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Here are the top 10 items from the Microsoft Fabric October 2024 Monthly Update that data professionals should be aware of: API for GraphQL Support for Service Principal Names (SPNs) : This new feature enhances security and simplifies authentication for data operations. Lakehouses Enhancements : New sorting, filtering, and searching capabilities have been introduced, making data management more efficient. KQL Queryset Update : A significant addition to KQL Queryset will revolutionize how users interact with their data, improving query efficiency and usability. Free Certification Opportunity : Microsoft is offering 5,000 free DP-600 exam vouchers for the Microsoft Certified: Fabric Analytics Engineer Associate certification, available until the end of the year. New Data Engineer Certification : The Microsoft Certified: Fabric Data Engineer Associate certification is now available, focusing on data ingestion, transformation, administration, monitoring, and performance optimization. Content Copilot Enhancements : Public preview of AI-enhanced Power BI report creation with Copilot, including improved clarity and contextual awareness for building valuable reports. Visual Calculations Update : Combo charts now support visual calculations, and field parameters can be used with visual calculations for more dynamic data visualization. Azure Map Update : Data bound reference layers now allow for dynamic integration with business data, enhancing the interactivity and flexibility of Azure Maps. Notebook Improvements : New features include automatic code generation in API for GraphQL, Git integration, deployment pipeline GA, and enhanced filtering, sorting, and searching in Lakehouse objects. Real-Time Intelligence Enhancements : Integration with GitHub for real-time dashboards, and the ability to save queries to dashboards, improving real-time data visualization and management. These updates bring significant improvements to data management, visualization, and operational efficiency in Microsoft Fabric

Jordan Berry assumes role of CEO, Tony Berry transitions to President and Chairman as company prepares for 2025 product launch. Charleston, SC - For Immediate Release Interloop®, a leader in Data Operations and Data Engineering solutions, announces the appointment of Jordan Berry as Chief Executive Officer and Tony Berry as President and Chairman. This leadership transition comes at a pivotal moment as the company prepares to launch Mission Control, a groundbreaking Data Operations platform for Microsoft Fabric in Q1 2025. Jordan Berry, who co-founded Interloop, brings a wealth of experience and vision to the CEO role. Reflecting on his new role, Jordan shared, “I am honored and excited to step into the role of CEO at Interloop. This transition marks a significant milestone for our company as we launch Mission Control, our new Data Operations platform for Microsoft Fabric. Tony will transition to President and Chairman, focusing on enhancing our operations and delivery. I look forward to leading our team in this exciting new phase and building on the strong foundation laid by Tony. Together, we will continue to drive innovation and growth for Interloop.” Tony Berry, who has served as CEO since Interloop’s inception, will now take on the role of President and Chairman. As Interloop looks forward to its next chapter, Tony emphasized the strategic importance of this transition: “I'm thrilled to announce my transition from CEO to President/Chairman at Interloop. Jordan’s assumption of the CEO role marks a pivotal moment for our company. This change is designed to support the launch and growth of our new Mission Control platform that is fueled by Microsoft Fabric. With Jordan at the helm, I am excited for the promising future ahead and the continued success of Interloop.” This leadership shift positions Interloop to expand its impact in the DataOps space as its Mission Control is set to redefine data management for enterprises leveraging Microsoft Fabric. Both Tony and Jordan remain committed to fostering a culture of innovation, delivering transformative solutions for clients, and driving the company’s ambitious goals forward. As Interloop enters this next era, the company’s mission remains steadfast: empowering businesses to harness the full potential of data through advanced operations and engineering solutions. With Jordan’s vision and Tony’s strategic leadership, Interloop is poised to capitalize on the opportunities ahead and continue its trajectory of helping mid-market companies across the country achieve more with their data. About Interloop Serving mid-market companies nationwide, Interloop is the premier data engineering firm and Microsoft ISV partner dedicated to taking emerging entities from data-dark to insight and impact. With expertise in data engineering and DataOps solutions that integrate seamlessly with industry-leading platforms like Microsoft Fabric, Interloop empowers organizations to streamline data processes and harness actionable insights that drive business success. Get Looped In Ready to achieve more with your data? Contact Interloop today to schedule your consult and learn more about the upcoming release of Mission Control projected for Q1 2025.

Author: Mclain Reese What is the Invoke Pipeline Activity? The Invoke Pipeline activity in Microsoft Fabric is your central command for automating and orchestrating complex data workflows by "calling" one pipeline from another. Think of it as the control hub that helps you build modular and reusable pipelines, keeping your data processes orbiting smoothly across your organization. 🆕 What’s New in This Update? With the latest update, the Invoke Pipeline activity has expanded its universe of possibilities. You can now call pipelines across multiple services, including Fabric , Azure Data Factory , and Synapse Analytics . This integration allows you to manage and streamline your data workflows across platforms like never before. Whether you’re transforming data on Azure, analyzing it in Synapse, or managing it in Fabric, this update makes your data processes faster than light. Why Is This Update a Game-Changer? Galactic Flexibility : By integrating services, you can now break down barriers and orchestrate workflows across the data galaxy. No matter which platform your data resides on, this update gives you the flexibility to unify it all. Simplified Command : Forget building complicated workarounds—this update brings everything under one roof. Managing data workflows across platforms is now streamlined, reducing friction and ensuring smoother operations. Modular Workflow Design : Create reusable, space-efficient pipeline components that can be deployed across multiple missions (or projects). This saves time, boosts efficiency, and keeps your data journey on course. 🔍 Seen the "Legacy" Label? No Cause for Cosmic Concern If you’ve spotted the "Legacy" label on your existing Invoke Pipeline activities, don’t panic—your pipelines are still fully operational. This just means they’re part of the previous version, but your workflows won’t skip a beat. You won’t need to take any immediate action, and your legacy pipelines will continue to function as expected, without crashing into any black holes. What’s Next? With the new Invoke Pipeline activity, you can now explore new frontiers in data automation. By integrating services across Fabric, Azure Data Factory, and Synapse, you’ve got the tools to keep your workflows in orbit and push the boundaries of what’s possible. Ready to learn more? Check out the official documentation for all the details: Learn more about the Invoke Pipeline activity update here. Looking to achieve more with your data? Get looped in with one of our data experts today.

Author: Anna Cameron Microsoft Power Automate, part of the Power Platform, is a robust tool designed to automate tasks across various systems and applications. Its low-code interface simplifies the automation of repetitive tasks, enhancing efficiency by integrating processes between platforms. With Power Automate, users can build custom workflows that trigger actions based on specific conditions, streamlining complex business processes. The platform supports a wide range of connectors, including Slack, Adobe, Calendly, and Google applications like Google Drive and Calendar. In this guide, we’ll walk you through creating a daily workflow using Power Automate that queries a Power BI dataset, extracts the data, and saves it to OneDrive as a CSV file. 1. Sign in to Power Automate: Start by logging into Power Automate. 2. Create a New Flow:  Go to "My flows" and choose "New flow". For this example, we'll set up a "Scheduled cloud flow" that runs automatically at a specified time. However, selecting an “Automated cloud flow” will also take you to a blank flow where you can add the “Recurrence” trigger as well. 3. Name and Schedule Your Flow: Give your flow a name and set when you want it to run. You can also set the schedule in the following step. Click "Create" to start building your flow. 4. Set the Flow's Trigger: The flow begins with a "Recurrence” trigger, which schedules when the flow's actions will occur. You can always return to this step and edit this step to adjust the run schedule, if necessary. 5. Add an Action: Click the "+" button to add a new action step. Since we want to query data from Power BI, search for "Power BI" in the “Add an action pane” and then click "See more" 6. Run a Query in Power BI: Choose the action to "Run a query against a dataset". 7. Select the Workspace and Dataset: You'll then choose the workspace and dataset where you want to run the query. First, you’ll be prompted to login in to the Microsoft Power BI tenant where the report is hosted. Once connected you will see your workspaces and datasets. 8. Write the Query: Next, you’ll need to write a query in DAX. It’s a good idea to first create this query in Power BI, so you can confirm the results before using it in the flow. Once you’re happy with the query, copy it into the “Query Text” parameter. Be sure to add an EVALUATE statement to the beginning of the query. Then, assign the DAX query to a variable and EVALUATE said variable at the end of the query. Hint: If the data you want export is already in a table visual in a Power BI report, you can export the DAX for that specific visual using the Performance Optimizer in Power BI Desktop. 9. Format the Data: Add a "Select" action to format the data properly. Open the dynamic content list by selecting the lightning bolt icon. Set the “From” parameter to use the First table rows from the previous “Run a query against a dataset” step. The “Select” action in this flow is used to make sure that the column headers appear correctly in the CSV file export. Specify the column names by adding them as Keys in the “Map” parameter. Then, insert an expression by clicking the icon instead of the lightning bolt icon. Use the expression, item()?['table_name[column_name]'] , to transform the column headers pulled from the Power BI dataset. The expression will change the column header from something like “DIM_Date[Week_Start_Date]” to “Week Start Date” in the exported CSV file. 10. Create a CSV File: Add another action to "Create CSV table" and set it up to use the dynamic content Output from the previous “Select” step. 11. Save the File to OneDrive: The final step is to add an action to save the CSV file to OneDrive. You’ll be prompted to login to OneDrive to choose file path where the file will be saved. Set the file name and include a timestamp by using the expression utcNow() . A timestamp will be useful in managing and organizing the files generated by the recurring Power Automate flow. 12. Save and Test: Save your flow and run a test to confirm that the flow works. Thankfully, Power Automate provides a 28-day run history for each flow to track whether a run was successful or not. Clicking on one of the failed runs will open the flow and show exactly what step resulted in the failure. In addition, Microsoft’s new Copilot feature will aid in troubleshooting the errors by explaining the error and providing suggestions to solve the error. Wrap Up Microsoft Power Automate is a powerful tool that simplifies task automation, from sending emails to managing complex, multi-step workflows. Whether you’re extracting data from Power BI, saving it to SharePoint, or sending reports directly to clients, Power Automate helps streamline and automate these processes with ease. Its seamless integration across platforms not only boosts productivity but also helps businesses save valuable time, making it an essential asset for optimizing workflows. Looking for clear, practical solutions to your data challenges? Let’s loop you in. Book your intro call with our data experts today.

Author: Interloop Team In the vast expanse of tech advancement, we find ourselves in a new era—one where AI copilots are not just a futuristic concept but an essential part of modern business operations. Since the launch of OpenAI's ChatGPT, the dream of having a virtual assistant capable of handling myriad tasks—responding to emails, reading documents, answering questions, and even participating in virtual meetings—has transitioned from fantasy to reality. Today, copilots are everywhere, guiding businesses through the complexities of day-to-day operations with the precision of a seasoned astronaut navigating the stars. The scope of AI copilots reach far and wide, encompassing tasks from summarizing emails and reviewing contracts to crafting press releases and generating code. However, while the enthusiasm for these capabilities sometimes outpaces the technology’s current limits, the undeniable truth is that Generative AI, paired with natural language processing, has revolutionized the way organizations function. For instance, sales teams leveraging generative AI have reported saving up to 10 hours per week by automating routine administrative tasks, freeing up valuable time for strategic selling and client engagement. Yet, as business leaders navigate this new frontier, they grapple with the critical challenges of governance and control. The convenience of AI copilots can sometimes lead to inadvertent lapses in security, with team members potentially inputting sensitive client data into systems like ChatGPT. Ensuring responsible and secure AI usage is not just advisable but imperative to safeguarding both proprietary and client information. As we explore the Generative AI landscape, three distinct categories of business copilots have emerged: Application Copilots : These are AI-powered extensions integrated into existing tools like Office 365, Zendesk, and HubSpot, enhancing productivity within familiar platforms. Functional Copilots : These specialized copilots serve as virtual analysts for specific business functions—whether it’s financial research, marketing, or sales. However, without access to your organization’s data, their insights may lack the depth needed for actionable recommendations. Contextual Copilots : The next evolution in AI assistance, these custom-built copilots are designed to understand your organization's unique culture, strategy, and data. Hosted privately and tailored to your specific needs, they offer unparalleled insights and are poised to become the most valuable copilots on your journey through the AI cosmos. As businesses continue to expand into this new AI-powered frontier, contextual copilots represent a significant opportunity. Organizations that invest in these advanced copilots will find themselves better equipped to navigate the complexities of their industry, making informed decisions with the confidence of a captain who knows every star in the galaxy. Where do we land? At Interloop, we think Contextual Copilots are the next evolution of copilots and where organizations stand to gain the most. We’re already seeing many ventures (and working with several) that are building their own contextual Copilots that understand the nuances of their business. Looking for clear, practical solutions to your data challenges? Let’s loop you in. Book your intro call with our data experts today.

The August 2024 updates for Microsoft Fabric puts Copilot and PowerBI at the forefront with some additional helpful enhancements for Data Engineers and Data Scientists. Here are the top 10 updates we think you should know about: Top 10 Microsoft Fabric Updates for August 2024 Copilot and AI Enhancements in Power BI : Users can now ask Copilot questions against their semantic model, improving data interaction and insights generation. V-Order Behavior in Fabric Warehouses : New feature allowing management of V-Order behavior at the warehouse level, enhancing data organization and retrieval efficiency. Monitor ML Experiments from the Monitor Hub : Integration of experiment items into the Monitoring Hub, facilitating easier tracking and management of machine learning experiments. Modern Data Experience in Data Pipeline : Enhanced connectivity to Azure resources, streamlining data integration and pipeline management. Reporting Enhancements in Power BI : Introduction of visual level format strings (preview) and dynamic per recipient subscriptions (generally available), enhancing report customization and distribution. Improved Dataflow Performance : Optimizations to dataflow performance, resulting in faster data processing and reduced latency. Enhanced Security Features : Introduction of new security features to protect data integrity and ensure compliance with industry standards. Expanded Data Connectors : Addition of new data connectors, broadening the range of data sources that can be integrated into the Fabric platform. Data Integration Improvements in Power BI : Updated Save and Upload to OneDrive Flow in Power BI, streamlining data management and sharing. Embedded Analytics in Power BI : Narrative visual with Copilot is now available in SaaS embed, enhancing storytelling and data presentation capabilities. Conclusion The August 2024 updates will help users supercharge their dashboards and more effectively monitor the Machine Learning and Copilot based solutions from within the Fabric portal. For the full updates - check out this video from the Microsoft Team:

The July 2024 update for Microsoft Fabric brings a host of exciting enhancements and new features, aimed at empowering data professionals with more robust tools and capabilities. Here’s a concise summary of the key updates we think you should be aware of: Enhanced Git Integration One of the standout features in this update is the improved Git integration. Data professionals can now create and manage Git branches and connected workspaces more efficiently. This enhancement simplifies version control and collaboration, making it easier to track changes and maintain consistency across projects 1 . Restore-in-Place for Warehouses The update introduces the ability to perform restore-in-place of a warehouse through the Microsoft Fabric Warehouse Editor. This feature is a game-changer for data recovery and management, allowing users to restore data without the need for complex procedures or downtime 1 . Real-Time Dashboards Real-time intelligence takes a leap forward with the introduction of ultra-low refresh rates for dashboards. Now, dashboards can refresh at intervals as low as 1 and 10 seconds, ensuring that data professionals always have the most current and accurate data at their fingertips. This is particularly beneficial for scenarios requiring immediate data insights and decision-making 1 . Browser Update Reminder for Power BI Users A crucial reminder for Power BI users: ensure your web browser is up to date. Starting August 31, 2024, accessing Power BI on browsers older than Chrome 94, Edge 94, Safari 16.4, or Firefox 93 may result in limited functionality. Keeping your browser updated ensures you can fully leverage the latest features and improvements in Power BI 1 . Conclusion The July 2024 update for Microsoft Fabric is packed with enhancements that significantly boost the capabilities of data professionals. From improved Git integration and real-time dashboards to new learning opportunities and community events, these updates are designed to streamline workflows, enhance data management, and foster professional growth. Stay tuned for more exciting developments as Microsoft continues to innovate and expand the Fabric platform. For the full update - check out this video from the Microsoft Fabric Team:

From print-outs on a bulletin board to fully automated lifecycle dashboard, Interloop® helps leading manufacturer go from data-dark to sights on the stars. OUR CLIENT Founded in 1951, this family-owned, operated venture designs and produces premier pyrometers with innovative wavelength selection that can accurately view through common industrial interferences including steam, flames, combustion gasses, water, plasma and oil. Industry leaders for 70+ years, our client proudly serves manufacturers across the globe with thousands of successful installations spanning steel, incineration, glass, CVD/semiconductor, aluminum and petrochemical spaces. THE CHALLENGE Answering critical business questions meant accessing multiple systems, manually downloading reports, and manipulating data. This cumbersome process drained significant time, effort and resources for straightforward questions that required quick answers. As their operations continued to scale internationally, this manufacturer knew it needed faster, automated reporting with reduced risk and margin for error. ENGAGE - THE FIRST MISSION From data-dark to shoot for the moon Interloop's first task was to develop a resource for our client’s business development team to track their progress and goals. This resource supported sales leadership in conducting one-on-one review sessions, forecasting sales, increasing pipeline visibility, and managing customer/account health. Data-curious and two steps ahead on prep-work, our client had already started consolidating data from different systems into one place - bringing data from their ERP, CRM and financial systems into Microsoft Access. With a clear runway, Interloop leveraged our proprietary FastDash process to design and develop a comprehensive sales dashboard customized to suit. Once live, our client immediately enjoyed near real-time insight and instantly realized the potential for more. Onward. They asked the Loopers to move from business development to providing insights on production and shipment including: Optimizing technician and assembler load balancing post-order. Predicting order delivery timelines and managing their distribution. Assessing if the order backlog could meet goals. Identifying the most and least productive technicians and assemblers. Determining which items could be delivered early to expedite invoicing. “I can’t believe how far we’ve come since starting this project.” EXPAND - THE SECOND MISSION Sights set on the stars with a Full Lifecycle Dashboard Interloop's next mission involved integrating production and shipment metrics for what would become a Full Lifecycle Dashboard. This robust enhancement provided our client with a comprehensive view of their business from sales through to production and shipment. Building on our solid foundation, we curated a fully automated Lifecycle Dashboard that spans sales, production, and shipment information - updated 8x per day, it provides near real-time insight into critical business functions. Additionally, PDF versions select dashboard pages are sent out once a week via email to designated members of the company to communicate the company’s performance. What used to take hours to export, compile, and format data to create these summary reports to share amongst leadership, now takes less than 5 minutes. “We went from a bulletin board with printed reports to a real time view displayed on a screen in the lab.” SKY IS THE LIMIT Growing Together, Celebrating Wins For us, this story is really the ideal evolution of a collaborative, curious client who came to us open and eager to expand potential and achieve more with their data. Starting from printed reports pinned to a bulletin board, our client now works from near-real time insights consistently communicated with automated distribution. What began as a singular department’s sales dashboard has since evolved into a true Mission Control platform leveraged daily to confidently across executive leadership to run and scale their venture. Today, Interloop is proud to continue supporting our client through iterations and enhancements to their Full Lifecycle Dashboard along with exploring options for migrating data into a more future-proof system that is cloud-based tomorrow. Interloop is a Microsoft ISV Partner at the forefront of helping manufacturing businesses across the country achieve more with their data. Ready to achieve more with your data? Let’s loop you in. Book your intro call with our data experts today.

Author: Will Austell When it comes to Customer Relationship Management (CRM) systems, maintaining data integrity is paramount. However, even with robust structures in place, challenges arise, such as the existence of orphan records. Stay with us as we delve into a practical solution based on a real client’s scenario using Python and SQL within a CRM's account module. The Challenge: Orphan Ship-To Accounts Interloop is working with a client that has a CRM system where accounts are categorized into Bill-To and Ship-To accounts, forming a parent-child hierarchy. Ideally, Ship-To accounts should always have a corresponding Bill-To parent. However, orphan Ship-To records, those without a Bill-To parent, can occur due to system limitations or human error. The Solution: Fuzzy Address Matching To address this challenge, Interloop proposed a solution leveraging Python's rapidfuzz library for fuzzy string matching and SQL for data manipulation to connect these orphan Ship-To records to an existing Bill-To parent record based on address matches. We will be working in a Spark notebook in Microsoft Fabric. Here's how it works: 1. Installing and Setting Up RapidFuzz First, we install the Rapidfuzz library, a powerful tool for string matching and similarity measurement, via pip. 2. Data Retrieval and Preparation We retrieve relevant data from the CRM database using SQL queries, focusing on Ship-To and Bill-To accounts within a specific region (e.g., EDOH in this example). These queries yield dataframes in a Spark environment, which we subsequently convert to Pandas dataframes for local processing. 3. Address Normalization Before comparison, we normalize the addresses of both Ship-To and Bill-To accounts by concatenating relevant address fields and applying lowercase conversion, stripping, and removal of non-alphanumeric characters. This step ensures uniformity for accurate matching. 4. Fuzzy Matching Using RapidFuzz, we iterate through each Ship-To and Bill-To pair, calculating a similarity score based on their normalized addresses. A threshold of 87% is set to consider matches, ensuring a balance between precision and inclusivity. The score threshold will vary and can be calibrated to meet your specific string-matching needs. In our example, we found the sweet spot was around 87% for optimal address matching. 5. Storing Matched Results Fuzzy matched results are stored in a delta table, preserving essential details such as IDs, account types, and dates entered. This structured storage facilitates further analysis and action. 6. Selecting Optimal Matches To mitigate redundancy, we select the highest scoring match for each Ship-To account, discarding lower-scoring alternatives. This step ensures the accuracy and efficiency of the matching process. Conclusion Incorporating fuzzy address matching into CRM data management workflows offers a pragmatic approach to address integrity challenges. By leveraging Python's rapidfuzz library and SQL for data manipulation, organizations can enhance the accuracy and completeness of their account records, thereby improving decision-making and customer service. In summary, through the integration of advanced matching techniques, the vision of a harmonized CRM dataset—free from orphan records—is within reach, ushering in a new era of data integrity and operational efficiency. Looking for clear, practical solutions to your data challenges? Let’s loop you in. Book your intro call with our data experts today.

Author: Anna Cameron Leveraging data for decision making begins with connecting to relevant data. However, what seems straightforward often proves to be complicated and time intensive. Factors like data volume, disparate data repositories across different platforms, and the lack of seamless data integration between different platforms can intensify the complexities that come with harnessing business data. More so, once data is cleaned, migrated, and accessible, it’s important to determine which type of connection is optimal for the given task. Here’s where Microsoft Fabric comes in. Microsoft Fabric offers a comprehensive suite of tools to streamline data connectivity and analysis. The selection of an appropriate method starts with understanding each method's strengths and limitations to ensure the best outcomes for diverse analytical scenarios. The three primary methods that can be used in Power BI include Import, DirectQuery, and the DirectLake. Each method carries advantages and drawbacks, so it’s essential to understand them all to see which aligns with your given analytics task. Import Importing data directly into a Power BI file is a relatively quick process that is conducive for smaller datasets. However, efficiency is tempered by its inability to sync real time data. The import process copies data tables from the lake house or warehouse and saves them in the Power BI file itself. Any modifications to the data source require manual importing of the data to reflect the changes in Power BI. To mitigate this limitation, scheduled refreshes can be used to ensure that data in the Power BI file is current. DirectQuery DirectQuery in Power BI offers a direct connection to the necessary data source which maintains data integrity and almost real-time data synchronization. Despite these advantages, this method encounters a performance trade off in slower analytics, particularly in scenarios with complex DAX calculations. DirectQuery functions by executing queries in the data source’s semantic model to retrieve data that fits the provided query. For example, a DAX query would be translated to a SQL query format to be run in the data source level. The result of that SQL query is then sent back to Power BI report where it can be used in a KPI visual. DirectQuery finds its niche in scenarios using large data sets where near real time data is more important that swift analytic processing. DirectLake DirectLake is a novel approach to data connection in Power BI. It essentially combines the advantages of import and DirectQuery while mitigating the respective limitations. By using parquet files sourced from Microsoft OneLake, DirectLake eliminates the need for query translation and bypasses the conventional data import, providing accelerated data access. Moreover, like DirectQuery, DirectLake ensures near real time data synchronization, making it a preferred choice for large data models where data changes frequently. Conclusion Using big data for decision making may be complex in business environments, but Power BI offers several techniques to make this possible by connecting through Import, DirectQuery + the DirectLake. Each method has its own advantages and limitations. Import mode is a relatively quick solution best for smaller data set, but is accompanied with the possibility of data staleness. On the other hand, DirectQuery and DirectLake are robust options for analysis of large data models where the analytics need to stay synced with changes in the data source. While DirectQuery can be a slightly faster method as it offers direct connectivity, it comes with the expense of slower analytics due to the need to translate queries between the data source and the Power BI file. DirectLake is a promising alternative that combines the strengths of import and DirectQuery while circumventing the need to translate queries. Ultimately, choosing the best connection method hinges on the specific requirements and nuances of the analytical task, ensuring that data-driven decisions are both informed and agile in response to dynamic business landscapes. Need help understanding and identifying which method is best for connecting your data with Power BI & Microsoft Fabric? Let’s loop you in. Book your intro call with our data experts today.