01
Platform architecture & readiness
Assess sources, workloads and the platform design needed to support analytics and AI.
- Source and target architecture
- Access, capacity and integration needs
- Readiness gaps and delivery sequence
Data platforms & analytics
Trusted data foundations and analytics your teams can act on.
DATA & AI
Build the data foundation behind better decisions
When reports disagree, pipelines fail or information sits in separate systems, analytics and AI cannot deliver dependable value. We help connect enterprise sources, build governed data platforms and pipelines, and shape Power BI reporting around the decisions your teams need to make.
Start with the reporting decision and the sources behind it. Agree common definitions, data ownership and the controls needed to move from a source record to a usable report.
What we deliver
From source systems to useful reporting
Agree the platform, pipeline and reporting scope around your decisions. Specify outputs, quality criteria and operating responsibilities before delivery.
02
Data pipelines & integration
Connect enterprise sources through defined ingestion and transformation steps.
- Source-to-target mappings and contracts
- Transformation and validation rules
- Refresh, exception and recovery design
03
Data quality & governance
Make definitions and responsibilities explicit before reports are trusted.
- Ownership and access boundaries
- Quality checks and reconciliation
- Lineage and change control scope
04
Power BI & semantic models
Shape common measures and reports around the decisions your teams make.
- Agreed metric definitions
- Semantic models and reporting views
- Reconciled measures and user acceptance
05
Data operations & optimisation
Plan what it takes to keep the agreed data and reporting service useful.
- Monitoring and refresh ownership
- Failure handling and recovery testing
- Performance and cost review
DELIVERY APPROACH
Validate the data before release
Agree decisions and measures, design the flow, validate the build, then release with operating ownership. Acceptance comes before operational use.
Analytics delivery, software and IP
Choose what sits beyond the data foundation
Platform and Power BI delivery establish the foundation. Add model development, reusable prediction/simulation IP or financial analysis software only where the decision calls for it.
Power BI + AI/ML
Reusable IP for AI/ML in Power BI, predictive dashboards and risk-scoring visuals. Use when evaluated model outputs need to appear in reporting.
Prediction or simulation needs
Use Machine learning for custom model development. Explore Predictive Analytics for customer, demand or risk patterns, and Digital Twin for asset monitoring and simulation.
FinSight
Separately available software for conversational analysis and reporting over financial data. Explore it when teams need to ask questions of financial information.
Separate routes, agreed scope
Products are available by licence, subscription or SaaS, with or without services. Accelerators are reusable delivery IP; assess fit, adaptation and implementation responsibilities rather than assume inclusion.
Illustrative engagement pattern
From fragmented sources to trusted reporting
For reports that disagree across systems, agree a source-to-report design and reconciliation evidence. Use this illustrative pattern to identify the outputs, controls and owners your reporting scope needs.
01
Map the source-to-report flow
Identify conflicting definitions and source ownership. Agree the pipeline, platform and semantic-model design, with a data-flow or lineage view to review.
02
Reconcile and control access
Compare source and report totals, review quality exceptions and agree who can access each view. Scope specialist identity and cloud-security work where required.
03
Release with operating ownership
Assign refresh, monitoring and recovery owners. Agree report acceptance and adoption measures; assess reporting quality separately from any wider business outcome.
Start with the data decision that matters
Discuss your source systems, reporting gaps and analytics priorities. Describe the current platform and main constraint; do not upload sensitive data.
BUYER QUESTIONS
Agree foundations, ownership and the next step
Scope the reporting requirements before expanding into AI. Choose a delivery model around the agreed scope and ongoing ownership needed.
Let’s connect
Tell us about your data platform and reporting priorities
What happens next
- We route your enquiry to the relevant portfolio specialist.
- Where needed, we agree an NDA before you share confidential information.
- We clarify your priorities and agree the right next step with you.