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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.

Learn commonly referenced terms and phrases used in Data & Artificial Intelligence Glossary Learn commonly referenced terms and phrases used in Data & Artificial Intelligence API (Application Programming Interface) API (Application Programming Interface) Application Programming Interface. In software, this term refers to a way of programmatically interacting with a the software, without the use of a user-interface built for humans. App App The app is what we call the main Interloop web application, this is the part you log in to, and where you can view and configure your organization's Connections, Jobs, Datasets, Monitors, & more. Artificial Intelligence Artificial Intelligence Computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. Business Intelligence (BI) Business Intelligence (BI) Business intelligence (BI) leverages software and services to transform data into actionable insights that inform an organization’s business decisions. CDN 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. 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. Data Lakehouse Data Lakehouse A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. Data Pipeline Data Pipeline A data pipeline is a series of data processing steps that moves data from one place to another. In Interloop an Ingestion or Sync Job would be synonymous with a Data Pipeline in other tools. ELT (Extract Load Transform) ELT (Extract Load Transform) Extract Load Transform. This is a similar but slightly different approach from ETL in which data is extracted from a source system, loaded into a central repository, and then later transformed on demand as needed. Ingestion Ingestion The act of retrieving or fetching data from a Connection. Java Database Connectivity (JDBC) Java Database Connectivity (JDBC) A SQL-based API created by Sun Microsystems to enable Java applications to use SQL for database access. A JDBC Source is one that supports JDBC connectivity. The JDBC driver for that data source and the URL format is required to set up the connection. JSON JSON JSON, or Javascript Object Notation, is a convenient format for storing structured data. OAuth OAuth An open standard for authorization that allows applications or websites limited access to resources hosted by other apps and websites on behalf of the user without sharing the user’s password. Rate Limits Rate Limits The limits imposed by an API vendor, such as Intercom, HubSpot, on the number of API requests sent to their public APIs. Reverse ETL Reverse ETL Reverse ETL is the process of sending data residing in your data lakehouse to various downstream operational tools. This includes various SaaS marketing, analytics, sales, and customer support tools. SaaS (Software as a Service) 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. Schema Schema A schema refers to the design of a database, including which fields are currently configured, what data types of stored in these fields. If you were to think of a database as a spreadsheet with columns and rows, the schedule would be the first row that defines the field names, plus the data types and formatting rules for each column. SDK (Software Development Kit) SDK (Software Development Kit) Software Development Kit. This is combination of libraries and tooling that can make it easier for developers to interact with the Interloop API. Service Account 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. SQL SQL Structured Query Language. The standard language for querying and retrieving information for analysis. SQL can be used to query raw data, group data, aggregate data and much more. For instance to query all leads that with the persona of "Rational Ray" would translate to the following in SQL: select * from leads where persona equals 'Relational Ray' Transformation Transformation The process of changing the format and structure of data. Universally Unique Identifier (UUID) Universally Unique Identifier (UUID) A UUID is a unique string that can be used to identify a particular record. Warehouse 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.

View Interloop's Fabric Attestation here or get in touch with us to learn more about Interloop & Microsoft Fabric. Publish Workload Requirements Attestation Checklist We, the vendor, Interloop Technologies, Inc., confirm and attest to reviewing, meeting and complying with the requirements outlined in the Microsoft Fabric Workload Development Kit (WDK) specifically the Publish Workload Requirements located at https://learn.microsoft.com/en-us/fabric/workload-development-kit/publish-workload-requirements . The following sections documents details, exceptions, or variances regarding the attestation of adherence to the Publish Workload Requirements . Business Requirements: Value To Customers: The workload provides the following value to customers: Interloop empowers teams using Microsoft Fabric to build and deliver Data Analytics & AI Solutions Faster. The Interloop Fabric Workload reduces engineering workloads and costs, enabling teams to focus on addressing the business challenges that matter. Trial: We provide an easy and fast trial experience. The trial is available to the customer without waiting time (less than 5 seconds), and provides a free and easy way to explore the offered workload for a limited time in accordance with Microsoft guidelines for Trials [ ] Yes [x] No Monetization: The workload is available on the marketplace for the customer to procure with or without a trial in accordance with the monetization guidelines [x] Yes [ ] No Technical Requirements: Microsoft Entra Access: The workload(s) use Microsoft Entra authentication and authorization. [x] No additional authentication and authorization mechanisms are used [ ] Additional authentication and authorization mechanisms are used for stored data In Fabric The following is the Interloop Tenant Id: 01783792-6de1-4267-bd2f-4109779ae40a One Lake: Workloads integrate with One Lake to store data in the standard formats supported by the Fabric platform so that other services can take advantage of it. [x] All data and metadata is stored in One Lake or Fabric Data Stores [ ] Not all data and metadata is store in One Lake or Fabric Data Stores N/A Microsoft Entra Conditional Access : Enterprise customers require centralized control and management of the identities and credentials used to access their resources and data and via Microsoft Entra to further secure their environment via conditional access. [x] The service works in its entirety with even if customers enable this functionality [ ] The service works in with limitations if customers enable this functionality [ ] The service does not work Microsoft Entra Conditional Access We fully integrate with Entra and support all of it’s access control features. Admin REST API: Admin REST APIs are an integral part of Fabric admin and governance process. These APIs help Fabric admins in discovering workspaces and items, and enforcing governance such as performing access reviews, etc. Basic functionality is supported as part of the Workload Development Kit and doesn't need any work from Partners. [ ] Microsoft Fabric Admin API’s are being leveraged (/admin/*) [x] No Microsoft Fabric Admin API’s are being used Customer Facing Monitoring & Diagnostic: Health and telemetry data needs to be stored for a minimum for 30 days including activity ID for customer support purposes, including Trials. [x] Minimum 30 days requirement is adhered to [ ] Vendor stores the data for __ additional days beyond the minimum requirement B2B: The implementation of the workload is in line with Microsoft Fabric’s sharing strategy focused on allowing customers to collaborate with their business partners, customers, vendors, subsidiaries etc. It also means users from other tenants can potentially be granted access to items partners are creating. [ ] Cross tenant B2B collaboration supported [x] Workload Item Access only within the tenant Items are not being shared across tenants Business Continuity and disaster recovery: The vendor has a comprehensive Business Continuity and Disaster Recovery (BCDR) plans designed to tackle unplanned disasters and recovery steps. Performance: The Workload implementation takes measures to test and track performance of their Items [x] Performance Metrics on workload performance are available via the monitoring hub [x] Workload additionally includes a separate monitoring UI to test and track performance [ ] Performance tracking is not currently available to the end user however vendor support personnel can monitor, test, track performance via their internal instrumentation and monitoring systems Presence: To ensure that customer expectations independent of their home or capacity region are met, vendors need to align with fabric regions and clouds. Availability in certain restrictions also impacts your Data Residency commitments. [x] Service availability and colocation/alignment in the following fabric regions We support all regions supported by Azure. By default, Interloop is hosted in the US Region. For our Enterprise Level customers, we support the selection of region-specific deployments. [ ] All or part of the service does not reside in Azure Interloop Fabric Workload is hosted within Azure and uses Azure based services. Public APIs: Fabric Public APIs are the backbone of automation, enabling seamless communication and integration for both customers and partners within the Fabric ecosystem. Fabric Public API empowers users to build innovative solutions, enhance scalability, and streamline workflows. [X] The workload uses Fabric Public APIs Design / UX Requirements: Common UX: The workload and all item types the partner provides as part of it comply with the Fabric UX guidelines. [x] The workload is fully compliant with the Fabric UX guidelines [ ] The following variance and/or exceptions have been granted by Microsoft N/A Item Creation Experience: The item creation experience is in accordance with the Fabric UX System. [x] Yes [ ] No Monitoring Hub: All Long running operations need to integrate with Fabric Monitoring Hub. [x] Yes [ ] No Trial Experience: The workload provides a Trial Experience for users as outlined in the design guidelines [ ] Trial Supported [x] Trial Not Supported Trials are not supported during Public Preview. Interloop intends to provide a 14-Day Free Trial for end users. Monetization Experience: The monetization experience is in line with the design guidelines provided [ ] The monetization experience is completely integrated with the marketplace and compliant with the guidelines [ ] Bring Your Own License (BYOL) [X] Free / Freemium [ ] Other This is a free experience during public preview. Interloop intends to monetize the workload in subsequent releases via the Azure Marketplace Accessibility: The user experience is in compliance with the Fabric UX design guidelines for Accessibility [x] The user experience is completely compliant with the guidelines [ ] The following limitations exist N/A World Readiness / Internationalization: English is supported as the default language. Localization through optional, should be considered. [x] English is the only supported language [ ] The following are the additional languages supported Item Settings: Item settings are implemented as a part of the ribbon as outlined in the UX guidelines [x] Yes [ ] No N/A Samples: Samples are optionally provided that preconfigure items of their type their type to help customers get started more easily. [x] Samples not provided [ ] Samples for pre-configuration of items provided Custom Actions: Custom actions can be optionally provided as a part of the item editor. [x] Custom Actions are not implemented [ ] Custom Actions implemented as part of Workload N/A Workspace settings: Workspace settings provide a way that workloads can be configured on a workspace level. [ ] Supported [x] Not Supported Global Search: Searching for items in Fabric is supported through the top search bar. [ ] Supported [x] Not supported Security / Compliance Requirements: Security general: Protection of customer data and metadata is of paramount importance. Workloads must go through a security review and assessment. Vendor attests that the security review and assessment was completed and will be periodically performed as enhancements and changes are made. Security issues discovered which could have a detrimental impact on the customer should be addressed promptly and customers notified where applicable. Interloop has strict security and privacy policies that adhere with Industry standards. We don’t host this information publicly but users can request a copy by sending an email to support@interloopdata.com Privacy: Partners that build workloads also have a responsibility to protect that data when they access it. Every workload goes through a privacy assessment and a privacy review. Vendor attests that privacy review was completed and is periodically performed as enhancements and changes are made. [x] Extra Requirements: Vendor attests that only essential HTTP-only cookies are used by the Workload and only after positively authenticating the user. N/A Data Residency: Microsoft Fabric is making an Enterprise Promise around data not leaving the geography of the tenant for stored data and data in transit. As a workload in Fabric directly and users need to be aware what your commitments to Data Residency are. Define what your commitments are to the Data Residency of customer data. Our approach to data residency is documented here: https://docs.interloopdata.com/interloop/policies/security Compliance: The publisher attests to the following security, data and compliance regulations and standards Interloop is a cloud hosted solution and utilizes Microsoft Azure and leverages strict security & privacy policies that creates a critical line of defense against potential malicious activity. Interloop does not store any customer data and instead leverages the Microsoft Fabric infrastructure to securely manage and administer a customer's data. Any access credentials used to connect to Sources or Destinations are managed and maintained securely using Azure Key Vault. All data, both in transit and at rest, is encrypted utilizing industry standards. Support: Live site: Partner workloads are an integral part of Fabric that require the Microsoft support teams need to be aware of how to contact you in case customers are reaching out to us directly. Microsoft direct vendor outreach: [X] Contact Name/Team: Interloop Support [X] Number: (843) 202-4399 [X] Email Alias: support@interloopdata.com [X] Self Service Portal https://support.interloopdata.com Supportability: Vendors are responsible for defining and documenting their support parameters (Service level agreement, contact methods, ...). This information needs to be linked from the Workload page and should always be accessible to customers. In addition, the Marketplace criteria, need to be taken into account for the listing of the SaaS offer. [x] Vendor attests that support information is published to the marketplace offering and available to user/customers directly via the workload Service Health and Availability: Vendors need to host a service health dashboard that shows their service health and availability to customers. This information can be included on the Supportability page. Customers can check the status of Interloop by visiting https://status.interloopdata.com Fabric Features: Application Life Cycle Management (ALM): Microsoft Fabric's lifecycle management tools enable efficient product development, continuous updates, fast releases, and ongoing feature enhancements. [ ] Supported [x] Not Supported Private Links: In Fabric, you can configure and use an endpoint that allows your organization to access Fabric privately. [ ] Supported [x] Not Supported Data Hub: The OneLake data hub makes it easy to find, explore, and use the Fabric data items in your organization that you have access to. It provides information about the items and entry points for working with them. If you're implementing a Data Item, show up in the Data Hub as well. [ ] Supported [x] Not Supported Data Lineage: In modern business intelligence (BI) projects, understanding the flow of data from the data source to its destination can be a challenge. The challenge is even bigger if you built advanced analytical projects spanning multiple data sources, data items, and dependencies. Questions like "What happens if I change this data?" or "Why isn't this report up to date?" can be hard to answer. [ ] Supported [x] Not Supported Sensitivity labels: Sensitivity labels from Microsoft Purview Information Protection on items can guard your sensitive content against unauthorized data access and leakage. They're a key component in helping your organization meet its governance and compliance requirements. Labeling your data correctly with sensitivity labels ensures that only authorized people can access your data. Extra requirements : For partners that are using Export functionality within their Item they need to follow the guidelines. [ ] Supported [x] Not Supported Additional Notes Please use this section to provide any further explanations, references, or notes that may be relevant to your attestation: References https://interloopdata.com/privacy-policy https://interloopdata.com/terms-of-service https://interloopdata.com/security Fabric Attestation Last Updated: November 27, 2024 Ready To Get Started? You're one small step from starting your data-driven journey. LOOP ME IN

With Interloop, becoming data-driven has never been easier - move from raw data to actionable insights in a matter of weeks. Let us loop you in. Get in touch with Interloop today. Contact Interloop Existing customer? Get technical help from our team by reaching out to through our Support Center . Send Us A Message We'll get back to you as soon as we can First name* Last name* Email* Company* Tell Us More SEND Yes, subscribe me to your newsletter. Ready To Get Started? You're one small step from starting your data-driven journey. LOOP ME IN