Independent Baseline
Document the current architecture from evidence rather than assumptions or vendor narratives.
Strategy & Architecture Assessment
Enterprise Data Architecture Assessment for Evidence-Backed Modernisation Decisions
DataConsultant reviews your current enterprise data architecture across business alignment, data domains, platforms, integration, governance controls, security, resilience, operating practices and technical debt. The result is a defensible baseline of what is working, what is creating risk or constraint, and which architecture actions should be prioritised before major cloud, analytics, AI or platform investment.
Evidence-led current-state architecture review
Gap, risk, technical-debt and dependency findings
Platform, integration and control decisions assessed together
Prioritised remediation roadmap and executive readout
Assessment criteria, evidence access, stakeholder participation, timeline and commercial terms are confirmed during scoping. The service is an independent consulting assessment and does not constitute statutory audit, certification or legal advice.
Risk Visibility
Connect architecture gaps with business, operational, security, governance and delivery exposure.
Decision Clarity
Clarify what to retain, remediate, consolidate, retire, redesign or investigate further.
Prioritised Action
Sequence recommendations around dependencies, urgency, readiness and transformation objectives.
When to use this assessment
Architecture Uncertainty Becomes Expensive When Major Decisions Depend on It
An assessment is useful when leadership needs a defensible view of the data estate before approving a platform, migration, operating-model, AI or transformation decision. It is especially valuable when architecture documentation, ownership or control evidence is fragmented across teams.
Platforms overlap without clear roles
Warehouses, lakes, lakehouses, integration tools and analytical environments have accumulated independently, making ownership, placement and retirement decisions difficult.
Data movement is brittle or opaque
Point-to-point interfaces, duplicated transformations, manual exchanges or unclear lineage create operational dependencies that are hard to assess during change.
Governance is not reflected in design
Ownership, classification, quality, metadata, access, retention, resilience and auditability expectations are inconsistent across platforms or projects.
Cloud, analytics or AI plans lack a baseline
Teams are making target-state commitments before understanding legacy dependencies, technical debt, workload constraints and architecture exceptions.
Get an Evidence-Backed Architecture Baseline Before the Next Major Investment Decision
Define the assessment boundary, evidence required and decisions the final report must support across platforms, data flows, controls and transformation dependencies.
Service definition and boundaries
A Diagnostic Review of Architecture Fitness, Gaps and Readiness
The engagement tests whether the current enterprise data architecture is coherent enough to support business priorities and planned change, and whether the most material risks, dependencies and design constraints are understood.
What DataConsultant actually does
We establish the scope and review criteria, request and organise evidence, interview accountable stakeholders, walk through current architecture and data flows, test architecture decisions against agreed requirements, identify gaps and contributing conditions, validate findings, and convert the results into prioritised recommendations and an executive decision pack.
01
Frame the decisionsDefine why the assessment is needed, which architecture decisions it must inform and what evidence is available.
02
Inspect the estateReview architecture artefacts, platforms, data flows, integration patterns, controls, operating evidence and stakeholder perspectives.
03
Validate findingsSeparate observed evidence from assumptions, record limitations and confirm material gaps with accountable owners.
04
Prioritise actionTranslate findings into architecture decisions, remediation priorities, dependencies and follow-on workstreams.
Typically in scope
- Current-state architecture and platform landscape
- Data domains, flows, integration and interoperability
- Architecture principles, governance and control implications
- Technical debt, resilience and operational supportability
- Gap, risk, dependency and target-readiness assessment
- Recommendations, priority roadmap and executive readout
Not automatically included
- Detailed target-state architecture or engineering design
- Platform migration, build or configuration work
- Penetration testing or formal security certification
- Statutory audit, regulatory certification or legal advice
- Vendor procurement or licensing negotiation
- Full data remediation, profiling or performance testing unless scoped
Assessment domains
Eight Architecture Lenses Connect Business Intent to Technical Reality
The exact criteria are tailored to the estate and decisions required. The assessment does not assume that every domain must be scored numerically; evidence can be recorded as established, partial, gap, not evidenced or not applicable where that is more defensible.
Business & Strategy Alignment
How architecture choices support business capabilities, critical decisions, transformation priorities, service expectations and investment constraints.
Evidence: priorities, roadmaps, sponsorshipDomains & Information Structure
Domain boundaries, authoritative sources, information concepts, data products, ownership, shared definitions and cross-domain dependencies.
Evidence: models, catalogues, ownershipPlatforms & Workloads
Platform roles, workload placement, storage and processing patterns, overlap, scalability, capacity, performance and lifecycle decisions.
Evidence: inventories, workload maps, costsIntegration & Interoperability
APIs, events, streaming, batch, replication, files, orchestration, schema management, error handling, lineage and fragile dependencies.
Evidence: interfaces, flows, incidentsGovernance, Metadata & Quality
Architecture governance, standards, catalogue and lineage coverage, quality controls, master-data dependencies, decision rights and exceptions.
Evidence: policies, standards, issue logsSecurity, Privacy & Resilience
Identity and access, classification, encryption, privacy constraints, retention, auditability, backup, recovery, availability and segregation.
Evidence: controls, risks, service needsOperations & Observability
Monitoring, service ownership, incident and change handling, capacity, reliability, performance evidence, release practices and support boundaries.
Evidence: telemetry, runbooks, service dataTechnical Debt & Transition Readiness
Architecture exceptions, unsupported patterns, retirement candidates, dependencies, skills, sourcing, migration constraints and required decision gates.
Evidence: backlog, exceptions, dependenciesEvidence to finding
Findings Are Traceable to Evidence, Context and Decision Impact
The assessment separates facts, stakeholder assertions and unresolved evidence gaps. Each material finding is documented with its observation, implication, evidence basis, affected architecture area, dependency and recommended response.
Step 1Evidence registerRecord documents, systems, workshops and limitations.
Step 2Architecture reviewInspect domains, platforms, flows, controls and operations.
Step 3Finding validationConfirm observations with owners and challenge assumptions.
Step 4Priority logicEvaluate impact, dependency, urgency and remediation effort.
Step 5Decision packTranslate findings into actions, roadmap and follow-on decisions.
Architecture diagrams & inventories
Data-flow, lineage & interface evidence
Policies, standards & architecture decisions
Issues, incidents, capacity & performance evidence
Transformation plans, budgets & dependencies
Stakeholder interviews & technical walkthroughs
No hidden proprietary pass/fail score
Priority criteria are agreed for the engagement and documented. Where evidence is incomplete, the limitation is recorded instead of inventing maturity, control effectiveness or performance conclusions.
Decision-ready outputs
What the Final Architecture Assessment Can Contain
Deliverables are tailored to the assessment objective and evidence available. The emphasis is on artefacts that leadership, architects, transformation teams and delivery partners can use to make and govern next decisions.
DELIVERABLE 01
Assessment scope & criteria
Agreed questions, architecture domains, evidence expectations, stakeholder roles, assumptions, exclusions and validation approach.
DELIVERABLE 02
Evidence register
Traceable record of source materials, interviews, system walkthroughs, missing evidence and material assessment limitations.
DELIVERABLE 03
Current-state architecture view
Landscape of major domains, data stores, platform roles, integration boundaries, control points and significant dependencies.
DELIVERABLE 04
Architecture findings report
Evidence-backed observations describing strengths, gaps, contributing conditions, implications, affected areas and confidence.
DELIVERABLE 05
Gap, risk & dependency register
Material architecture risks, technical debt, control gaps, transformation dependencies and ownership or decision issues.
DELIVERABLE 06
Target-state direction
Recommended capability, domain, platform, integration and control direction without implying detailed design is complete.
DELIVERABLE 07
Prioritised remediation roadmap
Sequenced architecture actions, dependencies, decision gates, accountable workstreams and areas requiring deeper design or validation.
DELIVERABLE 08
Executive readout & handover
Concise decision summary, priority actions, major trade-offs, evidence limitations and next-step recommendations for sponsors and architecture leadership.
Turn Architecture Findings Into Decisions Your Programme Can Act On
Agree the deliverables, priority logic and executive decision questions before the assessment starts so the output is usable for governance, funding and mobilisation.
Architecture gap map
From Fragmented Current State to a Governable Target Direction
The assessment is not just a list of defects. It establishes the delta between observed architecture and the capabilities required for the organisation’s intended future, so remediation can be sequenced around real dependencies.
Current-state pressure
Illustrative indicators identified through evidence
Platform overlap
Integration debt
Control consistency
Ownership clarity
Observability
Transition readiness
Target direction
Architecture characteristics required by the future state
Platform roles
Reusable patterns
Control by design
Domain ownership
Service visibility
Roadmap readiness
Illustrative visual only. Actual assessment status is based on agreed evidence and criteria; no default numeric score is applied.
Common assignments
Architecture Assessment Use Cases That Require More Than a Diagram Review
The same assessment method can be focused on different business situations, but the evidence, stakeholders and decision criteria change according to the trigger.
Platform modernisation baseline
Assess overlapping platforms, workload placement, integration patterns, controls and technical debt before approving a new lakehouse, warehouse or cloud data platform.
Integration and interoperability risk
Map fragile interfaces, duplicated transformations, schema dependencies, manual exchange and unclear data contracts that can undermine migration or operational resilience.
AI and analytics readiness
Review whether data platforms, metadata, lineage, quality, access, observability and domain ownership provide a dependable foundation for scaled analytics and AI use cases.
M&A or estate consolidation
Compare data domains, platforms, integrations, duplicated capabilities, control models and dependencies across acquired or reorganised environments.
Control remediation architecture
Assess whether architecture design and operating responsibilities address material findings around access, lineage, retention, resilience, data handling or auditability.
Architecture governance reset
Review principles, standards, exception handling, design authority, decision records and delivery compliance when projects are diverging from enterprise direction.
Engagement approach
A Structured Assessment Process With Validation Before Recommendation
The process is adapted to estate complexity and evidence availability. It avoids treating workshop opinions as facts and creates explicit checkpoints for scope, evidence, finding validation and executive decisions.
Scope
Confirm drivers, decisions, domains, systems, stakeholders, criteria and exclusions.
Evidence
Issue evidence request, establish inventory and record documentation or access gaps.
Walkthrough
Review architecture, data flows, platform roles, controls and operational practices.
Assess
Evaluate each domain against agreed requirements, principles and decision context.
Validate
Confirm material findings, evidence confidence, ownership and limitations with stakeholders.
Prioritise
Rank recommendations by impact, dependency, urgency, readiness and effort.
Readout
Present executive findings, roadmap, open decisions and recommended follow-on work.
What we need from you
Better Evidence Produces More Defensible Architecture Findings
DataConsultant can work with imperfect documentation, but missing evidence is recorded as a limitation rather than silently filled with assumptions. Early access to accountable stakeholders and representative artefacts improves assessment quality.
Business prioritiesTransformation objectives, critical capabilities, growth, service, cost, risk and target decisions.
Architecture artefactsCurrent diagrams, standards, decision records, domain models and approved patterns.
Platform inventoryData stores, cloud services, warehouses, lakehouses, integration and analytical platforms.
Data-flow evidenceInterfaces, lineage, orchestration, batch, event, streaming, file and replication dependencies.
Control evidenceAccess, classification, quality, metadata, retention, privacy, resilience and audit requirements.
Operational evidenceIncidents, problems, capacity, performance, monitoring, service ownership and support information.
Change portfolioCloud, ERP, analytics, AI, M&A, migration, procurement and retirement plans.
Stakeholder accessBusiness, architecture, data, cloud, security, governance, risk, operations and delivery owners.
Platform-aware, requirements-led
Review the Architecture Across Technology, Governance and Operational Boundaries
The assessment can cover the technology estate without becoming a product-reseller review. Recommendations are shaped by workloads, interoperability, existing investments, security and privacy requirements, operational capacity, skills and the architecture decisions the organisation actually needs to make.
Cloud & data platforms
Microsoft Azure, AWS, Google Cloud, Snowflake, Databricks, Microsoft Fabric, BigQuery, Redshift, Synapse Analytics and other relevant estate components.
Integration & orchestration
APIs, event platforms, Kafka, Airflow, dbt, ETL/ELT services, replication, files, data contracts and orchestration patterns.
Governance & metadata
Microsoft Purview, Collibra, Alation, Informatica and other catalogue, lineage, quality, policy or stewardship capabilities where deployed.
Analytics & AI consumption
BI, semantic layers, notebooks, machine-learning environments, AI applications and operational data consumers that depend on the architecture.
Security & privacy
Identity, access, encryption, secrets, classification, masking, retention, residency, logging and audit requirements relevant to the data estate.
Reliability & operations
Monitoring, observability, capacity, recovery, incident handling, change control, service ownership, supportability and technical lifecycle practices.
Validate Architecture Risk Before Migration, Consolidation or AI Scale
Share the current estate, planned change and known problem areas. We can define which evidence and architecture domains need review before the programme commits to a target design.
Commercial clarity
Custom Scope & Pricing for Enterprise Data Architecture Assessment
DataConsultant does not publish a fixed public fee for this service. A reliable estimate requires initial discovery because architecture assessment effort changes materially with estate size, evidence quality, stakeholder count, technical depth and the decisions the assessment must support.
Pricing is based on the agreed assessment boundary and evidence depth
The scoped proposal can define assessment domains, systems and platforms in review, stakeholder sessions, technical walkthroughs, evidence expectations, deliverables, review cycles, client responsibilities, exclusions and any optional target-state or implementation support. Timeline is confirmed after the same scoping process.
Request a Scoped QuoteBusiness scopeNumber of business units, domains, geographies and transformation workstreams.
Estate complexitySystems, platforms, environments, workloads, interfaces and deployment models.
Evidence conditionCompleteness of diagrams, inventories, lineage, operational data and decision records.
Stakeholder countInterviews, workshops, walkthroughs, validation sessions and executive review groups.
Technical depthHigh-level architecture review versus deep platform, integration, control or operational analysis.
Risk & control contextSecurity, privacy, resilience, regulatory, audit and evidence requirements.
Deliverable depthCurrent-state map, finding register, architecture principles, target direction and roadmap detail.
Follow-on supportOptional target architecture, implementation planning, assurance, migration or governance support.
Buyer fit
Choose an Assessment When You Need Independent Diagnosis Before Detailed Design
This service is deliberately different from implementation, formal audit and detailed future-state architecture. The right starting point depends on whether the immediate need is evidence, design, assurance or execution.
Good fit for this assessment
- You need an independent current-state baseline before major data-platform investment.
- Architecture documentation, ownership or platform roles are disputed or incomplete.
- Cloud, analytics or AI programmes need clarity on data-foundation dependencies.
- Technical debt or integration risk is slowing change or increasing operational exposure.
- Architecture governance needs evidence to prioritise standards, exceptions and remediation.
- Executives need a concise view of architecture risk, options and next decisions.
A different or additional service may be better
- You already have an accepted baseline and need detailed target-state architecture design.
- The issue is a single configuration defect requiring immediate engineering remediation.
- The primary need is formal legal advice, statutory audit, certification or penetration testing.
- A vendor selection is required without broader architecture, workload or operating analysis.
- You need implementation capacity rather than assessment and decision support.
- No accountable sponsor or evidence access is available for a meaningful review.
Why DataConsultant
Assessment Outputs Designed to Work Across Executive, Architecture and Delivery Teams
The value of an architecture assessment depends on whether its evidence, recommendations and boundaries are understandable to the people who must approve, govern and implement the next step.
Findings are tied to artefacts, walkthroughs, stakeholder evidence and documented limitations rather than unsupported maturity claims.
Architecture review criteria are connected to the decisions, capabilities, risks and transformation outcomes the organisation actually cares about.
Existing and planned technology is assessed against workload, interoperability, control, skill and operating requirements without assuming a preferred vendor.
Governance, privacy, security, resilience, lineage, quality and auditability are reviewed as architecture concerns, not detached checklists.
The final view distinguishes immediate actions, deeper design needs, dependencies and open decisions instead of ending at a generic findings list.
Where needed, separate follow-on support can carry context into target architecture, migration planning, assurance, governance and knowledge transfer.
Choose the Next Architecture Move From Evidence, Not Assumptions
Use a scoped assessment to establish the current-state facts, material gaps, dependencies and target-direction decisions before committing to detailed design or implementation.
Frequently asked questions
Enterprise Data Architecture Assessment Questions
Answers to common procurement and delivery questions about scope, evidence, findings, platforms, controls, timeline, pricing and follow-on work.
What is an Enterprise Data Architecture Assessment?
It is a structured, evidence-led review of the current enterprise data architecture against the organisation’s business priorities, architecture principles, platform roles, integration patterns, data-domain boundaries, governance controls, security and privacy requirements, resilience needs, operating practices and target-state ambitions. The assessment identifies strengths, gaps, risks, dependencies and practical remediation priorities; it is not a statutory audit or certification.
What does the assessment review?
Scope can cover business and architecture alignment, data domains and information structure, platforms and workloads, integration and interoperability, metadata and lineage, data quality and master-data dependencies, access and protection controls, resilience and observability, architecture governance, technical debt, lifecycle decisions and readiness for cloud, analytics or AI transformation. The final domains are agreed during scoping.
How is this different from a target-state data architecture project?
An assessment is primarily diagnostic: it establishes an evidence-backed baseline, identifies architecture gaps and risks, and recommends priorities. A target-state architecture project goes further into future-state design, logical and physical architecture, detailed patterns, standards, transition states and implementation guidance. The assessment can be used to determine whether that deeper design work is needed.
When should an organisation commission an architecture assessment?
Common triggers include platform modernisation, cloud migration, AI or analytics expansion, duplicated warehouses or lakehouses, fragile integrations, unclear data ownership, repeated architecture exceptions, rising technical debt, merger or divestment activity, regulatory remediation, procurement of a new platform, or concern that current designs cannot scale safely.
What evidence should we prepare?
Useful evidence can include business and transformation priorities, architecture diagrams, system and platform inventories, data-flow or lineage information, integration inventories, data-domain documentation, architecture principles, standards, security and privacy policies, issue and incident records, performance or capacity evidence, current roadmaps, vendor information, risk and audit findings, and access to accountable business and technology stakeholders.
What deliverables can we expect?
Typical outputs can include the agreed assessment scope and criteria, evidence register, current-state architecture view, domain-by-domain findings, architecture gap and risk register, technical-debt and dependency view, recommendations, target-state direction, architecture decision principles, prioritised remediation roadmap and an executive readout. Final deliverables depend on scope and evidence availability.
How are findings prioritised?
Findings are prioritised using agreed criteria such as business criticality, operational or control exposure, architectural dependency, transformation impact, urgency, evidence confidence and remediation complexity. DataConsultant does not rely on an undisclosed proprietary score or pass/fail threshold; priority logic and assumptions are documented as part of the assessment.
Can the assessment cover cloud, on-premises and hybrid estates?
Yes. The review can cover cloud, on-premises, hybrid and multi-cloud environments where relevant. The assessment remains requirements-led and considers workload fit, existing investments, interoperability, security, privacy, residency, resilience, skills, operating capacity and commercial constraints rather than assuming that one deployment model is automatically preferable.
Which platforms and technologies can be considered?
The assessment can consider the client’s existing and planned cloud, warehouse, lakehouse, integration, orchestration, metadata, quality, master-data, analytics and AI environments. Examples can include Microsoft Azure, AWS, Google Cloud, Snowflake, Databricks, Microsoft Fabric, BigQuery, Redshift, Synapse Analytics, Kafka, Airflow, dbt, Informatica, Microsoft Purview, Collibra and Alation where they are relevant to the estate.
Do you use architecture frameworks or vendor review frameworks?
Where appropriate, the assessment can use relevant client standards and recognised reference lenses to organise review criteria. For cloud workloads, first-party frameworks such as AWS Well-Architected or the Azure Well-Architected Framework may inform workload-specific checks. They do not replace enterprise data architecture criteria, legal advice, regulatory interpretation or the client’s own architecture governance.
Does an Enterprise Data Architecture Assessment guarantee security or compliance?
No. The assessment can identify architecture-related security, privacy, governance, resilience and control gaps within the agreed scope, but it does not guarantee compliance, eliminate risk, certify an environment, replace penetration testing or provide legal advice. Specialist assurance, regulatory, legal or security testing should be commissioned separately where required.
How long does the assessment take?
Timeline is confirmed after scoping. It depends on the number of business domains, systems and platforms, geography and regulatory context, architecture documentation quality, stakeholder availability, evidence access, workshop and review cycles, and whether the engagement includes deep technical analysis or target-state design support.
How is pricing determined?
DataConsultant does not publish a fixed fee for this service. Pricing is scope-led and confirmed through a Request a Quote process after the number of domains, systems, platforms, integrations, stakeholders, environments, evidence depth, workshops, control requirements, deliverables, onsite needs and any follow-on design or implementation support are understood.
Can DataConsultant work with our internal architects and existing vendors?
Yes. The assessment can be structured alongside internal enterprise architecture, data, cloud, security, governance, risk, operations and transformation teams, as well as software vendors and systems integrators. Responsibilities, evidence access, review roles, decision rights and escalation routes should be agreed during mobilisation.
Can DataConsultant help implement the recommendations?
Yes. Follow-on work can be scoped separately for target-state architecture, integration architecture, platform design, governance improvements, migration planning, architecture assurance, engineering support, operating-model changes, documentation, knowledge transfer or periodic health checks. Implementation scope is not automatically included in the assessment.
Enterprise Data Architecture Assessment Enquiry
Request an Assessment Scope Review
Share your contact details and requirement. DataConsultant can review the likely assessment boundary, evidence needs, stakeholder involvement and appropriate next step.