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Today’s manufacturing and distribution teams are balancing more complexity than ever. With rapid advances in AI, automation, and data platforms, the pressure to modernize is mounting across every part of the business - from operations to talent to tech.  But while the opportunity is exciting, the path forward isn’t always clear.  Business Challenges Facing Manufacturing & Distribution  These industries are navigating a perfect storm of operational demands, shifting workforce expectations, and emerging technologies. Here are just a few of the most common roadblocks:  Systems Integration  Connecting critical platforms like CRM, ERP, Payroll, and Timesheets is essential for operational visibility—but it’s often complex, costly, and time-consuming to implement.  Emerging Technologies  Keeping pace with innovations like robotics, IoT, and AI can feel like a full-time job in itself, especially for mid-market teams without dedicated R&D.  Talent Management  Attracting and retaining skilled workers continues to be a challenge, particularly as experienced workers retire and expectations shift across generations.  Unplanned Equipment Downtime  When systems or machinery go offline, productivity and profitability take a direct hit.  Cybersecurity Threats  As reliance on digital tools and connected devices increases, so does vulnerability to cyber-attacks and data breaches.  Supply Chain Disruptions  Delays, shortages, and geopolitical friction are putting added strain on already fragile supply chains.    How Data & AI Can Help  While none of these challenges are new, the tools available to solve them are evolving fast. With the right data infrastructure in place, manufacturers can shift from reactive to proactive - spotting risks sooner, streamlining operations, and scaling smarter.   Here are three ways data and AI can move the needle:  Unified Data Platform  - A solution like Microsoft Fabric  brings all your data sources together - simplifying integration, enabling cross-functional visibility, and creating a single source of truth across the business.  Embedded Power BI Dashboards  - Make insights actionable by embedding real-time dashboards directly within your business applications. With Power BI integration, teams can track KPIs, spot trends, and make data-backed decisions without switching tools.  Smart Sync -  Interloop’s Smart Sync offering connects your operational tools to your data platform, surfacing key insights and attributes exactly where teams need them. No more digging for reports - just smarter decisions, faster.  Real Results in the Field  A material handling equipment company in Michigan faced a common issue: disconnected data between CRM and ERP systems made sales performance tracking manual, time-consuming, and reactive.  The Challenge :  Sales commissions were tied to different milestones depending on the equipment type, requiring data from multiple systems. Performance reporting was only available monthly, after hours of spreadsheet cleanup. Reps had no real-time visibility into their numbers and couldn’t proactively adjust course.  The Solution:  Interloop helped unify CRM and ERP data in Microsoft Fabric, then built a Power BI dashboard embedded within the CRM. This gave sales reps instant access to real-time performance data—no spreadsheets, no bottlenecks.  The Result:   What used to take days now takes minutes. Reporting is refreshed daily, reps are empowered to self-monitor and adjust in real time, and leadership has clear visibility across the board.  Need Support on this Data Journey?  Our Fast Dash  solution helps teams move from insight to impact - fast. Whether you need to streamline reporting, centralize data, or activate AI, we’ll help you stand up a real-time dashboard tailored to your business.  Ready to get looped in? Let’s get started .

By Tony Berry  Data ingestion is a foundational component of any modern data architecture, enabling raw data to be collected, imported, and processed from a variety of source systems into a centralized lake or warehouse.  Microsoft Fabric provides several robust options for data ingestion - each with its own strengths, limitations, and ideal use cases. Whether your team is focused on building pipelines, accelerating ETL, or supporting analytics and AI workflows, choosing the right approach is critical.  Below is an overview of the six key ingestion methods available in Microsoft Fabric, with insights on when and why to use each.  1. Data Pipelines  Data Pipelines in Microsoft Fabric offer a code-free or low-code experience for orchestrating ETL workflows. They enable users to copy data from source to destination while also incorporating additional steps, such as preparing environments, executing T-SQL, and running notebooks.  Best for:  Teams looking to automate and scale standard ETL processes with limited code requirements.  ✅ Pros   Code-Free or Low-Code  – Accessible to broader teams.  Workflow Automation  – Supports scheduling and orchestration.  High Scalability  – Capable of managing large volumes of data.  ⚠️ Cons   Initial Setup  – Requires some configuration.  Performance Ceiling  – May not match code-rich options for extremely high-throughput.  Transformation Flexibility  – More limited for advanced data shaping or normalization.    Learn more about Data Pipelines   2. Dataflows Gen2  Dataflows Gen2 provides a visual, Power Query–based environment for data prep and transformation before ingestion. It’s designed for users who need custom, column-level transformations without writing code.  Best for:   Analysts and data engineers who need an easy way to prep and shape source data visually.  ✅ Pros   No-Code Interface  – Great for data prep without engineering support.  Custom Transformations  – Modify schemas, create calculated fields, and shape datasets.  Fabric Native  – Fully integrated into the Fabric ecosystem.  ⚠️ Cons   Source Limitations  – Bound to supported connectors.  Less Suitable for Scale  – Not optimized for massive or highly complex pipelines.  Flexibility Constraints  – May not support advanced ingestion logic.  Learn more about Dataflows Gen2     3. PySpark and Python Notebooks  For technically advanced teams, PySpark and Python notebooks offer unmatched flexibility and distributed processing capabilities. These notebooks are ideal for complex transformation pipelines, large datasets, and Spark-native workloads.  Best for:   Teams with Spark/Python expertise working on custom, high-scale data processing tasks.  ✅ Pros   High Performance  – Leverages Spark’s distributed compute engine.  Custom Logic  – Supports complex ingestion and transformation workflows.  Seamless Integration  – Connects to other Fabric components for end-to-end pipelines.  ⚠️ Cons   High Complexity  – Requires PySpark or Python expertise.  Manual Management  – Error handling, logging, and retries must be coded explicitly.  Setup Overhead  – More effort required than GUI-based tools.    Learn more about Notebooks in Fabric   4. Copy Job (New)  The new Copy Job  tool uses a visual assistant to move data between cloud-based sources and sinks. It’s a simplified option for users who want to ingest data quickly without building a full pipeline.  Best for:  Users who need a fast, lightweight ingestion option with minimal setup.  ✅ Pros   User-Friendly Setup  – Copy Assistant simplifies configuration.  Connector Support  – Works with a growing list of cloud sources.  Composable  – Can be included in broader pipeline workflows.  ⚠️ Cons   Gateway Restriction  – On-premises to on-premises transfers require a shared gateway.  Throughput Limitations  – May not match dedicated tools like the COPY statement.  Limited Connectors  – Support for sources is still expanding.  Learn more about Copy Job     5. COPY (Transact-SQL)  The COPY  statement is a high-throughput, T-SQL–driven method for ingesting data from Azure storage into Fabric. It’s best suited for engineering teams who need full control over ingestion behavior via SQL.  Best for:   Data teams already operating in a Transact-SQL environment and needing maximum performance.  ✅ Pros   Top-Tier Performance  – Delivers the highest available ingestion throughput.  Granular Control  – Tune performance, map columns, and control ingestion behavior.  ETL/ELT Integration  – Works seamlessly with existing T-SQL logic.  ⚠️ Cons   Azure-Only Source Support  – Currently limited to Azure storage accounts.  Code Requirement  – Requires SQL fluency; not ideal for all users.    Learn more about the COPY Statement   6. External Tools (e.g., Fivetran)  Fivetran offers a Managed Data Lake Service (MDLS)  that automates ingestion and normalization into Fabric and OneLake. With 700+ connectors and prebuilt logic, it’s a strong option for teams that prioritize automation and governance.  Best for:  Organizations seeking fast, governed ingestion from a wide variety of data sources—without building it all themselves.  ✅ Pros   Fully Managed  – Automates ingestion, normalization, compaction, and deduplication.  Extensive Connectors  – 700+ prebuilt source integrations.  Fabric-Native  – Supports OneLake and AI/analytics workloads.  Governance Ready  – Converts raw data into optimized formats (Delta Lake or Apache Iceberg).  ⚠️ Cons   Cost Consideration  – Fivetran licensing adds to overall project cost.  Learn more about Fivetran’s MDLS     Final Thoughts  Microsoft Fabric gives teams the flexibility to choose the right ingestion strategy based on technical maturity, scale, and existing architecture. Whether you're looking for no-code setup, full control via SQL or Spark, or fully managed ingestion, there’s an option designed to meet your needs.  Understanding the trade-offs of each method - and aligning them with your team’s strengths - sets the foundation for scalable, insight-ready data infrastructure.  Need help choosing the right data ingestion path?  At Interloop, we specialize in helping mid-market teams activate their data with clarity and confidence. Whether you're evaluating COPY vs. Pipelines, rolling out Fivetran, or just getting started with Microsoft Fabric - we can help you move from disconnected data to real-time insight.  Let’s get you from ingestion to action. Get looped in today .

The Loopers are back from Las Vegas - recharged, inspired, and ready to help more organizations harness the power of Microsoft Fabric. The second annual Fabric Community Conference (FABCON 2025) brought together more than 6,000 attendees for six days of hands-on workshops, live demos, and deep-dive sessions focused on data, AI, and the future of business transformation.   As an event sponsor, Interloop had a front-row seat to all the action. Here are our biggest takeaways.  FABCON 2025 Keynote Highlights  OneLake Security: Define Once, Enforce Everywhere  Managing data security across multiple tools and engines is notoriously complex - and risky. Microsoft’s OneLake security model simplifies governance by allowing organizations to define access permissions once and have them enforced consistently across all Fabric workloads.   With row-and column-level access controls, security roles, and fine-grained permissions, data owners can securely share what matters and keep everything else protected - whether it’s being queried in SQL or visualized in Power BI.  Copilot Across All Fabric SKUs  AI is no longer an add-on - it’s embedded in the foundation. With Copilot now available across all Fabric SKUs, users at every tier can take advantage of natural language capabilities to explore data, create visualizations, automate workflows, and generate insights.   Fabric data agents take it a step further, understanding your organization’s unique data model to accelerate time to insight. The new Copilot capacity makes it easier to enable features and manage users, lowering the barrier to entry for teams of any size.  Synapse Migration Made Simple  For organizations currently using Azure Synapse Analytics, Microsoft announced a built-in migration experience (in preview) that makes the move to Fabric smoother than ever. This tool automatically converts schemas, transfers data and metadata, and offers AI-powered guidance throughout the process - helping organizations unlock the benefits of Fabric without disruption or heavy lifting.  Loopers' Favorite Features  From preview announcements to developer-first tools, the conference delivered. Here’s what stood out most to our team:  Meaghan:   “Direct Lake semantic models in Power BI Desktop are game-changing for analysts. By accessing OneLake data directly, you get high-performance query processing without data duplication or long refresh cycles—no complex setup required.”   Jordan:   “The Fabric Command Line Interface (CLI) gives developers a fast, flexible, scriptable way to work with Fabric from the terminal. It’s built on Fabric APIs, supports automation, and feels like navigating a file system—only smarter.”   Tony:   “AI functions in preview make it easy to integrate GenAI into data workflows. With just one line of code, you can summarize, classify, and generate text using Spark or pandas DataFrames—no complex setup or clunky syntax needed.”     Final Thought: Data Is the Fuel  Microsoft Fabric is driving the next wave of data and AI transformation. But as always, your insights are only as strong as the data beneath them. Garbage in still equals garbage out.  Siloed, outdated, and poor-quality data can undermine even the most advanced platforms.  That’s where Interloop comes in.  As a Microsoft-certified partner, Interloop helps organizations build a unified data foundation—ensuring your Fabric environment and AI solutions are powered by clean, organized, high-quality data.  Get Looped In  Want to accelerate your data transformation with Fabric and AI? Let’s build something powerful - together.  Get looped in today .

A connection refers to the link between Interloop and an Operational System or Database. Interloop can either pull data from a Connection into the data engine or can sync data back out into a connection. Connection A connection refers to the link between Interloop and an Operational System or Database. Interloop can either pull data from a Connection into the data engine or can sync data back out into a connection. Ready To Get Started? You're one small step from starting your data-driven journey. LOOP ME IN

A service account is a login that is used with a team or a system rather than an actual individual. Often when connecting to operational systems, it can be helpful to setup a service account rather than using the login credentials of an existing user. Service Account A service account is a login that is used with a team or a system rather than an actual individual. Often when connecting to operational systems, it can be helpful to setup a service account rather than using the login credentials of an existing user. Ready To Get Started? You're one small step from starting your data-driven journey. LOOP ME IN

Explore Microsoft Fabric with Interloop’s Success Kit—featuring a curated data sheet, DataOps guide, and on-demand AI webinar to help you unify your data and accelerate your AI strategy. Your launchpad for smarter data, seamless Fabric integration, and AI-powered acceleration Microsoft Fabric Success Kit Curated for FABCON 2025, this kit delivers the essentials to help you align your data strategy, activate Microsoft Fabric and prepare for liftoff. MISSION CONTROL Less Time Fixing Broken Things, More Time on What Matters Interloop Mission Control enables data teams to connect Microsoft Fabric with the rest of their data stack to gain unprecedented visibility into their data infrastructure. With Mission Control, go from reactive to proactive by detecting problems early and solving them fast. Want help navigating what’s next? Let’s talk. JOIN THE WAITLIST Start Your Data Mission Here Each link below is a mission-critical checkpoint - handpicked by our team to equip your team with Fabric knowledge, clarity, and momentum. VIEW DATA SHEET Microsoft Fabric Overview A clear look at Fabric’s unified platform and how it simplifies your data stack. Go READ FULL FEATURE The Rise of DataOps Why modern DataOps is the fuel behind faster insights and AI readiness. Go WATCH WEBINAR You Can’t Have an AI Strategy Without a Data Strategy This session breaks down how data maturity shapes AI success—and what to do next. Go Need more Fabric, data or AI support? From unifying your data stack to building out copilots, we’re here to help you move faster, scale smarter, and stay in orbit. LOOP ME IN