How do you handle security and governance during a Fabric migration, especially for regulated industries?

Security and governance are built into every phase of our Fabric engagements—not bolted on at the end. We start with a comprehensive assessment of your existing security posture, including Entra ID configuration, network isolation, and data classification. During migration, we implement Microsoft Purview governance from the outset—sensitivity labels, data classification, lineage tracking, and policy enforcement. Access controls are designed using RBAC, row-level security (RLS), and object-level security (OLS) mapped to your organizational roles. Workspace hierarchy and naming conventions are designed to enforce data domain boundaries. For regulated industries, we configure private endpoints, network isolation, and audit logging to meet compliance requirements before any production data moves.

What kind of ROI can we expect from consolidating onto Microsoft Fabric?

The ROI comes from multiple sources. Infrastructure cost savings are often the most immediate win. Beyond cost reduction, organizations typically see significant improvement in Power BI report render times through DirectLake optimization, dramatic reductions in operational complexity (from managing five or more separate Azure services to a single governed platform), and the ability to enable self-service analytics and production AI capabilities that were impossible on the fragmented estate. Our phased approach means you start seeing returns on high-value workloads early—not just at the end of a multi-year project.

We have hundreds of SSIS packages and Synapse stored procedures. How complex is the migration to Fabric?

This is the hardest part of any Fabric migration—and the part most firms underestimate. SSIS packages can't be lifted and shifted into Fabric. They require fundamental re-architecture from procedural ETL to ELT patterns using Fabric Pipelines, Dataflow Gen2, or Spark Notebooks. Each package needs to be assessed for complexity, dependencies, and the optimal Fabric-native replacement. Synapse dedicated SQL pool workloads require DDL refactoring (distribution keys, indexes, and workload management settings don't exist in Fabric Warehouse), data extraction via CETAS to staging, and T-SQL compatibility remediation. Azure Data Factory pipeline migrations need a feature-parity gap assessment since Fabric Data Factory differs from ADF in key ways—no SSIS Integration Runtime, different connection handling, and no datasets concept. Pythian has done this work across complex, multi-workload environments and understands where the hidden compatibility gaps live.

Is Microsoft Fabric mature enough for enterprise-scale production workloads?

Fabric has matured significantly since its general availability in November 2023. As of mid-2025, over 28,000 paying organizations use it, including 80 percent of the Fortune 500. Microsoft is treating Fabric as its flagship data and analytics platform with monthly feature updates, and is actively steering customers from legacy services—retiring Power BI Premium P-SKUs, feature-freezing Synapse dedicated SQL pools, and migrating ADF users toward Fabric Data Factory. That said, features still move between preview and GA, and capacity-based pricing requires careful management to avoid unexpected costs. This is exactly where Pythian adds value. We know where the sharp edges are—which features are production-ready, which need workarounds, and how to architect around current limitations. We've helped dozens of organizations take Fabric from prototype to production, and we design every implementation with the operational discipline to handle enterprise-scale workloads reliably.

Strategic AI Workshops: Fast Track AI Deployment

Build your AI strategy

Fast-track months of strategic conversation—accelerate AI adoption across your entire organization.

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Assess AI-readiness

Audit data quality, accessibility, and governance to ensure your infrastructure can provide the high-fidelity, labeled datasets necessary for training reliable AI models.

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Deploy into production

Deploy high-velocity, data-first AI solutions engineered for seamless scalability and sustained performance.

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Identify and prioritize AI use case

Filter vague ideas into a high-impact AI roadmap. Fast track AI discussions from months of internal meetings into a 3-day hyper-focused AI strategic workshop, defining and designing your AI implementation roadmap. Our c-suite level IT team (CAIO, CDO, CISO, CIO, CTO) ensure your AI strategy is grounded in technical feasibility and clear business outcomes from day one.

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Prepare your data foundation for AI success

Modernize messy, legacy data estates ensuring your AI and ML models are grounded in accurate, secure, and governed enterprise data.

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Shift from linear-human scale to exponential growth with automation.

Transform your core business workflows with industrialized intelligence. You can bridge the gap between AI and your existing ERP or CRM systems, turning your high-value manual processes into streamlined, automated engines of growth.

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Integrate AI to synchronize real-time intelligence with core operations and systems.

Transform isolated AI experiments into operational velocity by engineering the connective tissue between sophisticated machine learning and your core enterprise systems. Move beyond pilots to seamlessly embed intelligence into your existing workflows, ensuring every model drives measurable, real-world ROI across your entire tech stack.

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Transform AI prototypes into high-velocity enterprise assets.

Accelerate your transition from prototype to production. By embedding AI directly into your legacy environment, you transform isolated models into secure, high-velocity enterprise assets designed to deliver immediate, measurable impact on your bottom line.

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Proactive MLOps and AI model governance.

Production AI requires constant vigilance against model drift and complexity bias. We provide ongoing management to monitor performance, retrain models as data changes, and optimize token costs. Ensure AI solutions remain a high-performing asset that evolves with your business.

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Paul Lewis

CTO, Pythian

Karen Pfiefer

Field CAIO and CDO, Pythian

Ernest Solomon

Field CISO and CTO, Pythian

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Field CTO , Pythian

Tony Muraki-Hart

Field CTO, Pythian

AI Development Services

Build production-grade AI solutions that integrate directly into your enterprise stack, we transform your proprietary data into a high-velocity engine for operational growth.

AI Integration Services

Transform isolated AI experiments into operational velocity by engineering the connective tissue between sophisticated machine learning and your core enterprise systems.

AI Automation Services

Move beyond simple task-replacement to engineer autonomous, enterprise-grade systems that plan, reason, and execute multi-step processes within your existing systems.

Machine Learning Solutions

Engineer robust MLOps pipelines around your proprietary data to ensure your machine learning assets deliver consistent, measurable ROI in live production environments.

Agentic AI Solutions

Build agents to reason and interface directly with your ERP and CRM systems, turn linear manual workflows into high-velocity automated engines.

Generative AI Solutions

Automate your most knowledge-heavy workflows with secure, fact-grounded outputs leveraging Retrieval-Augmented Generation (RAG) and precision fine-tuning for accurate, high-integrity results directly within your existing enterprise ecosystem.

Frequently asked questions (FAQ) about AI workshops

The primary goal is to move your organization from AI curiosity to a concrete, high-impact roadmap. Unlike a general course, our workshops focus on identifying specific use cases within your unique workflows, prioritizing them by ROI and feasibility, and aligning your leadership team on a unified top-down strategy.

We measure success through three lenses:

Efficiency: Estimated reduction in manual task time (typically 30-50% in targeted areas).
Strategic Clarity: A finalized implementation roadmap with clear KPIs.
Upskilling: Pre- and post-workshop assessments of your team's ability to identify and manage AI opportunities.

Pythian's AI workshop is a strategic-session where we focus on the why and when before we jump into the technical know-how. While we discuss LLMs, agents, and data infrastructure, the conversation is designed for executives and department heads to make informed investment decisions.

For maximum impact, we recommend a cross-functional group including:

Leadership: CEOs, COOs, and Department Heads.
Technology: CTOs or IT Managers.
Operations: Product Managers and Lead Business Analysts.
Early Adopters: Internal "AI Champions" who will drive day-to-day adoption.

Absolutely. We offer industry-specific modules for all departments, IT, Finance, HR, Supply Chain, Marketing, Education, Transportation, Healthcare and more! Before the workshop, we conduct a discovery call to ensure we gain a deeper understanding of your business.

We offer three flexible formats:

The Intensive (1 Day): Rapid ideation and initial prioritization.
The Deep Dive (2-3 Days): Full roadmap development, including risk assessment and governance.
Virtual or On-site: Available globally via interactive digital whiteboarding or in-person sessions at your headquarters.

Security is a core pillar of our strategy. We dedicate a specific module to Responsible AI (RAI), covering:

Data residency and leakage prevention.
The difference between public and private LLM instances.
Compliance with evolving regulations like the AI Act and GDPR.

No. In fact, a key deliverable of the workshop is a Data Readiness Assessment. We help you identify what data you currently have, what is missing, and how to structure your data backbone to support the AI tools you want to deploy.

You won't be left with just a slide deck. Every workshop concludes with a 30-60-90 Day AI implementation and integration plan. This includes assigned responsibilities, workshop notes and summary, and the high-impact AI roadmap.

We include a section on change management. We help leaders frame AI as a capacity creator rather than a replacement tool, focusing on how it automates routine tasks to allow employees to focus on higher-value, creative work.

AI Workshops

Fast-track months of strategic conversations—clearly define your data and AI strategy.