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Modernize existing reporting (Excel, BusinessObjects, SSRS, Cognos, Tableau) to Power BI Premium: tabular models, dataflows, Premium capacities, unified governance, RLS, Microsoft Fabric integration.
Most large organizations inherit a fragmented decision heritage: hundreds of shared Excel reports, legacy BusinessObjects or Cognos files, SSRS reports pointing to the same sources with different calculation rules. The result: multiple versions of truth on the same indicators, long analysis delays because each business request triggers an investigation, technical debt that accumulates (orphan reports, broken sources, forgotten calculation rules). This fragmentation weighs on figure confidence and steering capability.
For Microsoft 365 organizations, Power BI Premium is today the natural target. Three reasons. First, the tabular model (in-memory VertiPaq engine) offers superior analytical performance compared to classic relational models. Second, DAX is a rich expression language, documented (DAX Patterns, SQLBI), and well-tooled. Third, native integration in Microsoft 365 (Excel Connect, Teams Live, SharePoint) shortens the distribution chain. See also the Cognos to Power BI and Pentaho to Power BI paths for specific cases.
Microsoft Fabric (announced in 2023) unifies Power BI, Data Factory, Synapse Data Engineering, and Real-Time Analytics into a single platform with OneLake as the common storage layer. For new ambitious Power BI migrations, Fabric is now the recommended target rather than Power BI Premium alone. Advantages: Direct Lake (zero data copy from the lakehouse), integrated Spark notebooks, Data Activator for real-time alerting. The Power BI migration can fit into a broader data program including a lakehouse — see the Data engineering pipelines path.
Rapports éclatés (Excel, BusinessObjects, Cognos, SSRS, Tableau, Qlik), modèles redondants
Power BI Premium, modèles tabulaires partagés, dataflows, Microsoft Fabric optionnel
Microsoft default choice. Dedicated Premium capacity, datasets shared across workspaces, centralized RLS, native Office integration. Main recommendation for the majority of migrations.
More ambitious program including a modern lakehouse, real-time ingestion, Spark notebooks. Relevant when the BI migration is part of a global data redesign, not just reporting replacement.
Multi-cloud organizations seeking to avoid reinforced Microsoft dependency. Tableau covers functionally but greater migration effort because model semantics differ.
Specific cases linked to existing data ecosystem: Looker for BigQuery / GCP, Qlik for organizations valuing the associative approach.
A Power BI migration program is typically structured over **6 to 18 months** depending on volume and complexity. For an estate of **100 to 300 reports** with 10-20 source models, plan **8 to 12 months** with a 4-6 person cell: Power BI data architect, senior DAX and tabular developer, two to three Power BI developers, business referent assigned at 30%, project manager. For larger estates (1000+ reports, OLAP cubes, multi-country), a multi-year program structured in functional waves is necessary with a cell reaching up to 10 people during peaks.
Migrating identically without cleaning the heritage. If the organization has 800 reports of which 600 are inactive or redundant, migrating everything reproduces the debt in Power BI.
Dedicated Discovery phase: inventory extraction via source platform APIs, classification of each report by execution frequency, business criticality, redundancy. Inactive reports are archived, duplicates merged. Migration scope focuses on the 20% of reports carrying 80% of the value — typically 30 to 50% scope reduction. See the ATLAS methodology.
Reproducing in DAX Excel or MDX calculations without optimizing. Historical workarounds become useless or even harmful in the VertiPaq tabular engine.
Targeted refactoring: each complex measure is analyzed and rebuilt in modern DAX with standard patterns (variables, CALCULATE, native time intelligence, automatic aggregations). Optimizations are recorded as platform adaptations in the discrepancy registry, distinct from strict business parity.
Neglecting row-level security (RLS). Legacy sources often manage security via application filters or database roles, which do not transpose as-is to Power BI RLS.
Dedicated security audit from scoping: extraction of existing security model, design of equivalent Power BI RLS model (dynamic RLS via USERPRINCIPALNAME, static roles, Object Level Security if necessary). Parity tests with representative user accounts before each production deployment.
Launching Power BI Premium without workspace governance. Without framework, users create workspaces and reports randomly, and Premium consumption explodes.
Power BI Premium governance from deployment: workspace structure (Bronze/Silver/Gold or by business domain), Power BI Admin Portal configured, audit logs activated, dedicated Premium capacities with FinOps. See also the Power Platform + Copilot path for global Microsoft governance.
Data analytics platform for a national telecom operator. Harmonization of figures between national business, regional units, and subcontractors. Industrialized Power BI and Google Cloud Platform pipelines.
Pentaho to Power BI decision migration for a North American public organization. Data model enrichment, refresh industrialization, access governance.
For 100 to 300 reports with 10-20 source models, plan 8 to 12 months with a 4-6 person cell in nearshore co-delivery. For very large estates (1000+ reports), a multi-year program structured in functional waves is necessary. Scope is typically reduced by 30-50% in Discovery phase by archiving inactive reports.
Power BI Premium is sufficient for most classic BI migrations. Microsoft Fabric is relevant when the program is part of a global data redesign (OneLake lakehouse, real-time ingestion, Spark notebooks, Real-Time Analytics). Our initial scoping evaluates this choice per your data strategy and roadmap.
Three steps. Extraction of existing security model (legacy sources, application filters, database roles). Design of equivalent Power BI RLS model (dynamic USERPRINCIPALNAME roles, static roles, Object Level Security). Parity tests with representative user accounts before each production deployment. No sensitive report deployed to production without explicit business security referent agreement.
For a 100-300 report estate in nearshore co-delivery, plan 400 to 800 k€ over 8-12 months, excluding Microsoft licenses. For larger estates (1000+ reports, multi-country, Microsoft Fabric), plan 800 k€ to 1.5 M€ over 12-18 months. See delivery models.
We frame the trajectory, the budget, and the deliverables in a first thirty-minute conversation. A short POC can be proposed before committing to the full program.
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