Make the right data and analytics decisions before you build

The wrong first project can create years of technical debt

Organisations often begin with the visible symptom: another dashboard, another spreadsheet replacement, another data platform, or another AI pilot.

But the real issue may be unclear metrics, duplicated systems, poor data quality, missing ownership, or an architecture that has grown without a plan.

• Leadership does not have a consistent view of performance
• Multiple teams build overlapping or conflicting reports
• Nobody has a complete map of where important data comes from
• The organisation is considering Fabric, Azure, a warehouse, or another platform but is unsure what is actually needed
• Power BI has grown without clear workspace, security, or governance standards
• AI initiatives are being discussed before data readiness has been assessed
• Manual reporting is increasing but there is no prioritised modernisation plan
• Technical teams and business teams have different views of what should be fixed first

Datazeb helps turn those competing problems into a structured sequence of decisions.

Advisory services

Current-state assessment

Understand what you already have before deciding what to replace

A good strategy starts with an accurate picture of the current environment.

Datazeb can review:

• Business-critical reports and recurring management packs
• Power BI workspaces, datasets, reports, gateways, and refreshes
• Excel-based reporting and manual processes
• Databases, warehouses, and analytical tables
• ETL / ELT pipelines and scheduled jobs
• APIs and third-party integrations
• Automation workflows
• AI pilots, assistants, or knowledge solutions
• Security, access, governance, and ownership
• Known data-quality issues and recurring support problems

The goal is to distinguish what is valuable and should be retained from what is creating unnecessary risk or effort.

Business-priority mapping

Start with decisions, not technology

A technology roadmap is only useful if it reflects the decisions and outcomes the business is trying to improve.

Datazeb can work with stakeholders to identify:

• Critical management decisions
• High-value KPIs and reporting questions
• Operational blind spots
• Processes consuming excessive manual effort
• Data needed for growth, compliance, or service improvement
• Analytics requests currently blocked by technical limitations
• AI opportunities linked to measurable business tasks

KPI and reporting framework

A dashboard cannot resolve disagreement about what a metric means

Many reporting problems are definition problems disguised as technical problems.

Datazeb can help structure a measurement framework that clarifies:

• What each KPI means
• Who owns the definition
• How it is calculated
• Which source system is authoritative
• How often it should refresh
• Who should see it
• Which level of detail is required
• How exceptions should be interpreted

This creates a stronger foundation for executive dashboards, departmental reporting, and self-service analytics.

Data architecture roadmap

Design for the business you are becoming, not only the reports you have today

A target architecture should be proportionate to the organisation’s size, complexity, data volume, internal skills, and expected growth.

1. Current Systems
2. Integration Layer
3. Trusted Data
4. Analytics / AI
5. Governance & Ownership

Datazeb can define a phased target state without forcing an enterprise-scale architecture where a simpler solution is more appropriate.

Power BI governance

Make Power BI easier to scale without losing control

As Power BI adoption grows, organisations often face duplicated reports, inconsistent metrics, unclear ownership, and uncontrolled workspace growth.

A governance review can cover:

• Workspace structure and ownership
• Development / test / production approach
• Semantic model reuse
• Naming and documentation standards
• Row-level security and access
• Gateway and refresh ownership
• Deployment and release processes
• Report lifecycle and retirement
• Self-service BI boundaries
• Licensing and capacity considerations

The objective is not governance for its own sake. It is to make analytics easier to trust, maintain, and scale.

AI strategy and readiness

Do not start with ‘Where can we use AI?’ Start with ‘Which business problem is worth solving?’

Datazeb can help organisations evaluate AI opportunities based on business value, data readiness, workflow fit, risk, and implementation complexity.

• Prioritise practical AI use cases
• Assess whether trusted data or knowledge sources exist
• Identify permission and privacy constraints
• Determine where human review is required
• Separate chatbot, RAG, automation, and agentic use cases
• Define proof-of-concept success criteria
• Map dependencies before production deployment

Explore AI & Agentic Solutions

Automation opportunity mapping

Find the repetitive work worth removing

A strategic review can identify workflows where automation will create meaningful operational value.

• High-frequency manual processes
• Repeated exports and data re-entry
• Routine email and document handling
• Recurring approvals and reminders
• Cross-system hand-offs
• Manual reporting distribution
• Exception monitoring
• AI-assisted tasks involving text or documents

Each opportunity can be assessed by expected value, implementation complexity, dependencies, and operational risk.

Technology advisory

Choose platforms because they fit the problem – not because they are fashionable

Datazeb can help evaluate technology choices across analytics, databases, integration, cloud, automation, and AI.

The recommendation should consider:

• Existing technology investments
• Data volumes and refresh expectations
• Internal technical capability
• Security and governance needs
• Licensing and operating cost
• Integration requirements
• Expected growth
• Vendor lock-in and maintainability
• Implementation complexity

Prioritised roadmap

Turn a long wish list into a practical sequence

The output of an advisory engagement should make the next decisions easier.

A roadmap may classify initiatives into:

• Immediate risk or reliability fixes
• Quick wins
• Foundational data work
• Reporting modernisation
• Governance improvements
• Integration priorities
• Automation opportunities
• AI pilots
• Longer-term platform or architecture changes

Each initiative should be tied to dependencies, expected value, and an appropriate delivery sequence.

Typical deliverables

• Current-state assessment
• Pain-point and dependency map
• Business priority summary
• Target architecture
• Reporting / KPI framework recommendations
• Power BI governance recommendations
• Data integration roadmap
• AI readiness and opportunity map
• Automation opportunity backlog
• Prioritised implementation roadmap
• Executive summary for decision-makers

Deliverables should be proportionate to the scope. Avoid producing large strategy documents that nobody uses.

Advisory engagement options

Why Datazeb for strategy & advisory

How we work

1. Discover
   Understand business goals, decision-making needs, current frustrations, stakeholders, and constraints.
2. Assess
   Review the current reporting, data, platform, governance, automation, and AI environment.
3. Align
   Clarify priorities, KPI definitions, ownership, dependencies, and what success should look like.
4. Design
   Define the target state, principles, architecture, governance approach, and recommended initiatives.
5. Prioritise
   Sequence the roadmap based on value, dependencies, risk, and implementation complexity.
6. Support Delivery
   Datazeb can remain involved as advisor or implementation partner where required.

Frequently asked questions