model, and data-flow controls created during the engagement.

Standardized enterprise KPI governance

This outcome is tracked through the architecture, delivery assets, operating model, and data-flow controls created during the engagement.

Reduced reporting fragmentation

This outcome is tracked through the architecture, delivery assets, operating model, and data-flow controls created during the engagement.

Faster enterprise intelligence delivery

This outcome is tracked through the architecture, delivery assets, operating model, and data-flow controls created during the engagement.

Increased cross-functional visibility

This outcome is tracked through the architecture, delivery assets, operating model, and data-flow controls created during the engagement.

Improved strategic reporting consistency

This outcome is tracked through the architecture, delivery assets, operating model, and data-flow controls created during the engagement.

Enhanced operational responsiveness

This outcome is tracked through the architecture, delivery assets, operating model, and data-flow controls created during the engagement.

Make SAP BI & Business Objects visible, governed, and production-ready.