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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.

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A place to store the data accumulated from a wide range of heterogeneous Sources, generally used for data analysis and reporting. For example, Microsoft Azure, Amazon Redshift, Google BigQuery or Snowflake. Interloop has both Data Lake & Data Warehouse capabilities baked in. Warehouse A place to store the data accumulated from a wide range of heterogeneous Sources, generally used for data analysis and reporting. For example, Microsoft Azure, Amazon Redshift, Google BigQuery or Snowflake. Interloop has both Data Lake & Data Warehouse capabilities baked in. Ready To Get Started? You're one small step from starting your data-driven journey. LOOP ME IN

DATA SHEET Who Is Interloop DATA SHEET Get To Know Us Get To Know Us Get To Know Us Get To Know Us Interloop is a dynamic team of data engineers, data analysts, data scientists, and delivery experts dedicated to transforming how organizations leverage their data. With years of experience delivering data-backed solutions, we’ve honed our skills and insights to create professional service offerings and tools that empower organizations to make informed, data-driven decisions. Learn more about our Mission, Team and Offerings. VIEW YOU MAY ALSO ENJOY YOU MAY ALSO ENJOY YOU MAY ALSO ENJOY YOU MAY ALSO ENJOY LOOP ME IN Boldly go! Get in touch with our team of data experts today. Ready to Achieve More With Your Data? GET LOOPED IN GET LOOPED IN GET LOOPED IN GET LOOPED IN PREVIOUS NEXT