Data architecture and analytics platforms
Data architecture and analytics platforms
We help organisations build a data-driven operating model by designing data architectures, models, warehouses and analytics platforms that provide trusted data for decision-making.
A reliable data foundation for analytics and decision-making
Data creates value when it is structured, aligned, high quality and readily accessible. We design architectures that connect disparate sources, establish consistent data models and give organisations a reliable foundation for reporting, analytics and more advanced data use cases. The result is an organisation that has data but lacks a practical way to use it to guide operational and growth decisions.
Common challenges:
Data fragmented across different systems
Unstructured data storage
Fragmented analytics
Our approach: data as a strategic asset. We design data architectures that allow organisations to operate based on reliable data.
What the service includes
Data architecture design
We define data domains, sources, flows, storage, integration, quality and access principles.
Data modelling
We create conceptual, logical and physical data models aligned with business processes and analytics requirements.
Data warehouse development
We design and implement data warehouses, data lakes, ETL/ELT processes and consolidation solutions.
Analytics platforms and data governance
We build reporting, KPI and analytics environments and establish data quality, cataloguing and accountability principles.
Value to client
Easier scaling
Leaders and specialists receive timely, comparable data prepared for decision-making.
Data-driven operations
Analytics becomes part of day-to-day processes, planning and performance monitoring.
Better decisions
A modular architecture makes it easier to connect new sources, metrics and analytics use cases.
Trusted data
Consistent models and quality rules reduce the risk of conflicting metrics and inaccurate interpretations.
Service model
Services can be delivered as a standalone initiative or integrated into the full project lifecycle:
Data maturity and source assessment
Duration: 3–6 weeks
Includes
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Analysis of data sources, models, quality, responsibilities, reports and technologies
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Analysis of data sources, models, quality, responsibilities, reports and technologies
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Analysis of data sources, models, quality, responsibilities, reports and technologies
Result
Current-state assessment
Prioritised data improvement plan
Current-state assessment; prioritised data improvement plan
Data architecture and model
Duration: 4–10 weeks
Includes
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Design of the target architecture, data domains, flows, models, quality and access principles
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Design of the target architecture, data domains, flows, models, quality and access principles
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Design of the target architecture, data domains, flows, models, quality and access principles
Result
Agreed data architecture
Core data models
Agreed data architecture; core data models
Data warehouse and integrations
Duration: 2–6 months
Includes
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Data collection, transformation and consolidation
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Implementation of the warehouse and data quality mechanisms
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Data collection, transformation and consolidation; implementation of the warehouse and data quality mechanisms
Result
A functioning centralised data platform
A functioning centralised data platform
A functioning centralised data platform
Analytics and management metrics
Duration: 1–4 months
Includes
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KPI models, reports, summaries and visualisations
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User access solutions
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KPI models, reports, summaries and visualisations; user access solutions
Result
An analytics and performance-monitoring environment ready for decision-making
An analytics and performance-monitoring environment ready for decision-making
An analytics and performance-monitoring environment ready for decision-making
When this service creates the most value
when an organisation needs a common data model or warehouse
when preparing reports requires substantial manual work
when data is stored across multiple systems and metrics are calculated inconsistently
Build a reliable data foundation for organisational decision-making
Bring data sources, models and analytics together in a consistent, governed and scalable platform.
Discuss the project