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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.

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

Content Delivery Network. CDN's are a network of servers which make downloading files faster for end users by placing them all around the world to reduce latency and transfer time over the internet. CDN Content Delivery Network. CDN's are a network of servers which make downloading files faster for end users by placing them all around the world to reduce latency and transfer time over the internet. Ready To Get Started? You're one small step from starting your data-driven journey. LOOP ME IN

A software distribution model where the application is hosted by a company on its servers and is accessed by clients via the internet by paying a subscription fee. For example, Salesforce. SaaS (Software as a Service) A software distribution model where the application is hosted by a company on its servers and is accessed by clients via the internet by paying a subscription fee. For example, Salesforce. Ready To Get Started? You're one small step from starting your data-driven journey. LOOP ME IN