Requirements and KPI definition
Clarify the decisions, audiences, business rules and measures that reporting should support.
Business intelligence consulting
Turn business questions into reliable reporting by aligning requirements, KPI definitions, data, technology and the people who use the results. Start with the decision you need to support—not an assumption that you need another dashboard or a platform rebuild.
Discuss Your BI RequirementsA business intelligence (BI) consultant helps an organization turn business requirements and data into dependable analytical capabilities. The consultant works across business stakeholders and technical teams to understand information needs, assess data sources, define measures, design solutions and support implementation.
Depending on the engagement, the consultant may advise an internal team, lead a defined assessment, guide architecture or contribute to implementation. BI consulting is centered on decision-support information: what should be measured, how data is prepared, how results are presented and how the solution is governed and adopted.
A BI consultant may support one specialist task or a broader delivery lifecycle. Confirm the specific capabilities and deliverables for your engagement before work begins.
Clarify the decisions, audiences, business rules and measures that reporting should support.
Review relevant source systems, data quality, integration needs and platform constraints before recommending a design.
Design or guide analytical models, dashboards and reports around validated definitions and user needs.
Address ownership, access, quality, documentation, release practices and knowledge transfer as part of the solution.
These are common BI consulting work categories, not a guarantee that every item is currently available as a standalone service. Confirm scope and team availability with Office Solution AI Labs.
An effective engagement should leave the organization with validated business logic, documented dependencies and a clear operating approach—not only a report file.
Describe the business problem, the current reporting environment and the outcome you want to improve.
Identify stakeholders, users, sources, constraints, security needs and the work required to reach a useful result.
Document verified observations, assumptions, options, risks and appropriate next steps.
Define deliverables, roles, dependencies, acceptance criteria, timelines and commercial terms.
Review progress at agreed checkpoints and test data, calculations, access and usability against requirements.
Provide agreed documentation and knowledge transfer, with ongoing support only where it is in scope.
Responsibilities can overlap. Use the business outcome and required work—not job titles alone—to determine which capabilities your project needs.
| Role | Typical focus |
|---|---|
| BI consultant | Connects business questions with requirements, metrics, data, architecture, reporting and governance. |
| Data analyst | Explores and interprets data to answer questions, identify patterns and communicate findings. |
| Data engineer | Builds and operates data pipelines, platforms and infrastructure used to prepare and move data. |
| Data scientist | Applies statistical, predictive or machine-learning methods to investigate and model data. |
| BI developer | Builds and maintains reports, semantic models and other BI assets, often in a specific platform. |
Evaluate the proposed consultant against your business context, systems and project responsibilities. Ask for relevant evidence where available, and independently verify credentials or affiliations.
A business intelligence consultant helps organizations turn business requirements and data into useful reporting and analytical capabilities. Work can include discovery, KPI definition, data integration, modeling, dashboards, governance, testing and adoption.
A BI consultant works with stakeholders and technical teams to understand decisions and reporting needs, assess data sources, define metrics, shape a solution and help validate and govern it. The exact responsibilities depend on the engagement.
Consider specialist help when reporting is manual, KPI definitions conflict, data sources are fragmented, dashboards are unreliable, a BI platform is being planned or modernized, or an internal team needs additional expertise.
No. A data analyst typically focuses on exploring and interpreting data. A BI consultant may work more broadly across business requirements, metrics, data architecture, reporting, governance and implementation. The roles can overlap in smaller teams.
Not necessarily. Business intelligence consulting can span requirements, data and reporting strategy across platforms. A Power BI consultant focuses on Microsoft's Power BI platform and its implementation. The appropriate scope depends on the business need.
Relevant skills may include business analysis, communication, SQL, data modeling, integration concepts, BI platforms, data quality, governance, security, testing and documentation. Required depth varies by project.
Cost depends on scope, expertise, duration, data readiness, platform, delivery model and support needs. Compare deliverables, assumptions, internal effort, licenses, cloud consumption and ongoing operations—not only an hourly or daily rate.
If available, describe the business decision, current reports or manual process, source systems, intended users, refresh needs and known data-quality concerns. Do not send passwords, unrestricted production exports or sensitive personal data in an initial enquiry.
Office Solution AI Labs publishes BI-related services and solutions. Contact the team to confirm current consultant availability, technology expertise, delivery model and the scope that can be supported.
Share your business challenge, current reporting environment and desired outcome. The initial discussion can help establish whether an assessment, advisory engagement or focused project is appropriate.
Please do not include passwords, sensitive personal data or confidential production data in this form.
We are an authorized implementation partner of Snowflake, Databricks, Amazon, Automation Anywhere, Denodo, DataDog, New Relic, and Elastic.