Current-state map
Connect important sources, pipelines, storage, models, reports, consumers, and owners. Record the dependencies a proposed change would affect.
Data & analytics strategy
Data platform assessment
Assess your data platform before committing to repairs, a migration, or a rebuild. We examine architecture, pipelines, reporting, reliability, cost, and ownership, then deliver prioritized findings and an implementation outline.
The problem
Find out what to repair, what to replace, and what to leave alone.
Common signals
When this work becomes useful
- Refreshes and pipelines fail unpredictably
- Cloud or BI costs are difficult to explain
- Reports disagree or run slowly
- A migration or major investment is being considered
Concrete output
What the engagement can produce
Findings and unresolved questions
Inspect representative workloads, failures, access, costs, and maintenance practices. Separate observed issues from assumptions and explain what missing evidence prevents us from concluding.
Repair-versus-rebuild options
Compare keeping the current platform, targeted repairs, selective replacement, and a staged migration. Include disruption, dependencies, ownership, and the conditions that would rule an option out.
Implementation outline
Define the first recommended scope, sequence, responsible people, prerequisites, and acceptance checks. The assessment can also recommend deferring a project.
Scope variants
Shape the engagement around the need
An analytics domain
Review the full data path behind one area of reporting, from source access through models and decisions. A Power BI-only review has its own health-check service.
Cloud platform review
Architecture, workloads, cost, security, pipelines, performance, and operating readiness.
End-to-end assessment
From source acquisition through reporting and decision use.
Delivery approach
From current state to clear ownership
Frame the decision
Agree the business problem, coverage, constraints, and evidence available for review.
Inspect the data path
Follow representative outputs back through models, transformations, sources, and ownership.
Compare interventions
Test the important assumptions and compare options without a predetermined platform recommendation.
Hand over the findings
Review priorities, dependencies, unknowns, and the first implementation outline with the people who own the decision.
Technical context
Platforms and disciplines
- Power BI
- Microsoft Fabric
- Snowflake
- SQL
- Pipelines
- Semantic models
What we need to begin
- A decision to support and an agreed review boundary
- Representative architecture, pipeline and reporting artifacts, workload history, and cost information
- Approved read-only access or guided review with system owners
- Business and technical participants who can resolve definitions and confirm constraints
Engagement fit
Clear boundaries make better projects.
Often a good fit
- Teams planning a modernization
- Organizations inheriting an undocumented environment
- Leaders facing performance or reliability issues
- Buyers validating an existing proposal
Probably not the right fit
- A compliance certification
- Penetration testing
- A generic checklist without system access
Anonymized proof
Assessment work is grounded in the same operational details used to improve reporting systems: source definitions, refresh paths, semantic models, review routines, and maintenance ownership.Explore representative work
Questions
What teams often ask first
Will the assessment include implementation?
The assessment produces findings and an implementation outline. Repairs or a follow-on project require a separate agreement. You can take the findings to your own team or another provider.
How is this different from a Power BI health check?
A Power BI health check concentrates on reporting models, workspaces, measures, refreshes, and access. A data platform assessment spans the upstream sources, pipelines, storage, architecture, economics, and team responsibilities as well.
What affects assessment cost and timing?
Coverage, source and platform count, documentation, access restrictions, representative workload availability, and the people needed to answer important questions. We scope those conditions before setting a delivery window.
Will you recommend a new platform?
Only if the findings justify it. A smaller repair, a clearer definition, better monitoring, or a decision to wait may be the more useful result.
Compare scope, prerequisites, investment guidance, and ownership before deciding.
The packaged engagements and delivery models make the commercial boundary visible without forcing every project into the same shape.