Most organizations are making decisions based on data they do not fully trust. Information is scattered across ERPs, CRMs, databases, spreadsheets, files, and disconnected systems — and teams spend hours reconciling inconsistent numbers, rebuilding manual reports, and trying to answer the same questions from different angles, often arriving at different results.

The Azure Data Platform Readiness Assessment by iNBest helps organizations evaluate the current state of their data environment and define a clear, practical architecture for building a modern analytics and AI-ready data platform on Azure and Microsoft Fabric. iNBest assesses your data sources, integration patterns, data quality, governance model, reporting environment, and organizational readiness — and delivers a prioritized roadmap for consolidating your data estate on a unified, scalable platform.

During the engagement, the iNBest team maps your data sources, reviews current pipelines and integration approaches, evaluates your Power BI environment and semantic model maturity, assesses data quality and ownership practices, identifies security and compliance gaps, and designs a target architecture using Azure services including Microsoft Fabric, OneLake, Azure SQL, Azure Data Lake Storage, Azure Databricks, and Microsoft Purview — based on your use cases and consumption profile.

WHAT IS INCLUDED:

Business and technical discovery workshop to identify data domains, analytics use cases, reporting priorities, and organizational pain points
Data source inventory: relational databases, file systems, cloud storage, APIs, SaaS platforms, ERP systems, CRM systems, and legacy data sources
Current state architecture documentation: pipelines, transformation logic, integration patterns, and end-to-end data flows
Power BI and reporting environment evaluation: workspace structure, semantic model design, dataset architecture, access patterns, refresh performance, and governance maturity
Data quality assessment by domain: completeness, consistency, accuracy, timeliness, and known data quality issues
Data ownership and stewardship evaluation: accountability model, classification practices, and data management culture
Security and access control review: row-level security implementation, workspace permissions, sensitivity labeling, and compliance posture
Microsoft Fabric and OneLake readiness evaluation: fit assessment, workspace and domain structure recommendations, and OneLake integration approach
Azure Databricks, Azure SQL, and Azure Data Lake Storage evaluation based on workload types, data volumes, and processing patterns
Microsoft Purview governance fit review: data cataloging, lineage tracking, data classification, and policy management
Target architecture design with recommended Azure and Fabric services, integration patterns, and data flow model
Azure consumption estimation for the recommended platform components
Use case prioritization by business impact and technical feasibility, including analytics, real-time processing, and AI readiness scenarios
Implementation roadmap by phase with effort estimates, dependencies, and quick win identification
Executive summary with key findings and data modernization recommendation

WHAT IS NOT INCLUDED:

This assessment does not include data platform implementation, pipeline development, semantic model construction, dashboard creation, data migration, or any configuration changes. Implementation and build services are available as a separate engagement with iNBest following assessment completion.

WHO THIS IS FOR:

This assessment is designed for data managers, BI directors, chief data officers, CIOs, finance directors, operations directors, and IT leaders in mid-market and enterprise organizations looking to consolidate fragmented data environments, modernize their analytics infrastructure, or build a reliable data foundation to support AI and advanced analytics. It is particularly relevant for organizations running Power BI without a governance model, teams generating recurring manual reports across disconnected systems, organizations evaluating Microsoft Fabric for their analytics workloads, and businesses that want to activate AI use cases but lack the data infrastructure to support them.

ASSESSMENT COVERAGE FOR QUALIFIED PROJECTS:

iNBest may provide partial or full coverage of the assessment cost — up to 100% — based on project size, technical scope, estimated consumption, and commercial evaluation. This coverage is provided directly by iNBest. It is not a Microsoft program credit, guaranteed discount, or funding commitment. Final coverage percentage, scope, and commercial terms are confirmed through a private proposal following eligibility validation. Contact us to validate whether your project qualifies.

This service is available in Spanish.

Azure Data Platform Readiness Assessment

iNBest

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