A fragmented analytics estate
Teams maintain separate datasets and overlapping transformations. We identify the shared foundation needed to reduce duplication and support agreed consumers.
DATA & ANALYTICS SOLUTIONS
Data Analytics Platform
Design and modernize analytics platforms, warehouses and lakehouses using Microsoft Fabric, Azure and Power BI.
BUILT FOR YOUR OPERATIONS
A shared platform for analytics your teams can use.
When reporting grows across disconnected files and tools, each new question becomes another integration project. We design or modernize a common analytics foundation so data can be organized, governed and consumed consistently. An engagement can involve Microsoft Fabric, Azure, Power BI or your existing stack, depending on requirements. The architecture should follow your data, access needs and operating model, with licensing and running costs made visible.
THE PROBLEMS WE ADDRESS
Where this service can help.
Start with the friction your team encounters, then define the outcome worth improving.
An architecture that no longer fits
Existing storage and reporting arrangements may struggle with new sources or responsibilities. We assess practical modernization options and migration boundaries.
Unclear ownership and access
A central platform still needs accountable dataset owners and permission rules. We define these alongside workspaces, environments and data organization.
CAPABILITIES & DELIVERABLES
What your engagement can include.
The final scope is agreed in writing. These capabilities explain the work we can deliver and the responsibilities that need to be established.
Platform assessment and design
A documented target architecture, source landscape and implementation roadmap. Recommendations account for existing investments, operating constraints and intended workloads.
Warehouse or lakehouse foundation
The agreed storage organization, data layers and environment setup, with naming, access and deployment conventions appropriate to the chosen platform.
Selected data and consumption paths
The sources, pipelines and curated datasets named in scope. Connections to reporting or AI consumers are validated for their agreed use.
Governance and operational handover
Ownership, access responsibilities and relevant operating guidance. Monitoring, capacity management and future expansion are addressed to the extent agreed in the proposal.
EXAMPLE USE CASES
Practical ways to put it to work.
Illustrative applications, not claims about completed client projects. Feasibility depends on your systems, information and operating requirements.
A common analytics foundation
Organize agreed business-system data so different teams can work from shared structures rather than separate exports and reconciliations.
Modernizing an existing platform
Assess a staged move from fragmented storage or reporting arrangements to a warehouse or lakehouse design suited to the workload.
Preparing for wider analytics and AI
Create curated, permission-aware datasets that can support future reporting and AI use cases without assuming they all need to be built at once.
HOW WE WORK
From first conversation to handover.
We make the scope and review points clear before building. A free introductory conversation helps identify the appropriate next step; detailed assessment and delivery are separately scoped.
01 / Understand
Assess current analytics, source systems, consumers, ownership and operating costs.
02 / Define
Choose an architecture and staged scope with explicit access and licensing assumptions.
03 / Build & validate
Build the agreed foundation and validate selected source-to-consumer data paths.
04 / Release & hand over
Hand over platform conventions, responsibilities and the agreed plan for ongoing operations.
FREQUENTLY ASKED QUESTIONS
Questions before we begin.
Do we have to move to Microsoft Fabric?
No. Fabric is one option. We assess your current stack and requirements before recommending whether to reuse, extend or change the platform.
Is this the same as creating Power BI dashboards?
Dashboard development focuses on how people consume and interpret information. A platform engagement establishes the shared data architecture and operating foundation beneath those experiences.
Are licences and cloud capacity included?
They are identified separately unless your proposal says otherwise. The required subscriptions, capacity and usage costs depend on the selected architecture and workload.
Can the platform be introduced in stages?
Yes. A first phase can establish the foundation and selected data flows. Additional sources, domains and consumers can then be prioritized as separate increments.
START WITH A CONVERSATION
Bring the challenge. Let’s find the next step.
Discuss your goals, current systems and the work you want to improve. The free assessment is a 30-minute introductory conversation; a detailed technical or workflow assessment is a separate paid engagement.