BI strategy and roadmap
Connect business priorities to reporting initiatives, governance, platform decisions, skills and a phased delivery roadmap.
Business intelligence consulting
Business Intelligence Consulting That Turns Business Data into Trusted Decisions
Connect business priorities to data architecture, analytics models, reporting and governance. Start with the decisions people need to make, then assess the sources, definitions and operating practices needed to support them.
Power BI may be a good fit for some Microsoft environments; the right platform and implementation depend on your existing investments, users, data, security and operating model.
Discuss Your BI RequirementsWhat is business intelligence consulting?
Business intelligence consulting is advisory and implementation support that helps organizations turn operational and analytical data into reliable information for planning, monitoring and decisions. A BI engagement can span business requirements, KPI definitions, data integration, architecture, modeling, reporting, security, validation and user adoption.
Some organizations need an independent assessment before choosing a platform. Others need help with fragmented reporting, inconsistent measures, unreliable refreshes, slow reports or unmanaged self-service content. Scope should reflect the actual business problem rather than assume that every challenge needs a new platform.
Business intelligence consulting services
Work may be strategic, technical or delivery-oriented. Capabilities, availability and deliverables are confirmed against the agreed scope before an engagement begins.
Architecture and platform advisory
Assess existing investments and requirements before recommending a data warehouse, lakehouse, semantic layer or reporting platform.
Data integration and ETL/ELT
Plan data access, ingestion, transformation, refresh, quality checks, error handling and operational ownership.
Data modeling and semantic layer
Define grain, facts, dimensions, relationships, reusable measures and business definitions that support consistent analysis.
Power BI consulting and implementation
Scope Power Query, semantic models, DAX, reports, security and deployment to the requirements of your Microsoft environment.
Dashboards and reporting
Design reports around user tasks, agreed KPIs, accessible interactions and the decisions they are intended to support.
Legacy BI modernization
Inventory reports and dependencies, prioritize what to retain or rebuild, map logic and reconcile representative results.
Governance, security and adoption
Address ownership, access, quality, lifecycle practices, user enablement and support responsibilities.
The listed areas describe possible BI consulting work; they are not a guarantee that every capability is currently available as a standalone service. Confirm the specific scope with Office Solution AI Labs.
A practical business intelligence architecture
A common BI design separates source systems, ingestion, storage, transformation, semantic modeling, presentation and governance. The implementation should reflect workload, security, support and cost requirements.
- Layer 1
Business sources
ERP, CRM, finance, operations, databases, files, SaaS platforms and APIs.
- Layer 2
Ingestion and integration
Approved connectors, gateways, APIs, batch loads or change-data patterns where supported.
- Layer 3
Storage and transformation
A suitable warehouse, lakehouse or analytical store with documented transformation and quality rules.
- Layer 4
Semantic and metric layer
Facts, dimensions, relationships, calculations, KPI definitions and appropriate security.
- Layer 5
Reports and analytics
Interactive reports, dashboards, paginated output, embedded analytics or approved exports.
- Layer 6
Governance and operations
Identity, access, lineage, audit, monitoring, lifecycle, support and cost controls.
Architecture decisions should account for data volume and growth, latency, source impact, connectivity, identity, residency, retention, concurrency, recovery, support and total cost. A reporting tool should not automatically become the integration engine or enterprise data store.
From business questions to trusted KPIs
Define measures before building visualizations. For each KPI, document the decision it supports, calculation, grain, inclusions and exclusions, time and currency rules, authoritative source, refresh frequency, owner and sensitivity.
For example, “revenue” may refer to booked, invoiced, recognized, gross or net revenue. Finance and business owners should agree which definition is appropriate for each purpose; a chart cannot resolve an ambiguous business definition.
Choose a BI platform for the workload
Power BI, Tableau, Qlik and other analytics platforms have different capabilities and operating models. Selection should follow requirements and existing investments, not platform preference alone.
- Existing data and BI investments, skills and support model
- Data volume, growth, transformation complexity and refresh needs
- Source-system load, connectivity, identity and gateway requirements
- Security, privacy, residency, retention and compliance obligations
- Concurrency, availability, recovery and operational expectations
- Licensing, capacity, cloud consumption and total cost of ownership
BI dashboard and reporting use cases
Reporting should be shaped around its audience, business process and intended action. Examples below are use-case categories, not customer case studies or claims of completed projects.
Executive and financial reporting
Bring together approved financial and operational measures while preserving definitions, reconciliation and sign-off controls.
Sales and customer analytics
Connect customer, pipeline and order data to agreed sales measures, with clear attention to source systems and data ownership.
Operations and supply chain
Monitor service, inventory or operational processes using relevant refresh, latency and exception requirements.
Enterprise self-service BI
Define reusable models, content ownership and access boundaries that support appropriate analysis by business teams.
Requirements may vary across finance, retail, healthcare, manufacturing, BFSI and FMCG. Validate applicable policies, business definitions, access controls and source-system constraints for each industry.
Governance, security and production readiness
Establish ownership and controls alongside delivery. Depending on the platform and data, this may include identity, least privilege, classification, workspace policies, row-level or object-level security where supported, approved sharing, audit, monitoring and lifecycle management.
- Test access with representative users and roles.
- Separate development, test and production as appropriate.
- Document owners, release checks, rollback and support.
- Monitor refresh failures, usage, quality and capacity.
- Review and retire content that is no longer needed.
BI consulting engagement methodology
A structured engagement connects discovery to production operations, with validation and business-owner review built into each stage.
- Phase 1
Business discovery
Clarify decisions, stakeholders, pain points, priority KPIs, current reports and expected outcomes.
- Phase 2
Current-state assessment
Inventory platforms, data sources, models, reports, integrations, access, refreshes and operational dependencies.
- Phase 3
Target-state design
Recommend architecture, semantic layer, platform approach, governance, security and delivery sequence.
- Phase 4
Representative proof of concept
Test a relevant business domain, data path, metrics, access rules, report experience and performance assumptions.
- Phase 5
Build and integration
Develop the agreed pipelines, transformations, models, measures, reports and supporting operational controls.
- Phase 6
Validation and acceptance
Reconcile outputs, test edge cases, permissions, refresh, usability and performance with business owners.
- Phase 7
Deployment and enablement
Release through the agreed lifecycle, transfer documentation and train the appropriate creators and consumers.
- Phase 8
Monitor and improve
Review adoption, freshness, quality, performance and cost to prioritize evidence-based improvements.
Legacy BI modernization and migration
Modernization may include Tableau, Qlik, Cognos, SAP BusinessObjects, MicroStrategy, Oracle Analytics, SSRS or spreadsheet reporting. Begin with inventory and prioritization rather than recreating every report without review.
- Identify report owners, users, schedules and criticality.
- Map sources, calculations, filters, prompts and security.
- Classify content to retire, retain, rebuild or redesign.
- Reconcile representative outputs and test access.
- Plan cutover, user enablement and legacy retirement.
Frequently asked questions
What is business intelligence consulting?
Business intelligence consulting combines advisory and implementation support to help organizations turn business and operational data into reliable reporting and analytical capabilities. Work may cover strategy, requirements, integration, models, reports, governance, validation and adoption.
What is included in BI consulting services?
Depending on the need, services may include BI strategy, KPI discovery, architecture, data pipelines, data modeling, Power BI or other platform work, migration, governance, performance review, training and ongoing support. Scope and deliverables should be agreed for each engagement.
Does every BI project need Power BI?
No. Power BI may fit organizations working with Microsoft data and productivity services, but platform selection should consider existing investments, users, architecture, security, licensing, skills and the operating model.
How should a BI project define KPIs?
Document the business purpose, calculation, grain, included records, time and currency rules, source, refresh needs, owner, target and sensitivity. Business owners should approve definitions before they are implemented in a model or report.
How do you improve trust in dashboards?
Agree authoritative sources and metric definitions, document transformation and refresh behavior, reconcile report results with approved source data, test access and make ownership and freshness visible to users.
Can BI consulting help with legacy platform migration?
A migration assessment can inventory reports, sources, calculations, schedules, security and users, then prioritize assets to retire, retain, rebuild, consolidate or redesign. Mapping is conceptual; features and results require validation in the target.
How are BI security and governance addressed?
Plan identities, least-privilege access, data classification, workspace and content ownership, row-level or object-level security where supported, release controls, auditing and monitoring. Test permissions using representative user roles.
How is BI project value measured?
Agree measurable outcomes before implementation, such as reporting cycle time, refresh reliability, data quality, usage or decision latency. Establish a baseline and compare under defined conditions; benefits are not guaranteed by deploying a dashboard.
How much does business intelligence consulting cost?
Cost depends on scope, complexity, data readiness, platforms, delivery model and support. A proposal should describe deliverables, assumptions, dependencies, acceptance criteria and costs beyond consulting, such as licenses and cloud capacity.
How do we get started?
Describe the decisions or reporting problems you want to address, the tools and data sources you use today, and the outcome you want. An initial discussion can help determine whether an assessment, roadmap or focused implementation is appropriate.
Discuss your business intelligence requirements
Tell us about the decisions, reporting challenges, data sources and outcomes you want to address. An initial discussion can help determine whether an assessment, roadmap or focused implementation is appropriate.
Do not send passwords, sensitive personal data or confidential production data through this enquiry form.
