Business Intelligence - Built for Executive Decisions. Governed for Enterprise Scale

End-to-end BI – executive and operational dashboard development in Power BI and Tableau, semantic layer design and governance, self-service analytics programmes, embedded BI development, real-time operational reporting, BI migration from legacy platforms, DataOps and pipeline reliability engineering, and Power BI Centre of Excellence design. Delivered for Fortune 500 enterprises across manufacturing, financial services, healthcare, energy, and retail.

Power BI is our primary enterprise BI platform – including Power BI Service, Premium, Embedded, paginated reports, and mobile. We also deliver in Tableau, Looker, Qlik Sense, and MicroStrategy. Platform selection is driven by your existing infrastructure, licensing, and user base – not our preference. For most enterprise clients, Power BI delivers the strongest combination of governance capability, Microsoft ecosystem integration, and total cost of ownership.

A semantic layer is a governed business representation of your data – defining metric calculations, dimension hierarchies, and business rules in a single, maintained layer that every dashboard and report draws from. Without it, calculation logic is recreated independently in every report – producing conflicting numbers, inconsistent definitions, and the expensive whose data is right? debate that consumes leadership meeting time and erodes trust in BI. Every Kernshell BI engagement includes semantic layer design as a core deliverable, not an optional extra.

Self-service and governance are not mutually exclusive – they require the right architectural approach. We design certified datasets with enforced row-level security and validated semantic layers as the foundation for self-service. Business users build their own reports on these certified foundations – they access governed data with correct metric definitions, not raw tables they can mis-aggregate. Usage monitoring, workspace governance, and certification programmes maintain quality standards as self-service adoption scales across the organisation.

A focused BI engagement – executive dashboard suite on an existing data source – delivers production dashboards in 4–8 weeks. A full BI platform implementation – data warehouse, semantic layer, executive dashboards, self-service programme, and DataOps – is typically 12–20 weeks depending on source system complexity and reporting scope. A BI migration from a legacy platform – SSRS, Business Objects, Cognos, QlikView – typically adds 4–8 weeks depending on report volume. All timelines are defined with clear milestones following the requirements and data assessment phase.

Via Fivetran, Airbyte, custom API ingestion, or direct database replication – for SAP, Salesforce, Microsoft Dynamics, Oracle, and custom operational systems. Source system integration is mapped and validated during the data assessment phase, with connector reliability and data freshness monitored as part of ongoing DataOps operations. For operational BI requiring near-real-time data freshness, we implement streaming data pipelines with Kafka or Azure Event Hubs connecting source systems to live Power BI streaming datasets.

BI platforms built for AI readiness from day one – feature-store-compatible semantic layers, versioned data models supporting training dataset reproducibility, data quality controls catching issues before they enter ML pipelines, and cloud platform selection (Snowflake, Databricks, Azure Synapse) with native ML integration. The governed, documented data foundations that produce trustworthy BI are the same foundations that produce reliable ML training data – Kernshell builds both requirements into every BI platform engagement from the first architecture decision.