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By Elizabeth Wentworth  As a Microsoft Partner, Interloop had the privilege to host our first Fabric Analyst in a Day workshop this past quarter! Imagine consolidating all your data into a single source of truth and turning complexity into clarity—that’s exactly what this intermediate-level training delivered. Designed for Power BI Data Analysts with experience on Power BI but new to Microsoft Fabric, the session brought together professionals eager to explore Fabric’s powerful capabilities. Watching curiosity turn into confidence as participants built reports and unlocked insights was inspiring. This wasn’t just a training; it was a deep dive into how Microsoft Fabric can unify data, streamline workflows, and empower organizations to make smarter, faster decisions.  What is Microsoft Fabric and Why Does It Matter?  Microsoft Fabric is an end-to-end analytics platform designed to unify your data and analytics in one place. Instead of juggling multiple tools and disconnected data sources, Fabric brings everything together—data ingestion, transformation, storage, and visualization—into a single, integrated experience.  Key Features We Explored  During the workshop, we introduced participants to Shortcuts, Dataflows Gen2, and Pipelines, which make it easier to connect and transform data from various sources. These features allow analysts to streamline workflows and reduce complexity, ensuring data is always up-to-date and ready for analysis.  Power BI Integration  One of the most exciting aspects of Fabric is its seamless integration with Power BI. Fabric seamlessly integrates with Power BI, enabling analysts to build rich, interactive reports directly on top of lakehouses using Direct Lake mode for real-time analytics without manual refreshes. This combination accelerates decision-making and ensures insights are always current.  How Does the Workshop Work?  The Fabric Analyst in a Day workshop is designed to give data professionals a hands-on, guided experience with Microsoft Fabric—without overwhelming them with technical complexity. Rather than just listening to theory, attendees spend most of the day working through guided labs that simulate real-world scenarios. These labs walk participants through the entire analytics lifecycle—from connecting and ingesting data to transforming it and building interactive Power BI reports—all within Fabric’s integrated environment.  Why Labs Matter  The labs are where learning truly happens. They allow participants to explore Fabric’s features like Shortcuts, Dataflows Gen2, and Pipelines in a practical, step-by-step way. By the end of the day, attendees not only understand the concepts but have applied them, leaving with confidence in how Fabric can streamline workflows and deliver meaningful insights.    Lab Topics Covered:   Lab 1 – Power BI Desktop   Set up Power BI Desktop in a lab environment, analyze reports, and review Power Queries to understand data sources.  Lab 2 – Fabric Workspace   Create a Fabric workspace and build a Lakehouse for centralized data storage.  Lab 3 – Lakehouse Shortcuts   Connect to ADLS Gen2 using Shortcuts, create Visual Queries, and ingest data into a Lakehouse.  Lab 4 – Dataflows Gen2   Ingest data from multiple sources—SharePoint, Snowflake, and Dataverse—into a Lakehouse using Dataflows Gen2.  Lab 5 – Data Pipelines   Configure scheduled refreshes for Dataflows, create Data Pipelines, and automate refresh schedules for streamlined workflows.  Lab 6 – Data Engineering   Build SQL views and create semantic models to prepare data for reporting.  Lab 7 – Power BI Experience   Auto-generate reports, design custom reports from scratch, connect Power BI Desktop to semantic models, and experience Direct Lake mode for real-time data refresh.  Why Should Companies Care?  Data is the backbone of every modern business decision—but fragmented systems and manual processes slow down insights and increase risk. Microsoft Fabric changes that by creating a single, integrated analytics platform that unifies data and streamlines workflows. For companies, this means faster access to accurate information, improved collaboration, and the ability to make decisions with confidence.  The Value It Delivers  By adopting Fabric, organizations can:  Boost Efficiency: Reduce time spent managing multiple tools and data silos.  Improve Accuracy: Work from a single source of truth, minimizing errors and inconsistencies.  Accelerate Insights: Enable real-time reporting and analytics with Power BI integration.  Drive Impact: Turn raw data into actionable insights that support strategic goals.  Cost-Effective Learning: The Fabric Analyst in a Day workshop is completely free, making it an accessible way for teams to gain hands-on experience without budget constraints.  The Risk of Standing Still  Companies that delay modernizing their analytics stack risk falling behind competitors who are leveraging unified platforms for speed and agility. Manual processes and disconnected systems lead to inefficiencies, missed opportunities, and higher operational costs. Fabric offers a clear path forward—one that positions businesses to thrive in a data-driven world.  Why It’s Valuable  This workshop isn’t just about learning features—it’s about understanding how Fabric can solve real business challenges. By the end of the day, attendees see how Fabric simplifies analytics, reduces manual effort, and accelerates insights. It’s a practical, high-level introduction that leaves participants confident in the platform’s potential, while recognizing that expert guidance—like Interloop’s—makes implementation seamless and impactful.  Conclusion  The Fabric Analyst in a Day workshop was an exciting way to bring together a diverse group of talented professionals—Digital Leads, Solution Architects, Developers, Analysts, and Directors—all eager for hands-on learning with Fabric. Watching participants collaborate in the labs and explore how Microsoft Fabric can transform their analytics workflows was inspiring. It gave participants and facilitators the chance to dive deeper into Fabric and see firsthand how these tools solve real business challenges.     If your organization is looking to unify data and accelerate decision-making, Microsoft Fabric is a game-changer—and Interloop is here to help you make the most of it.  Next Steps  Want to join us for the next Fabric Analyst in a Day workshop? Check out our Events Page to stay updated on upcoming sessions and webinars—we’d love to see you there!    Have questions or want to explore how Fabric can fit into your organization ? Contact Interloop directly and let’s start the conversation!

In 2025, AI dominated headlines. But beneath the hype, something more important happened. Organizations stopped treating data and AI as experiments — and started treating them as infrastructure. Planning shifted from static exercises to living systems. Insight began to replace intuition. And the gap between companies testing AI and those operationalizing it widened. As this year comes to a close, at Interloop we’re already looking ahead. The best 2026 strategies won’t start with spreadsheets. They’ll lead with trusted data, contextual intelligence, and systems designed to adapt in real time. Here’s what 2025 revealed for us — and how forward-looking leaders should be thinking about what's to come. 2025: The Year Data Foundations Finally Got Real For years, organizations talked about becoming “data-driven.” In 2025, that conversation matured. Mid-market leaders stopped asking whether they needed better data foundations and started asking how quickly they could get to insight that actually supported decision-making. The problem wasn’t a lack of tools — it was fragmentation, latency, and inconsistency. In response, Interloop expanded its Data Foundation  and Fast Dash  offerings to help clients unify their data and deploy dashboards rapidly using Microsoft Fabric. The goal was simple: accelerate time-to-insight without sacrificing trust, governance, or clarity. This shift was on full display at Fabcon Las Vegas , Microsoft Fabric’s premier event. There, Interloop showcased real-world use cases demonstrating how modern data foundations and rapid dashboard deployment can move organizations from raw data to decision-ready insight faster than ever. The conversations weren’t theoretical — they were grounded in execution, scale, and business outcomes. 2025 made one thing clear: strong data foundations are no longer a prerequisite for innovation — they are the innovation. From Insight to Action: AI Enters the Planning Cycle As data foundations strengthened, the role of AI evolved. In 2025, AI began moving out of isolated analytics environments and into the workflows where decisions actually happen. Leaders weren’t looking for novelty — they were looking for relevance, speed, and context. That shift led Interloop to launch its Custom Copilot Kitted Offering : tailored AI copilots designed to integrate seamlessly into client workflows. These copilots weren’t built to replace human judgment, but to enhance it — automating routine analysis, surfacing insights at the moment of need, and delivering personalized intelligence at scale. At the same time, Interloop leaned into its role as Customer Zero , adopting Microsoft’s vision for Becoming Frontier early. By implementing emerging IQ innovations — including Work IQ, Fabric IQ, and Foundry IQ — Interloop embedded contextual intelligence, semantic data layers, and secure AI grounding directly into its own operations. Our takeaway from 2025? AI delivers value not when it’s impressive, but when it’s embedded. Becoming Frontier: What It Actually Takes The idea of becoming a “frontier firm” gained traction in 2025 — but the reality proved more nuanced than marketing headlines suggested. Frontier organizations aren’t defined by how many models they deploy or how quickly they adopt new tools. They’re defined by how effectively intelligence is grounded in trusted data, governed at scale, and aligned with business context. Through its work as Customer Zero and with clients across industries, Interloop saw firsthand that becoming frontier requires more than experimentation. It requires semantic layers that make data understandable, architectures that make lineage transparent, and AI systems that are secure, explainable, and actionable. It requires bringing people along — empowering teams to use data and AI for strategic planning, not just reporting. In 2025, Interloop focused on empowering others to become frontier firms, guiding clients to leverage their data and AI capabilities for competitive advantage and long-term resilience. Frontier isn’t a destination. It’s an operating model. Scaling What Works: Partnership as a Force Multiplier As demand for intelligent planning accelerated, so did the need for scale. In 2025, Interloop joined forces with Atlantic Tomorrow’s Office , strengthening its market presence and expanding its ability to deliver Data & AI services at scale. The partnership reinforced Interloop’s leadership in Microsoft-powered solutions while ensuring clients could access the depth, continuity, and operational support required for long-term success. This wasn’t about changing direction — it was about extending reach. The challenges organizations face in 2026 won’t be smaller than those of 2025. They’ll be more complex, more interconnected, and more dependent on intelligent systems that can grow with the business. Scale matters — not just in technology, but in execution. Looking Ahead to 2026: When Planning Becomes Predictive and Proactive If 2025 was the year organizations operationalized data and AI, 2026 will be the year planning becomes predictive and proactive. Forward-looking leaders are already rethinking how they forecast, allocate resources, and adapt to change. Predictive analytics are replacing static projections. Copilot-style tools are supporting real-time decision-making. Unified data models are turning annual planning cycles into continuous, responsive systems. In 2026, strategy won’t live in spreadsheets. It will live in platforms that connect insight to action — dynamically, securely, and at scale. The organizations that succeed won’t be those with the most data, but those with the clearest signal. Those that planned not just for growth, but for clarity, speed, and adaptability. The Bottom Line: Trust Moves Business Forward You don’t need more data dumps or dashboards — you need data you can count on. In 2025, organizations learned what it takes to operationalize data and AI. In 2026, that foundation becomes the engine for smarter, faster planning. When teams trust the numbers, decisions accelerate, strategies sharpen, and AI moves from buzzword to business engine. Interloop builds that confidence into the architecture — keeping every insight aligned and every decision on course. As planning evolves from static to predictive and proactive, trust remains the true north. Ready to chart your course in the new year? Get looped in today .

By Matt DeLeon  Microsoft Fabric is reshaping how organizations manage, analyze and activate data. Before Fabric, analytics projects relied on multiple tools across Azure Data Factory, Synapse, SQL engines and separate BI platforms. Each workload operated in isolation, adding complexity and slowing insights.   Fabric changes that by unifying data engineering, analytics and AI into one integrated environment. Whether you lead operations, manage pipelines or build dashboards, Fabric provides a centralized platform to turn raw data into meaningful action.  This guide walks through how to get started with Fabric based on your role, how to build hands-on experience and how to develop confidence as you progress.  What Makes Microsoft Fabric Different  Fabric brings together capabilities from Power BI, Azure Synapse Analytics, Azure Data Factory and new Data Engineering workloads in a single analytics platform. Instead of moving across fragmented systems, teams work within one environment designed for speed, collaboration and scale.  Here’s how the core components work together:  Data Factory  Provides a streamlined experience for ingesting, preparing and transforming data from a wide range of sources.  Synapse Analytics  Delivers SQL-based analytics with support for open data formats and native integration with OneLake.  Data Engineering  Offers Apache Spark, notebooks and orchestration tools for large-scale processing and advanced transformations.  Power BI  Connects directly to data stored in Fabric, allowing teams to build dashboards and share insights across the organization. Fabric also includes additional workloads that elevate analytics:  OneLake  Unified, organization-wide storage that functions much like OneDrive for data. It centralizes files, improves governance and simplifies collaboration.  Data Science  Integrates with Azure Machine Learning so teams can build, deploy and operationalize predictive models directly within Fabric. These models can be incorporated into BI reports or downstream processes.  Real-Time Intelligence  Provides no-code connectors, streaming ingestion, geospatial tools and automated actions so teams can monitor metrics and act on insights instantly.  Where to Start Your Fabric Learning Journey  Because Fabric spans multiple workloads, the best starting point depends on your role. A focused approach will help you ramp up quickly and effectively.  Sales Managers   Begin with Power BI for sales performance, customer segmentation and pipeline visibility.  Finance Teams   Explore the Data Warehouse for consistent reporting, audit-friendly structures and financial modeling.  Data Engineers   Start with Data Factory and Data Engineering to build pipelines, transformations and orchestration workflows.  Business Analysts   Spend time in Power BI and Real-Time Intelligence for dashboarding and streaming insights.  Data Scientists   Dive into the Data Science workload to train and deploy models across Fabric.  Operations Leaders   Use OneLake and shared workspaces to manage data assets, streamline collaboration and support decision-making.  Choosing a role-aligned starting point makes the learning curve more manageable and sets clear direction for developing your skills.  How to Get Started  Create a Sandbox Workspace   Set up a trial workspace in Microsoft Fabric to safely explore lakehouses, build pipelines and experiment without touching production environments.  Use Microsoft Learn Modules   Microsoft provides free, self-paced training for each workload. Begin with “ Get Started with Microsoft Fabric ,” part of the DP-600: Microsoft Fabric Analytics Engineer course. These modules offer guided exercises and foundational knowledge.   Join Workshops for Practical Experience   Workshops like Fabric Analyst in a Day (FAIAD)  provide hands-on, scenario-based training. Sessions hosted by partners such as Interloop give real-world context and accelerate learning.  Connect with the Community   Participate in Microsoft Fabric forums , user groups or online communities to learn best practices and see how other professionals approach solutions.  Explore Official Documentation   Microsoft’s documentation  is comprehensive and updated frequently. Use it to validate concepts, study patterns and troubleshoot challenges.  Start Small and Build Confidence   Begin with simple datasets or workflows, then expand to more complex projects as you gain comfort with the platform.  Stay Curious and Experiment   Fabric evolves quickly, especially with the continued integration of AI. Testing new features helps deepen understanding and reveals innovative approaches to solving problems.  Set Clear Goals   Define what you want to achieve—building a dashboard, automating pipelines or integrating machine learning. Clear goals help you stay focused and measure your progress.    The Future of Analytics with Fabric  Unified Data Reduces Complexity and Cost   Fabric consolidates data tools into one environment, reducing licensing, maintenance and governance overhead. Teams gain consistency, fewer silos and stronger compliance.  Integrated Analytics Drive Faster Decisions   With unified storage, built-in AI and real-time processing, teams can move from reactive reporting to operational insight. Decisions become faster and more proactive.    Why Choose Fabric Over Other Platforms  End-to-End Integration   Unlike Snowflake or Databricks, which require assembling separate tools for ingestion, transformation, warehousing and BI, Fabric unifies the full analytics lifecycle with OneLake as a single storage foundation.  Built-In Business Intelligence   Power BI is natively integrated, removing the need for a separate BI layer and accelerating adoption for both technical and business teams.     AI Everywhere   Copilot is embedded across workloads, expanding access to predictive analytics and natural-language reporting without complex setup.  Enterprise-Grade Security   Fabric integrates with Microsoft Purview and Microsoft 365 security services, making governance and compliance more seamless for regulated industries.    Ready to activate your data?  Analytics is shifting from fragmented systems to unified platforms. Organizations adopting Fabric now will accelerate their ability to plan, automate and innovate in 2026 and beyond. Experimentation, hands-on learning and a role-aligned approach are the fastest ways to build confidence on the platform.  Get started with Interloop  — and see how we can help you connect Fabric, Fivetran and your customer tools for seamless, scalable impact.

Key Announcements: AI Innovations and IQ Platform Transformations  A Look Back at Microsoft Ignite 2025: The Era of AI and the IQ Suite  The energy from Microsoft Ignite 2025 continues to reverberate throughout the tech world. This year’s event was marked by a host of groundbreaking announcements, especially for those passionate about artificial intelligence, data platforms, and the evolving ways Microsoft empowers organizations to achieve more. Interloop was fortunate to be in attendance for this amazing event, and we didn’t want to keep our findings to ourselves. Below is a recap of what we have found as the most influential news for Microsoft users, with a special focus on the new IQ suite—including Fabric IQ, Work IQ, and Foundry IQ. Let’s dive into how these innovations are reshaping the future of productivity and analytics.  AI Everywhere: Smarter Workflows and Experiences  Microsoft reaffirmed its commitment to embedding AI in every aspect of the workplace. Keynotes showcased major advancements in Copilot, which is now more deeply woven into Microsoft 365, Teams, and Dynamics 365. These updates allow users to automate repetitive tasks, generate content, and extract richer insights from their data. With more sophisticated natural language capabilities and heightened context awareness, Copilot is positioned to become an essential tool for businesses of all sizes.  Introducing the IQ Suite: Intelligent Solutions for Every User  Among the most highly anticipated announcements was the debut of the comprehensive “IQ” suite. Microsoft IQ delivers a new layer of intelligence to its cloud and productivity platforms, offering predictive analytics, proactive recommendations, and dynamic automation integrated into daily workflows. The suite now features three flagship offerings: Fabric IQ, Work IQ, and Foundry IQ.  Fabric IQ : Microsoft’s latest evolution in unified analytics, Fabric IQ introduces AI-powered data integration, analysis, and visualization tools that seamlessly bridge data silos and accelerate business intelligence. Users can ask natural language questions and receive instant, actionable reports, all within a secure governance framework.   Work IQ : Work IQ is designed to elevate workplace productivity by using AI to optimize workflows, streamline collaboration, and personalize work experiences. Through smart automation and context-aware insights, Work IQ helps individuals and teams work more efficiently and make better decisions.  Foundry IQ : Foundry IQ brings intelligent automation and advanced analytics to manufacturing, supply chain, and industrial operations. By leveraging real-time data and AI-driven recommendations, Foundry IQ empowers organizations to innovate faster, increase operational agility, and drive transformative outcomes.  Democratizing Data and Decision-Making  Fabric IQ, Work IQ, and Foundry IQ collectively stand out by making advanced analytics and intelligent automation accessible to everyone—from data engineers and business analysts to frontline employees and industry specialists. These offerings are tightly integrated into Microsoft Teams, Power Platform, Azure, and other Microsoft services, democratizing data-driven decision-making across organizations and industries.  What’s Next for Microsoft Users?  Microsoft Ignite 2025 underscored the company’s dedication to putting AI-powered tools in the hands of every user. With the expanded IQ suite, including Fabric IQ, Work IQ, and Foundry IQ, Microsoft is making it easier than ever to access advanced analytics, automation, and actionable insights. As these new features roll out, expect smarter collaboration, more intuitive digital experiences, and a quicker journey from raw data to informed decisions.  Interloop is excited to be on the cutting edge of Fabric and helping organizations to realize the value that these additional IQ offerings are helping to support.  Stay tuned for continued updates as these innovations and how to make the most of your Microsoft Fabric and these IQ offerings by tuning into our monthly newsletters.

In 2025, AI may drive the headlines — but trust drives the results. For mid-market leaders, confidence in data is now the line between progress and paralysis. The Data Confidence Gap Is Growing Data is everywhere. Confidence in it? Not so much. In an era where business leaders are expected to back every move with data, trust in that data is eroding. According to Salesforce’s March 2025 Trust in Business Data Leaders Survey , fewer than half of U.S. executives say their data strategies align with business priorities — a drop of 14 percentage points from 2023. This disconnect isn’t just frustrating — it’s expensive. Bad data now costs U.S. companies more than $3 trillion annually . And the impact isn’t limited to dashboards: data-related trust gaps are directly slowing down digital transformation, AI initiatives, and cross-functional alignment. When leaders don’t trust their data, they delay action — or, even worse, act on assumptions. Why Mid-Market Teams Feel It More Mid-sized organizations face a unique challenge. They have enterprise-level complexity, but often without enterprise-level infrastructure or data teams. The result? A patchwork of systems, spreadsheets, and self-serve analytics that frequently operate on slightly different truths. The average mid-market company now runs nearly 900 cloud applications but integrates only 29% of them . It’s no wonder nearly half of mid-market CFOs say poor data integration is blocking timely, critical decisions. Trusted data isn’t just a tech-team problem — it’s the foundation every AI initiative depends on. It’s a confidence accelerator that spans the entire organization and determines whether insights actually turn into impact. What Makes Data Trusted? Trust doesn’t come from volume or visualization. It comes from consistency, clarity, and context — regardless of who’s asking the question. To earn confidence from decision-makers, data must be: Reliable:  Clean, complete, and accurate Governed:  Defined the same across systems and teams Traceable:  Easy to audit, explain, and reverse-engineer Accessible:  Available to the right people at the right time Integrated:  Not stuck in siloed apps or shadow spreadsheets In short, trusted data is data that people don’t need to second-guess. AI Is Only as Trustworthy as Its Data AI has become a boardroom priority — but too often, it’s launched without a stable foundation. In 2025, a whopping 95% of organizations report little to no measurable business return on their generative-AI investments ( MIT Media Lab / Campus Technology ). And according to Salesforce’s Your Data, Your AI  study, more than half of professionals don’t fully trust the data powering their company’s AI tools. Trusted data, on the other hand, turns AI from risky to ready: Predictive insights become believable Generative tools get smarter — and more explainable Self-service analytics (like Microsoft Fabric’s Copilot tools) deliver the same answer every time — regardless of who’s asking The message is clear: trust is the real unlock for AI adoption. Microsoft Fabric: Unifying Data for Trust at Scale Enter Microsoft Fabric  — a platform built from the ground up to unify your data stack. Fabric consolidates data engineering, transformation, warehousing, and analytics into one seamless experience. That means less duplication, fewer silos, and more transparency into where your numbers come from and how they were calculated. With OneLake , built-in lineage views, and centralized security, Fabric helps teams: Align on a single source of truth Trace metrics from dashboard to data source Streamline governance without slowing down access Microsoft Fabric isn’t just unifying your data stack — it’s redefining how trust scales. With OneLake and Copilot integrations, Fabric creates traceable, explainable systems that keep AI and analytics aligned with how teams think and make decisions. For mid-market organizations, it’s a chance to modernize without rebuilding from scratch. 🔗 Explore Interloop’s Microsoft Fabric Overview Interloop’s Role: The Bridge, Not the Bottleneck Many organizations think of trust-building as a compliance task. Interloop takes a different approach in that we design data systems that earn trust through architecture — not red tape. Our mission is simple: help mid-market teams activate data they can trust and AI they can scale. That means helping clients: Connect tools like Fivetran to automate clean, consistent ingestion Implement Microsoft Fabric to unify reporting and metrics Build integrated pipelines that surface trusted, explainable insights — not just data dumps Because Interloop is both technical and strategic, we serve as a bridge between systems and stakeholders, aligning IT, ops, and leadership around the same metrics and definitions. 🔗   See how we go from file drop to business action in 60 seconds Trusted Data in Action According to Gartner’s 2025 Future of Data & Analytics brief, organizations that establish clear data-trust frameworks are twice as likely to outperform peers in revenue growth and operational efficiency.  The takeaway is simple: trusted data drives better business performance. Interloop clients have seen similar measurable gains after adopting Microsoft Fabric — from cutting report latency from days to hours to strengthening visibility and consistency across key business metrics. Fabric’s built-in lineage tools help teams trace data in minutes instead of days, turning once-siloed information into shared understanding. Trusted data isn’t flashy — it’s foundational. How to Start Building Trust If your team is second-guessing data — or not using it at all — start here: Audit your core KPIs.  Are they defined and calculated the same way across tools? Check your lineage.   Can your analysts explain where your most-used metrics come from? Connect your systems.  Integrate critical data sources (CRM, ERP, finance) into a unified platform. Decide what “trust” means.  Set measurable goals for data availability, accuracy, and access. Bring in the right partner.  Choose a consultancy that can bridge strategy, systems, and team needs — not just implement tooling. The Bottom Line: Trust Moves Business Forward You don’t need more data dumps or dashboards — you need data you can count on. When your teams trust the numbers, decisions get faster, strategies get sharper, and AI turns from buzzword to business engine. Interloop builds that kind of confidence into your architecture — keeping every insight aligned and every decision on course. Ready to activate your data? Start with Interloop — and see how we can help you connect Fabric, Fivetran, and your customer tools for seamless, scalable impact. Get looped in today .

Microsoft Fabric is redefining analytics — here’s how to make it work for you.  Artificial intelligence has dominated boardroom agendas for two years running. Yet beneath the headlines and hype, a more sobering reality is emerging: according to BCG’s 2025 research , only about 5% of organizations are deriving measurable value from AI investments.  The problem isn’t ambition — it’s activation.  Most companies still wrestle with fragmented data systems, inconsistent reporting, and disconnected analytics that stall decision-making. For mid-market teams balancing growth and efficiency, that fragmentation can feel like trying to plan a moon landing with half the controls missing.  Enter Microsoft Fabric , an end-to-end platform designed to unify data engineering, analytics and AI under one roof. But adopting Fabric isn’t just a tech upgrade. It’s a strategic shift in how mid-market organizations prepare, plan and perform.  At Interloop, we see Fabric as the bridge between today’s complexity and tomorrow’s clarity. Here’s how leaders can navigate this new frontier — and why unification is the real unlock for AI success in 2026.  1. Before You Build, Benchmark  Most mid-market organizations already have pockets of excellence: Power BI dashboards here, a cloud data warehouse there, maybe a few AI pilots sprinkled in. What’s missing is the connective tissue — a unified foundation that keeps insight flowing instead of getting trapped in silos.  Start by mapping your current landscape.  Where does your data live? How many tools handle ingestion, transformation and reporting? How often do those systems sync and how often do they argue?  Fabric thrives on clarity. By consolidating ingestion, storage and analytics into OneLake , the platform eliminates costly duplication and latency. But readiness isn’t only about systems. It’s about culture, sponsorship and alignment.  Leaders should evaluate three dimensions before lift-off:  Data:  Are inputs consistent, governed and reliable?  Analytics:  Do teams share a single version of the truth?  Activation:  Can insights translate to measurable action?  Organizations that achieve alignment across all three see productivity gains of up to 25% annually. The rest spend that time reconciling conflicting numbers in spreadsheets.  🔗  Need a high-level primer?   Microsoft Fabric Overview     2. Plan, Prove and Propel  The journey to Fabric shouldn’t begin with a wholesale migration. It should start with a controlled plan  that proves value fast.  Choose one high-impact domain: finance forecasting, operations or customer analytics. Move that workload into Fabric and measure what changes. Most organizations find reporting latency drops, collaboration improves and costs become more predictable thanks to Fabric’s consumption-based model.  Next comes foundation building.  This is where OneLake’s unification shines — every dataset, model and pipeline lives in one environment. It’s the difference between managing multiple dashboards and navigating from a single mission control.  Automation also plays a key role. Fabric can orchestrate data movement from intake to insight with minimal manual effort. As one Interloop client put it, “What used to take a day of hand-offs now takes a minute.”   🔗  From File Drop to Business Action in 60 Seconds  shows that speed in action.  Govern Lightly — Not Loosely  Governance is often where momentum dies. Too much red tape and innovation stalls; too little and chaos reigns. The goal is balance — guardrails, not roadblocks.   Establish clear ownership: who builds, who publishes, who audits. Use Fabric’s built-in lineage and permissions tools to track data movement without creating bottlenecks. Governance should enable trust, not fear.  🔗 For a deeper dive into empowering safe self-service, see How Data Agents Unlock Trusted Self-Service at Scale .  Create a Center of Excellence  Even the best technology falters without people leading adoption. A Center of Excellence (CoE)  ensures continuity, training and accountability.  According to McKinsey, transformation initiatives with executive sponsorship are 3x more likely to succeed . The CoE formalizes that sponsorship, turning early wins into repeatable processes across departments.    3. From Unified Data to Unified Decisions  Once your data foundation is steady, the real payoff begins — turning insight into action.  Fabric brings real-time analytics to the mid-market. Dashboards refresh in seconds, not hours. Teams can monitor sales trends, manufacturing performance or customer behavior and react in the moment, not after the quarter closes.  AI amplifies that impact. Predictive models can surface churn risks before they hit the bottom line or forecast demand to inform smarter inventory decisions.  The key is activation , embedding AI and analytics into daily workflows, not side projects. Unified data shortens the distance between question and answer.  PWC research   shows organizations with unified data see up to 10× higher ROI  on AI initiatives than those still operating in silos.  🔗 Explore Fabric’s AI capabilities in Built-In AI, Real-World Potential .   Planning for 2026  Looking ahead, unified analytics will shape how companies plan. Scenario modeling and “what-if” simulations, powered by connected data, allow leaders to test strategies before committing budgets. It’s the closest thing to business time travel — and it starts with clean, connected information.  4. Stay the Course  Digital transformation rarely fails because of technology. It fails because organizations lose alignment midway.  In that same McKinsey study , the findings tell a familiar story — about 70% of large-scale transformations still fall short , most often from weak planning or cultural resistance. Fabric adoption is no exception.  Common pitfalls include:  Over-governing:  slowing adoption with excessive control  Cost sprawl:  neglecting consumption monitoring  Change fatigue:  underestimating the human side of transformation  AI overreach:  chasing headlines instead of business outcomes  The antidote is steady navigation. Start with clear metrics, celebrate small wins and communicate progress often.  As we remind clients, AI is the amplifier — Fabric is the foundation.  One without the other won’t get you to orbit.  Your Next Orbit  The leaders who will thrive in 2026 aren’t the ones who adopted AI fastest — they’re the ones who built the infrastructure to make it work.  Unified analytics through Microsoft Fabric transforms data from an operational burden into a strategic asset. It lets teams see the whole picture, act with confidence and plan with precision.  At Interloop, we help organizations bridge strategy and execution — from Fabric architecture and migration to enablement and AI activation. We help your teams build the frameworks that keep insights trustworthy and scalable.  Ready to activate your data?  Get started with Interloop  and see how we can help you connect Fabric, Fivetran  and your customer tools for seamless, scalable impact.

By Mclain Reese Microsoft Fabric   is a powerful analytics platform — but it isn’t built to handle every data integration need. When it comes to reverse ETL (Extract, Transform, Load) and connecting to the wide range of tools that marketing and sales teams rely on, Fabric needs a wingman.   That’s where   Fivetran   — and its newly acquired   Census   technology — comes in. Together, they make it possible to turn data stored in Fabric into actionable insights that drive personalization, automation, and growth.  What It Means  Fabric excels at analytics and warehousing. Fivetran’s reverse ETL capabilities excel at connectivity. Many organizations have valuable customer and product data siloed in systems outside their engagement stack — CRMs, CMSs, or marketing automation platforms.   Fabric alone can’t close those gaps, but Fivetran’s reverse ETL functions bridge the divide, syncing curated data from Fabric directly into customer engagement tools.  This enables high-value use cases like dynamic segmentation, lifecycle marketing, and hyper-personalized campaigns — all powered by a single, trusted data source.  How It Works  Here’s how Fabric and Fivetran’s reverse ETL capabilities work together in a typical workflow:  Extract siloed data   — Pull customer, product, support, and sales data from multiple systems into Fabric.  Transform in Fabric  — Use Fabric’s notebooks and transformation tools to clean, join, and enrich the data — preparing it for your engagement tool’s schema.  Sync with Fivetran  — Connect Fabric’s curated tables to your CRM or marketing automation platform, mapping fields that populate key data points for Sales Sequences and Marketing Emails.  Activate in the customer engagement tool  — With enriched, up-to-date data, teams can build dynamic user segments and launch targeted campaigns that meet customers where they are.  Why It Matters  Fabric alone can’t connect directly to many popular business tools — a limitation that can stall activation. Fivetran fills this gap with its broad connector library , empowering marketing and sales teams to use all available data for smarter segmentation, campaign automation, and better engagement.  By using events and attributes sourced from Fabric, organizations can send personalized messages and recommendations at every stage of the buyer’s journey — turning static analytics into real-time action.  Example: Turning Manual Workflows into Automated Wins  A client recently used this approach to unify customer data stored across multiple systems outside of  HubSpot . By extracting it into Fabric, transforming it to match HubSpot’s schema, and syncing via Fivetran, they automated what had been a manual, error-prone process.  The result — cleaner data, faster execution, and personalized email campaigns that drove measurable engagement and conversion gains. What once took hours of spreadsheet manipulation and manual imports now happens automatically — freeing teams to focus on strategy instead of data wrangling.  Closing Thoughts  Microsoft Fabric is redefining how teams analyze data — but when paired with Fivetran’s reverse ETL, it also redefines how they activate  it. The combination bridges the last mile of data integration, helping organizations unlock siloed insights, enrich their CRMs, and deliver personalized experiences at scale.  Ready to activate your data?   Get started with Interloop   — and learn how we can help you connect Fabric, Fivetran, and your customer tools for seamless, scalable impact.

By Ralph Jaquez  About the Series   Microsoft Fa bric Functions is  Interloo p’s deep dive into the features that make Fabric not just powerful, but practical. We’re cutting through the noise to show how these tools drive real business results. Whether you're leading strategy or scaling systems, this series is built to help you turn complexity into clarity – and manual tasks into momentum.   Not Just a Translator — A Game Changer for Self-Service  There’s been a lot of buzz lately around Fabric Data Agents  — and for good reason. If you’ve read the Microsoft docs, you already know the core pitch: ask questions in plain English, get answers from your data without writing SQL, DAX, or KQL.  But the real value of a Data Agent isn’t just in translating language. It’s in how it changes the way people access and trust data  — especially for teams that have long been stuck behind bottlenecks.  Why You’d Actually Use One  Let’s walk through a (fictional but familiar) example: PalmettoEV , a growing electric scooter and small EV rental company operating in cities across the U.S. and Europe.  PalmettoEV’s data lives in multiple systems:  App usage in Firebase  Kiosk activity in SQL Server  Loyalty data in MySQL  Vehicle telemetry in BigQuery  All of it has been harmonized in Microsoft Fabric so the team can analyze trips, vehicles, customers, and payments in one place.  Before Data Agents, a simple question like “How many unique riders did we have in Barcelona last month?”  meant:  Submitting a request to the data team  Waiting for someone to write and validate a query  Going back and forth when definitions didn’t match  With a properly configured Fabric Data Agent , that same question can be asked in natural language — and answered instantly.  Why? Because the Data Agent already knows:  Which tables to query  How the business defines a “rider”  What counts as “Barcelona”  Who is allowed to access what  Where It Shines for Teams Like PalmettoEV  Think of the Data Agent as a domain-specific concierge for your data.  It allows users to ask targeted, business-relevant questions like:  “Which scooters had repeated downtime last week in Madrid?”   “List riders who booked more than three trips in Paris this month.”   “Show daily revenue in Austin for the last 30 days.”   Each of these works — and delivers trusted answers — because the agent is built on a clean, business-aligned model.  The Real Magic: Your Data Model  Here’s the hidden truth behind every successful Data Agent: the magic isn’t in the AI — it’s in the model.   For PalmettoEV, that meant doing the foundational work:  Harmonizing vehicle IDs across systems to track downtime  Defining a “trip” in one consistent, business-accepted way  Linking customers, trips, and payments with clean, trusted relationships  When the underlying model is strong, the agent becomes a reliable tool — not a novelty. Everyone gets the same answer to “What’s our average trip duration per city?”  — and it’s the right one.  When the model is weak or inconsistent? You get vague results, mismatched metrics, and frustration. That’s when trust erodes, and teams revert back to manual queries (or give up altogether).  Why This Matters for Mid-Market Leaders  Fabric Data Agents make it possible to scale trusted, self-service access to data — without overburdening your data team or compromising on accuracy.  But here’s the catch: self-service only works when the answers are right.   That’s why the real win isn’t just spinning up a Data Agent — it’s investing in the modeling work that makes it useful:  Aligning terms across teams  Cleaning up relationships  Standardizing definitions  Harmonizing across platforms  Done right, you get a tool that meets users where they are — and gives them answers they can act on.  This Is Where We Come In  At Interloop, we specialize in building harmonized, business-friendly models that make tools like Fabric Data Agents shine — whether your data lives across ERPs, CRMs, telemetry feeds, or a mix of cloud and on-prem systems.  Our goal is simple: make sure when your users ask a question, they get an answer they can trust.   Final Word  Fabric Data Agents aren’t a shortcut around modeling — they’re the best reason to double down on it.  If you want analytics your team can actually use (and trust), this is a powerful tool worth exploring. But like most things in data, it works best when the foundation is solid.  Let’s make sure it is.  Curious whether your data model is ready for a Fabric Data Agent?   Let’s get you there.   Get looped in today.

By Luisa Torres   About the Series   Microsoft Fabric Functions is Interloop’s deep dive into the features that make Fabric not just powerful, but practical. We’re cutting through the noise to show how these tools drive real business results. Whether you're leading strategy or scaling systems, this series is built to help you turn complexity into clarity – and manual tasks into momentum.   The Promise of Built-In AI (Without the Buzzwords)  AI is everywhere — but where does it actually add value for your business?  With Microsoft Fabric’s built-in AI Functions, the potential is right at your fingertips. No complex setup, no training models, no separate infrastructure. Just smart, simple capabilities that live inside the tools you already use — ready to help you work faster, smarter, and more consistently.  These functions are especially useful for text-heavy tasks: summarizing survey results, tagging customer feedback, extracting data from messy notes, translating content for global teams, and more.  The best part? You don’t need a data science team to use them.  What You Need to Get Started  If your organization is already using Microsoft Fabric, you're nearly there. Here’s what’s required:  A Fabric workspace (F2 or P SKU license)  AI Functions enabled in your environment  Optional: your own Azure OpenAI resource (for additional customization or during trial periods)  No servers. No outside APIs. No training loops. Microsoft handles the heavy lifting — so your team can focus on applying the insights.  What These AI Functions Actually Do  Fabric currently includes eight AI Functions designed to streamline and elevate how your team works with unstructured text. Here's a look at what’s available today — and why it matters.  Text Similarity   Quickly compare two pieces of text to assess how closely they align in meaning. Useful for matching customer complaints to known issues or grouping support tickets by theme.  Text Classification   Automatically tag or categorize incoming messages, forms, or documents. For example, sort customer feedback into categories like billing, tech support, or feature request — without manual review.  Sentiment Analysis   Gauge emotional tone across surveys, product reviews, or emails. Get a clear pulse on how customers or employees are feeling at scale.  Information Extraction   Pull specific details — like names, dates, locations, or product codes — from large batches of text. A fast track to turning unstructured text into structured, usable data.  Grammar and Spell Correction   Clean up typos, fix punctuation, and apply professional polish to rough input. Great for internal reports, customer comms, and audit readiness.  Summarization   Shorten long reports, meeting notes, or customer feedback into digestible highlights — without losing the important stuff.  Translation   Instantly translate content between languages. Ideal for global businesses managing multi-market communications.  Response Generation   Draft helpful, on-brand replies to common customer questions or internal prompts. Think of it as a built-in assist for everyday messaging needs.  Each of these tools can be used directly within your Fabric workflows — often as easily as applying a formula in Excel.  Why It Matters for Mid-Market Businesses  These AI Functions aren’t about replacing people — they’re about freeing them up to focus on higher-value work.  Save time   AI can scan, sort, and summarize in seconds — leaving your team with more time for strategy, interpretation, and action.  Improve decision-making   When sentiment analysis or pattern detection is applied early, teams spot trends faster — and react sooner.  Scale operations without scaling headcount   Whether you’re managing 100 survey responses or 100,000, AI applies the same logic, instantly and consistently.  Ensure consistency and quality   These functions help eliminate manual variability and reduce the risk of human error — great for audits, reporting, and customer trust.    Start Small, Think Big  You don’t need to be an AI expert to start seeing results.  Apply a function to your next customer feedback export. Use summarization on a long report. Try translation on your international reviews. Small use cases build trust and open the door to larger automation and insights efforts.  And if you’re not sure where to begin — we’re here to help.  Fabric AI Functions are currently in public preview. As with any AI tool, always review output before taking action.  Curious where Fabric AI Functions could make a difference in your business?   Let’s explore it together.  Get looped in today.

By Mclain Reese   About the Series:   Microsoft Fabric Functions is Interloop’s deep dive into the features that make Fabric not just powerful, but practical. We’re cutting through the noise to show how these tools drive real business results. Whether you're leading strategy or scaling systems, this series is built to help you turn complexity into clarity – and manual tasks into momentum.   Rethinking File-Based Processing  Event Streams are Microsoft Fabric’s solution for real-time data detection and intelligent automation. While often associated with IoT sensors or clickstream activity, their value goes far beyond that. For organizations managing files day in and day out — spreadsheets, exports, inventory reports — Event Streams offer a faster, smarter way to work.  They allow you to detect when a file hits a storage location, evaluate its content or naming convention, and trigger an automated workflow within seconds. No polling, no batch jobs, no delays.  The File Bottleneck You’re Probably Living With  Every business handles file-based data. Daily sales reports from POS systems. Customer lists exported from CRMs. Payout summaries from processors. Inventory files passed between warehouses. It’s all part of the operational hum — and for many teams, it’s also a manual headache.  We’ve seen this story before:  Analysts refreshing folders, waiting on file drops.  Batch jobs running on fixed schedules — whether the data’s there or not.  Processing delayed by time zones, weekends, or simple oversight.  Human error sneaking into spreadsheets and cascading into campaigns.  Manual handling isn’t just inefficient. It introduces risk — of missed revenue, broken trust, and wasted effort.  A Real Example: How a Bank Automated the Pain Away   One of our clients, a national banking institution, came to us with a common challenge. Their marketing team needed regular exports from Salesforce — files delivered by dealership clients — to power their targeted outreach campaigns. But their internal process was slowing them down.  Here’s what that looked like:   A full analyst day, every other week, just to prep the data.  Messy Excel workflows full of VLOOKUPs and room for error.  Campaign delays when files arrived late.  Risk of emails going to the wrong people — or not going out at all.  This wasn’t just a workflow problem — it was a credibility issue.  What We Implemented: Fast, Smart, and Fully Automated  By introducing Event Streams and Data Activator Reflexes, we gave them a system that reacts in real time and operates with business logic baked in.  Now, when a Salesforce export file lands in their ADLS Gen2 folder:  The Event Stream detects it instantly.  A Data Activator Reflex checks that it meets the right criteria.  The appropriate workflow is triggered within 60 seconds.  Built-in validations clean and standardize the data.  Final outputs are pushed directly into their marketing system — ready to go.    The Payoff: Tangible Business Wins  Saved time:  They reclaimed over 8 analyst hours a month — hours now spent on strategy, not spreadsheets.  Reduced risk:  No more human error in targeting or processing. Every campaign hits the right audience.  Better performance:   Campaigns launch on time. Client relationships stay intact. The system scales effortlessly as volume grows.  Event Streams didn’t just make things faster — they made them smarter and safer.  Why This Matters for Mid-Market Leaders  1. You get immediate business responsiveness.   Event Streams eliminate the lag between file arrival and business action. Whether a file drops at 3 p.m. or 3 a.m., processing begins right away. This keeps you on pace with global partners, campaign schedules, and operational SLAs.  2. You gain intelligent, built-in business logic.  With Reflexes, you can route files based on name, type, or even content. Set conditions. Apply logic. Automate decisions that used to live in someone’s head — or worse, in a clunky spreadsheet macro.  3. You connect directly into the systems that matter.  Need to trigger a pipeline? Write to a Lakehouse? Send data to your CRM? Event Streams play well with the entire Fabric ecosystem, giving you full control from intake to output.  So, When Do Event Streams Make Sense?  If your team regularly handles files that arrive on unpredictable schedules, vary by format or business function, or tie into critical downstream systems — Event Streams are for you. They’re especially valuable when timeliness and accuracy are non-negotiable.  They may be overkill, however, for ultra-simple workflows with consistent delivery and no branching logic. But if your operations are scaling or your file processes are getting more complex, they’re a smart, future-ready investment.  Making the Case Internally  To start small but smart, identify one manual workflow that happens often:  Estimate how many hours your team spends on it monthly.  Add up the risk or cost of error.  Pilot an Event Stream flow on that one scenario.  From there, it’s easier to identify and prove ROI — then scale it up.  Final Word  Event Streams turn file chaos into clarity. They remove the guesswork, cut the delay, and protect your most valuable resources: time, trust, and talent.  For our banking client, that meant cleaner data, faster campaigns, and happier clients. For you, it might mean freeing up a bottleneck that’s been quietly costing more than you realized.  This post is part of our Microsoft Fabric Functions Series. Stay tuned for our next breakdown: taking your data to the next level with AI functions.  Have file-processing friction or automation questions? Let’s solve them.  Get looped in today .