Data
One consistent view, built from many sources.
At a glance
- Best for
- Multi-entity or multi-site organisations whose figures live in separate systems and rarely agree
- Typical engagement
- Fixed-scope or ongoing, agreed to fit the work.
- Typical duration
- Varies by scope; agreed at the start of the engagement.
- Team
- Sized to the scope, drawn from our delivery team.
The problem
Where this costs you time.
Figures in separate systems
The answer to one question lives in four places that disagree.
Reconciliation by hand
Teams spend days each period matching figures across sources.
No consolidated view
Leaders see partial pictures and make decisions with incomplete data.
What we do
Capabilities
Source consolidation
Data gathered from each system into one agreed structure.
Reconciliation
Checks that totals match across sources, with differences explained.
Common dimensions
Entities, sites, dates and categories aligned across every source.
Consolidated reporting
Dashboards and reports built on the single, reconciled view.
Scheduled refresh
Updates on the cadence the business needs, from daily to monthly.
Traceable figures
Every number can be traced back to the source record it came from.
Benefits
What changes when this works.
Outcomes we design for. Measured results appear only after a client confirms them.
- One set of numbers across the business
- Less time spent reconciling
- Leaders working from complete data
- Figures that can be traced and checked
Process
How data aggregation engagements run.
Stage 1
Discover and Diagnose
Business, workforce and compliance analysis.
Tech deliverablesProcess map, data-flow map, risk registerStage 2
Design and Align
Solution architecture, operating models, integration planning.
Tech deliverablesArchitecture, prototype, test planStage 3
Implement and Enable
Deployment, onboarding, system validation, change management.
Tech deliverablesBuild, integrate, test, trainStage 4
Govern and Optimize
Continuous compliance monitoring, reporting, automation and enhancement.
Tech deliverablesMonitor, support, improve
Technologies
Tools we would use.
Integration
- Extract and load tools
- APIs
- Scheduled jobs
- File connectors
- Database replication
Reconciliation
- Matching rules
- Variance reports
- Exception queues
- Control totals
- Audit trails
Reporting
- BI dashboards
- Consolidated models
- Drill-through to source
- Scheduled reports
- Semantic layers
Industries
Where this matters most.
Oil and gas
Production, maintenance and workforce data from several sites combined into one view.
Pharmaceuticals
Consolidated quality and batch records, reconciled across facilities for review.
Chemicals and fertilizers
Plant, warehouse and finance figures aligned so cost and output agree.
Related
Where this connects.
- Data Strategy & GovernanceDecide who owns your data, what it means, and how it is kept reliable.
- Data strategy and roadmap
- Ownership, definitions and quality rules
- Policies that people can follow
- Data EngineeringReliable pipelines that move and prepare data from source to use.
- Pipelines from source to warehouse
- Data models built for analysis
- Monitoring for freshness and quality
- Our platformStellar Core connects people, payroll and compliance.Explore Stellar Core
FAQ
Questions we hear.
Answers are drafted for review. Anything that needs a fact from Stellar is marked.
Have a business challenge worth solving?
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