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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.

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 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

WEBINAR You Can’t Have an AI Strategy Without a Data Strategy WEBINAR No Data, No AI. Build the Fuel. No Data, No AI. Build the Fuel. No Data, No AI. Build the Fuel. No Data, No AI. Build the Fuel. The AI landscape is evolving at warp speed, but without a solid data strategy, even the most advanced AI initiatives can stall before they get off the ground. In this expert-led webinar, Interloop’s team breaks down the Five Pillars of AI Success, shares real-world implementation insights, and demos how businesses are leveraging Copilot and Microsoft Fabric to turn data into true AI acceleration. - How to create an AI strategy (even if you’re mid-flight)
 - Why the right data foundation makes or breaks AI success
 - Avoiding common pitfalls (like scope creep and ungoverned models) 
- Live AI and Copilot demo in action Ready to make AI work for you? Watch the webinar now. 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