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university.jpg","associationType":"TEASER","width":512,"height":512,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNjYxMDQ1LTQxNTI2OWlGNTdFMTJBNTA2Qjg5OEQ2?revision=2\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNjYxMDQ1LTQxNTI2OWlGNTdFMTJBNTA2Qjg5OEQ2?revision=2","title":"LeeStott_1-1666688214857.png","associationType":"BODY","width":520,"height":503,"altText":null},"BlogTopicMessage:message:3661045":{"__typename":"BlogTopicMessage","subject":"Simulation game designed to train students to handle a bankruptcy case using Power Platform","conversation":{"__ref":"Conversation:conversation:3661045"},"id":"message:3661045","revisionNum":2,"uid":3661045,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:210546"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n Technology is transforming the education sector, increasingly helping teachers around the world to provide better, more interactive learning experiences. Dutch institution Avans Applied Science University is a prime example. Here, a law teacher (with no technical background) has recently created a simulation game designed to train students to handle a bankruptcy case as it would happen in real life. Built using Microsoft Power Platform, the game takes students through various steps of the case. All with the help of a chatbot created using Power Virtual Agents, which interacts with students and asks them legal questions. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":1866},"postTime":"2022-10-25T02:15:57.296-07:00","lastPublishTime":"2022-10-25T02:16:58.129-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" \n Avans university that is using Power Platform and a student challenge to champions technology awareness and adoption. \n \n \n \n Netherlands-based Avans University of Applied Sciences is a vocational institution located across three different cities: Breda, 's-Hertogenbosch, and Tilburg. The school has more than 30,000 students, and 40 courses taught in 18 institutes. \n This is something that teacher Frank van der Kruis finds highly appealing. A huge advocate of digital solutions himself, he’s eager to make teaching more dynamic and engaging. “As teachers, our task is to prepare our students for what awaits them outside the classroom,” he says. “But when it comes to teaching law, it’s hard to convey what the real world is about if your curriculum is limited by week-one, week-two-type of courses. That’s why I think the solution lies in new technologies: they allow us teachers to show them what real life can be about and spend more quality time with them.” \n \n \n \n A taste of real life \n Frank van der Kruis’s simulation game was built using a combination of Microsoft Power Automate, Forms and Excel. By logging into it from the university portal, students playing the role of liquidators can wander around the theatre and perform a range of tasks – from accessing its funds to examining its assets. So what is the challenge set to students? \n A local theatre has just filed for bankruptcy. As the liquidator assigned to the case, you are responsible for overseeing its assets, closure, future and anything in-between. You’ll have to deal with lawyers, the curator of the theatre, tons of paperwork, and a broad range of legal hurdles. All while making as few mistakes as possible, in the least amount of time. How are you going to ensure that everything is carried out correctly? And what kind of legal skills will you be required to use along the way? \n This is the assignment that Insolvency Law students at Avans University in the Netherlands have been tasked with by their tutor, Frank van der Kruis. But while tasks like this are found in written form on law courses across the world, van der Kruis has used technology to turn his assignment into an interactive simulation game that gives his students hands-on experience of managing the complexities of a real-life bankruptcy case. It’s a ground-breaking, transformational initiative that’s promising to revolutionize the teaching and learning experience at Avans University and beyond. \n “One of the greatest things for me as a teacher is to say that I’ve really prepared my students to become great professionals in the real world,” he says. “This game is a crucial part of that.” Throughout the game, they will also have to interact with a chatbot created through Microsoft’s Power Virtual Agents, which will help them move on with the story. As they reach various stages of the game, the chatbot will pose legal questions to the students, who can only move on by answering the question right. “Bankruptcy cases are all about interactions with third parties, but when you have 180 students playing the game, it’s not like I can hire actors,” he continues. “So we’ve created an extraordinary new chatbot that makes up for that role.” To keep track of their progress, van der Kruis is relying on a Power BI platform that uses a Power Automate flow to capture the data and save it in a Dataverse environment. The platform can then produce real-time dashboards that allow to check how students are doing, what kinds of questions they ask and more. “For me, one of the most important things is that the students can do their work at the time that they want,” he adds. “So when we built the chatbot, I saw students use it during the weekend or late at night. That means they can complete the course in their own time.” \n Democratizing digital learning for teachers and students \n Now in its fourth edition, Avans’ simulation game has helped to train more than 600 students, many of whom have described it as an authentic escape room experience. “This project is very new for them because they don't have to pass any real exam,” says Roel Steendijk. “That’s exciting but also very stressful and frustrating, and that’s really what this program is about. “It's about showing them that the real world is often frustrating. That you don't just apply the rule and go on. You have unforeseeable scenarios and different stakeholders and players.” \n Yet while students seem keen to give these solutions a try, convincing some teachers to do the same isn’t always as easy. \n “Not everyone is immediately sold on embedding simulations into their educational design,” he continues. “Some teachers still prefer their traditional assignment-based courses.” However, this is not stopping him and Frank van der Kruis from offering them a new, different perspective on teaching. “The great thing about Microsoft’s Power Platform range is that it’s designed to help teachers to solve their own problems, which are specific for them,” he concludes. “The fact that it has a low technical threshold means that we were able to build a complex simulation system and chatbot in just months. \n Technology is transforming the education sector, increasingly helping teachers around the world to provide better, more interactive learning experiences. Dutch institution Avans Applied Science University is a prime example. Here, a law teacher (with no technical background) created a simulation game designed to train students to handle a bankruptcy case as it would happen in real life. Built using Microsoft Power Platform, the game takes students through various steps of the case. All with the help of a chatbot created using Power Virtual Agents, which interacts with students and asks them legal questions. If your interestd in learning more, you can read this casestudy here. \n \n ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"5974","kudosSumWeight":1,"repliesCount":2,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNjYxMDQ1LTQxNTI2N2k1OEU0Q0MyRDM4MEYyNTBF?revision=2\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNjYxMDQ1LTQxNTI2OWlGNTdFMTJBNTA2Qjg5OEQ2?revision=2\"}"}}],"totalCount":2,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"coverImage":null,"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""}},"Conversation:conversation:4365279":{"__typename":"Conversation","id":"conversation:4365279","topic":{"__typename":"BlogTopicMessage","uid":4365279},"lastPostingActivityTime":"2025-01-23T00:00:00.016-08:00","solved":false},"User:user:2544588":{"__typename":"User","uid":2544588,"login":"MohamedFaraazman","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/dS0yNTQ0NTg4LTYyNjQyOWlGRjM1NUU0RkZBMjc5NTZD"},"id":"user:2544588"},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzY1Mjc5LWRTdmlvMg?revision=3\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzY1Mjc5LWRTdmlvMg?revision=3","title":"power-bi-vector-logo-1024x487.png","associationType":"COVER","width":1024,"height":487,"altText":""},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzY1Mjc5LUVIZjFLVQ?revision=3\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzY1Mjc5LUVIZjFLVQ?revision=3","title":"power bi.png","associationType":"BODY","width":1296,"height":627,"altText":""},"BlogTopicMessage:message:4365279":{"__typename":"BlogTopicMessage","subject":"Mastering Power BI: My Journey to Becoming a Microsoft Certified Power BI Data Analyst","conversation":{"__ref":"Conversation:conversation:4365279"},"id":"message:4365279","revisionNum":3,"uid":4365279,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:2544588"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":476},"postTime":"2025-01-23T00:00:00.016-08:00","lastPublishTime":"2025-01-23T00:00:00.016-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Hello Everyone, I’m Mohamed Faraazman bin Farooq S, a final-year Artificial Intelligence and Data Science student at BSA Crescent University, Chennai, India, and a Microsoft Learn Student Ambassador (MLSA). Today, I want to share my journey of earning the Microsoft Certified: Power BI Data Analyst Associate Certification —a challenging yet rewarding experience. Being part of the MLSA program provided me with access to valuable resources, tools, and a vibrant community that were instrumental in my preparation. \n Introduction to the Microsoft Power BI Data Analyst Associate Certification \n The Microsoft Certified: Power BI Data Analyst Associate certification validates your expertise in analyzing and visualizing data using Power BI, one of the most widely used tools for business intelligence (BI) and data analytics. This certification equips professionals to harness Power BI’s advanced features for data-driven decision-making, making it an excellent career booster for aspiring data analysts and BI professionals. \n Why Power BI Skills Are in High Demand \n The increasing reliance on data for strategic decisions across industries has made tools like Power BI essential. Power BI enables organizations to transform raw data into actionable insights with its robust data modeling, visualization, and report development capabilities. The PL-300 certification validates these skills, enhancing your career prospects, job security, and overall efficiency in data analysis roles. \n Overview of the PL-300 Certification Exam \n The PL-300 exam is designed for individuals with a foundational understanding of Power BI who wish to deepen their expertise. By earning this certification, you will: \n \n Collaborate effectively with stakeholders to understand business requirements. \n Clean and transform data to support informed decision-making. \n Develop optimized data models using Power BI tools. \n Create impactful data visualizations to communicate insights. \n \n \n Key Areas of Focus: \n \n Data Preparation: Learn to connect to diverse data sources, clean data using Power Query, and integrate it into Power BI for analysis. \n Data Modeling: Master DAX (Data Analysis Expressions) for building calculated measures and columns, and optimize data relationships. \n Data Visualization: Develop clear, impactful reports and dashboards, emphasizing storytelling through data. \n Asset Deployment: Manage datasets, configure data refresh schedules, and maintain workspaces in the Power BI environment. \n \n Preparation Tips and Study Resources \n To excel in the PL-300 exam, it’s crucial to understand Power BI’s features, functions, and real-world applications. Below are key topics and preparation tips to guide you: \n 1. Mastering Microsoft’s Ecosystem \n \n Power BI Service: Understand its integration with Microsoft 365 and Azure for data storage and security. \n Microsoft 365: Learn about organizational-level security and how it affects Power BI’s data access. \n Azure Integration: Familiarize yourself with Azure data storage and security features relevant to Power BI Premium. \n \n 2. Becoming Proficient in DAX \n \n Filter Context: Understand how DAX manages filter contexts for dynamic data modeling. \n Time-Series Functions: Master calculations over time for trend analysis. \n AI/ML Features: Explore Power BI’s machine learning and AI capabilities, although they are a smaller part of the exam. \n \n 3. Optimizing Performance \n \n Query Optimization: Use Power Query Editor for merging tables, filtering data, and automating data refresh. \n Data Modeling: Practice creating relationships, primary keys, and calculated columns for efficient models. \n Performance Tools: Learn Power BI’s built-in tools to enhance report processing. \n \n 4. Visualization Best Practices \n \n Appropriate Visual Selection: Choose visuals based on data type (e.g., bar charts for comparisons, line charts for trends). \n Storytelling: Focus on clear report navigation, formatting, and layout for effective data storytelling. \n \n 5. Hands-On Practice \n \n Practice DAX and Power Query: These are critical for real-world scenarios and frequently tested in the exam. \n Microsoft Practice Exams: Familiarize yourself with the format and assess your readiness through official practice exams. \n \n Domains Covered in the PL-300 Exam \n The exam is divided into four main domains: \n 1. Prepare the Data (25-30%) \n \n Data Sources: Connect to various data sources, including cloud platforms and databases. \n Data Transformation: Use Power Query for data cleansing and transformation tasks. \n \n 2. Model the Data (25-30%) \n \n Data Relationships: Define relationships and optimize data models. \n DAX Calculations: Create calculated columns and measures using DAX. \n \n 3. Visualize and Analyze the Data (25-30%) \n \n Report Design: Develop insightful reports using Power BI’s tools. \n Dashboard Creation: Create user-friendly dashboards for actionable insights. \n Analytics Features: Leverage analytics tools to identify trends and patterns. \n \n 4. Deploy and Maintain Assets (15-20%) \n \n Dataset Management: Organize and configure datasets effectively. \n Workspace Maintenance: Manage and deploy workspaces for efficient data sharing. \n \n Recommended Study Materials \n Microsoft offers a wealth of resources to prepare for the PL-300 exam: \n Microsoft Learn Paths: \n \n Data Analytics in Microsoft Power BI: Comprehensive modules tailored to each exam domain. \n DAX Fundamentals and Power Query: Detailed resources on essential tools for data transformation and calculations. \n \n Instructor-Led Training: \n \n Course PL-300T00-A: A three-day training that provides hands-on experience and targeted exam preparation. \n \n Practice Exams: \n \n Official Microsoft Practice Exams: Simulate the exam environment to build confidence and identify areas for improvement. \n \n Benefits of the PL-300 Certification \n Earning the PL-300 certification offers numerous advantages: \n \n Enhanced Career Prospects: Certified professionals often command higher salaries and better job opportunities. \n Diverse Job Roles: Pursue positions such as Data Analyst, BI Developer, or BI Consultant. \n Increased Efficiency: Streamline data processes and drive actionable insights for better decision-making. \n \n Conclusion \n The Microsoft Certified: Power BI Data Analyst Associate certification is a valuable milestone for data analysts aiming to excel in their careers. By mastering Power BI’s data wrangling, modeling, visualization, and optimization capabilities, you can position yourself as a key player in the data analytics field. With the right preparation, dedication, and access to Microsoft’s resources, success in the PL-300 exam is within reach. \n If you’re considering this certification, I encourage you to leverage the Microsoft Learn Student Ambassador program, just as I did, to achieve your goals. Best of luck on your journey to becoming a Power BI-certified professional! 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These Power BI AI features will 10x your productivity and quality of work ","introduction":"","metrics":{"__typename":"MessageMetrics","views":42159},"postTime":"2023-06-01T00:00:00.034-07:00","lastPublishTime":"2023-06-01T05:06:48.102-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" \n \n \n Gone are the days where all you are required to do as a Data Analyst is to create Reports and Dashboards for the business. We are now in the age of decision intelligence where you are required to directly support business decisions through the output from your Power BI Reports and Dashboards. \n \n To meet this level of demand and expectations, you need to start leveraging the AI capabilities in Power BI. In case you are not aware, Power BI has so many AI Features that will 10x your productivity and greatly improve the quality of your work. \n \n Let's Explore the AI Features together \n \n \n \n \n \n Before we explore the AI Features covered in this blog, kindly take few seconds to fill this Survey. We also have a joke for you at the end of the Survey: Kindly take few seconds to fill this survey about Power BI DAX \n \n \n Smart Data Discovery and Visualization in Power BI \n Power BI is rich in AI features; Smart Data Discovery and Visualization is one of them. While some people have used these features before, many do not know that it is enabled and delivered through the power of Artificial Intelligence. \n \n Smart Discovery enables Power BI to automatically discover and visualize your data. Let's have an example as can be illustrated below using a data in Power BI Service. \n \n \n \n This feature is also available in different forms within Microsoft Ecosystem. Let's look at the Data stored in SharePoint List below. \n \n \n \n Another way to see this in action is through Microsoft Teams. Let's look at Power BI Integration in Microsoft Teams and how the Smart Data Discovery and Visualization get the teams activity data analyzed and visualized. \n \n \n \n \n Natural Language Query (NLQ) in Power BI \n Natural Language Query in Power BI is magical. by directly typing your question, you can get quick answers and insights about your data. See how this feature is used via QnA in Power BI Service. \n \n \n \n \n \n Anomaly Detection in Power BI \n This feature can help quickly spot and detect any unusual or unexpected patterns/data points within your dataset. You can better detect and visualize Anomalies. This puts a lot of power in your hands. \n \n \n \n \n \n Key Influencers in Power BI \n A lot of Power BI Data Analysts are not familiar with this feature. Also, we have people that are aware of it but haven't used it before or not frequently. \n If I were you, I would use this over and over again because it can help me understand a lot about business. \n \n \n \n \n \n Decomposition Tree in Power BI \n Decomposition Tree Visual in Power BI is an artificial intelligence (AI) visualization. It can be leveraged for Ad Hoc exploration and conducting root cause analysis. \n You can you it to find the next dimension to drill down into based on certain criteria. \n \n \n \n \n Sentiment Analysis with AI in Power BI \n Perform sentiment analysis on your dataset without writing codes. This can be helpful when analysis customer survey with their feedback \n \n \n \n \n Forecasting with AI in Power BI \n Yes, you can also run forecasting with Power BI. In this example, we are forecasting for \"Total Defect\" items for the next couple of months. This predictive insight can help you prescribe measures to reduce the outcome. \n \n \n \n \n \n Additional Resources \n Power BI DAX Suggestion Project - https://aka.ms/DAXPowerBISession \n Enable DAX Suggestion in Power BI : https://aka.ms/EnableDAXSuggestion \n \n \n \n \n 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a Gantt Chart using Power BI","conversation":{"__ref":"Conversation:conversation:3605928"},"id":"message:3605928","revisionNum":11,"uid":3605928,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:1356577"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n Few weeks ago, I was tasked to build a Gantt chart, but I didn’t have a clue on how to do it. So, I did it the “Old fashion way” using excel sheet and adding all the adjustments manually i.e., \n colors, timeline, dates and tasks. I completed the task, but I felt there was a way around it and that was when I discovered a visualization on Power BI where you can build a Gantt chart is just a matter of minutes. Let’s breakdown the step-by-step process to achieve this. \n Don’t worry if this is new to you🙂. Let’s get to the introduction. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":164732},"postTime":"2022-08-29T23:44:45.919-07:00","lastPublishTime":"2022-08-29T23:44:45.919-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Introduction: What is a Gantt chart? \n This is a chart that is mostly used in project management visually representing projection timelines for the project and the tasks. This is a tool that clearly outlines tasks and to which teams they have been assigned to. This helps you to manage the whole project in an efficient manner by taking note of the projection timeline. You get to keep everyone on the same page from product managers, program managers, business analyst, developers etc. \n The main advantage of working with a Gantt Chart is that you get to plan, schedule, and execute your projects on just one chart. The other cool thing is you can track the progress by what has been completed, what is going on and upcoming tasks. \n \n Step 1: Using your excel table Gantt chart data You first need to format your excel datasheet into a table. To format as a table select the datasheet> on the home tab click on format as table. Once you have done so save the file (You can access the excel file I used for the demo here 😃) \n \n \n \n Step 2: Launch Power BI Desktop. If you already have Power BI desktop installed, open it. If not, download it from the official site. Power BI's landing page has 4 panes; Visualizations, Fields, Filters and working space where you will visualize the data. \n \n \n \n \n \n By default, you get these visualizations, so to access more visuals you need a license to them. \n \n Sign in with your office account (school or work account) to Power BI. If you don’t have one don’t worry about that, here is how to create a developers account \n Once we are signed in let's import our Gantt chart visual. \n \n Step 3: Import Gantt Chart visual to Power BI - On the visualizations pane click on the three dots (ellipsis) and select get more visuals. \n \n \n \n \n Search Gantt chart, then click Add. \n \n \n \n This success dialog box is displayed once the visual is successfully added. All good to go \n But first let's discuss the properties of a Gantt chart since this will come handy for the next steps and will really help you match the properties you have on the excel sheet with the properties in Gantt. \n \n \n Legend- this displays which category the project is, \n Task- this basically describes the project work to be done in a specified period of time \n Parent- this takes a summary of the child tasks that you have in your project \n Start Date- this describes the starting date of the project you are working on \n End Date- this describes the end date of the project you are working on \n Duration- timeframe for working on a particular project i.e., 3 months, 6 months etc. \n % Completion- the amount of task that has been completed in terms of percentage \n Resource - This is what you use in the project. For instance, you have developer resource, program manager resource, Business analyst resource etc. \n Tooltips - Text boxes that are displayed when a timeline or data grids are hovered over \n Milestones - this refers to the important or specific pointers in your project that describe the improvements or backlogs in a project \n \n \n \n These properties basically define the timelines, start date, etc. of the whole project, \n \n Step 4: Lets import our data \n On the Home tab and click on get data> choose Excel as your data source. Import the excel sheet you have stored locally. \n \n \n Select the table you had formatted to load your data into Power BI. Once you select the table you will see a preview of the data. Select load once you have ascertained the data is in the correct format. In case you would like to alter the format of the data, click Transform Data which will open the Power BI Query Editor on a separate window for you to modify your data before loading it into the Power BI project. \n \n \n \n We are all set! \n \n Step 5. Time to visualize! On the visualizations pane select Gantt chart to display a blank chart. Once you are done, we can now link our excel data to the properties of the Gantt chart. i.e., task (Excel) to match with task (Gantt), start date (Excel) and start date (Gantt) etc. This will depend on how you have named your excel columns \n \n \n \n \n \n Step 6: All done - We have been able to build our Gantt chart using Power BI. This will enable us to track the tasks that we have against time and the team members playing the different roles on different tasks. You can customize your chart further on other properties such as the title of the chart, background color, date type, data labels by using the tabs below the visualizations pane. \n \n \n \n \n Step 7: Save, Publish and Share - We can now share the chart with our colleagues. Save the chart and publish to desired workspace on Power BI Service. This will enable your workmate's view and collaborate on the chart you have shared with them. \n \n \n \n \n \n Next Steps \n Interested in learning more about the different types of visualizations that come with Power BI here are some resources that can help you explore: \n \n Visualization Types in Power BI \n What is Power BI? - Power BI | Microsoft Docs \n \n Interested in related content, register for the Power Platform Kenya Community today here. \n \n \n \n \n \n \n \n \n \n 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BlogTopicMessage:message:3848917":{"__typename":"BlogTopicMessage","subject":"Transforming Expense Management: Award-Winning Expense Tracker App at the Power Platform Hackathon","conversation":{"__ref":"Conversation:conversation:3848917"},"id":"message:3848917","revisionNum":5,"uid":3848917,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:1886716"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n Discover how the Expense Tracker App revolutionized expense management and emerged as the champion at the prestigious Global Power Platform Hackathon held in Nairobi. Explore its innovative features, seamless integration, and powerful analytics that enable businesses to track their sales expenses with ease and make informed financial decisions. Dive into the success story of this groundbreaking app and learn how it is reshaping the way organizations manage their finances. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":7765},"postTime":"2023-06-20T00:00:00.032-07:00","lastPublishTime":"2023-06-20T00:00:00.032-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Introduction \n Introducing our cutting-edge Expense Tracker App tailored specifically for sales professionals, revolutionizing the way you manage and submit your expenses. With its seamless user interface and powerful features, our app is designed to streamline the entire process, eliminating the hassle and time-consuming nature of expense management. Say goodbye to tedious paperwork and welcome a new era of efficiency and accuracy. From capturing receipts on the go to generating comprehensive expense reports with just a few taps, our Expense Tracker App empowers you to take control of your financial records effortlessly. Maximize your productivity and focus on what truly matters - closing deals and exceeding targets. Experience the future of expense tracking and unlock a world of convenience with our game-changing app. \n \n Scenario \n Sarah, a dedicated sales representative, has just returned from a productive business trip. As she settles back into her office, she realizes that she needs to submit her expense report for the trip. In the past, this task would have been time-consuming and frustrating, involving stacks of receipts, manual calculations, and tedious paperwork. \n \n However, this time, Sarah decides to leverage the power of the Expense Tracker App. With a few taps on her smartphone, she effortlessly captures photos of her receipts, instantly digitizing them and eliminating the risk of losing important documents. \n As Sarah reviews her expense entries, she notices that the app automatically categorizes expenses based on predetermined settings, saving her valuable time. She can easily customize categories or add additional details for more precise reporting. The app also allows her to attach notes and comments to each expense, providing valuable context to her finance department. \n \n Impressed by the app's intuitive interface, Sarah proceeds to generate her expense report with a single tap. Within seconds, a comprehensive and professional report is generated, complete with itemized expenses, totals, and any necessary supporting documentation. \n \n With her expense report ready, Sarah securely submits it directly from the app to her finance team. She appreciates the app's integration capabilities, which seamlessly connect with her company's expense management system, ensuring a smooth and efficient workflow. \n Thanks to the Expense Tracker App, Sarah has reclaimed precious hours that she can now devote to nurturing client relationships and closing deals. She appreciates the app's ability to transform a previously cumbersome task into a streamlined and enjoyable experience, leaving her confident in her financial records and impressed by the app's user-friendly design. \n In this scenario, the Expense Tracker App has revolutionized Sarah's expense management process, empowering her to stay organized, save time, and focus on what she does best – driving sales success. \n \n The Solution \n The Expense Tracker App is a comprehensive solution built using the power of Microsoft's Power Platform suite of tools, which includes SharePoint Lists, Power Automate, Power BI, and other Power Platform components. Let's delve into each of these components and how they contribute to the functionality and effectiveness of the app: \n \n SharePoint Lists: SharePoint Lists serve as the backbone of the Expense Tracker App, providing a robust and flexible data storage mechanism. The app utilizes SharePoint Lists to store and manage various data elements, such as expense entries, receipts, user profiles, and expense categories. SharePoint Lists enable seamless collaboration, data organization, and secure access control, ensuring data integrity and consistency. \n \n Power Automate: Power Automate, an integral part of the Power Platform, automates and orchestrates business processes. In the Expense Tracker App, Power Automate enables seamless integration and workflow automation. For instance, when a user submits an expense entry, Power Automate can trigger automated notifications to the finance team, initiate approval workflows, or generate email alerts for specific actions. This streamlines the entire expense management process, reducing manual effort and improving efficiency. \n \n Power BI: Power BI empowers the Expense Tracker App with dynamic and interactive data visualization capabilities. By connecting to the SharePoint Lists that store expense data, Power BI allows users to generate insightful reports and dashboards with just a few clicks. Sales professionals and finance teams can leverage these visualizations to gain valuable insights into spending patterns, track key metrics, and make data-driven decisions. Power BI's intuitive interface and customizable reporting features enhance the overall user experience and provide a clear overview of expense-related information. \n \n Power Apps: Power Apps enables the creation of custom, user-friendly interfaces for the Expense Tracker App. It allows developers to design intuitive forms, screens, and user interactions tailored to the specific needs of sales professionals. With Power Apps, users can easily navigate through the app, capture receipts, enter expense details, and review their submissions. The flexibility of Power Apps ensures a seamless user experience across various devices, including desktops, tablets, and mobile devices. \n \n The integration of these Power Platform components results in a powerful Expense Tracker App that revolutionizes expense management for sales professionals. It leverages SharePoint Lists for data storage, Power Automate for workflow automation, Power BI for data visualization, and Power Apps for a user-friendly interface. This combination of Power Platform tools enhances efficiency, accuracy, and productivity, ultimately enabling sales professionals to focus on driving sales success while effortlessly managing their expenses. \n \n Database \n We opted for the SharePoint List database because of its ease to integrate with power platform and security. \n We created a list (Expense Tracker102) with ten columns namely: Employee Name, Date, Travel Destination, Travel Mode, Hotel Name, Amount, Other Spends, Created By, Attachment, and Status. \n \n The “Employee name” column shows the purpose of the travel whether it is a trip, conference, meeting etc. \n The “Date” column indicates the date scheduled for the travel. \n The “Travel Destination” column shows the destination of the travel. \n “Travel mode” column indicates whether the traveler will travel by air, road or train. \n “Hotel Name” column to show the hotel where the employee will reside. \n “Amount” column to indicate the total amount spent. \n “Other Spends” column includes any other spends apart from the included expense. \n “Created by” column to show who created that particular expense. \n “Attachment” column for any attached receipts. \n “Status” column to show whether the expense has been approved, rejected or pending. \n \n \n \n Diagram 1: SharePoint List ½ \n \n \n Diagram 2: SharePoint List 2/2 \n \n Architecture Diagram \n \n \n Diagram 3: Architecture Diagram for Expense Tracker \n \n How the Power Apps Works \n The power of Power Apps comes to life as we delve into the inner workings of our Expense Tracker application. Leveraging the encrypted SharePoint list as our foundation, we have crafted a seamless user experience that ensures secure access and optimal functionality. \n As users launch the app, they are greeted with an elegantly designed login page illustrated below, setting the stage for a personalized and secure experience. To maintain the utmost security and exclusivity, only registered users with their information stored in our database can gain access. This authentication process guarantees that only authorized individuals can enter the app and engage with its powerful features. \n We understand that sometimes passwords can slip from memory's grasp. Fear not, for we have anticipated this possibility and provided a solution. Should a user find themselves locked out due to a forgotten password, a straightforward pathway to resolution awaits. By simply reaching out to the dedicated admin, password resets can be swiftly arranged, ensuring a smooth reentry into the world of expense tracking. \n Our meticulous attention to detail and unwavering commitment to user experience shine through in every aspect of the app. With carefully chosen words and a touch of sophistication, we have crafted an environment where security, convenience, and seamless functionality converge, making the Expense Tracker application a truly exceptional tool for modern expense management. \n \n \n Diagram 4: Expense Tracker Login Page \n \n Once the user successfully logs into the app, they will be granted access to a wealth of valuable information. A dedicated page awaits them, displaying a comprehensive overview of their past expense submissions. This intuitive interface not only allows users to review their previous entries but also empowers them with the ability to make necessary edits and updates as needed. \n Within this dynamic page, a range of powerful functionalities becomes readily available. Users can effortlessly search for specific expense records, swiftly locating the information they seek. Furthermore, the option to add new entries seamlessly integrates into the user interface, ensuring a streamlined process for capturing and documenting new expenses. The list itself remains adaptable and responsive, providing a refreshing \"refresh\" feature that instantly updates the displayed information. \n To further enhance usability and organization, a convenient sorting capability has been implemented. With a simple tap, users can arrange their expense list in alphabetical order, ensuring clarity and ease of reference. This intelligent feature allows for quick and efficient browsing of past submissions, ultimately saving valuable time and effort. \n \n \n Diagram 5: Expense Tracker History Page \n \n If the user wants to add a new request, then they can submit it here. \n \n Diagram 6: Expense Tracker New Submission Page \n \n After the submission the user can then view their submission. \n \n Diagram 7: Expense Tracker Submission Page \n \n Business process configured on Power Automate \n We implemented business logic in the app using Power Automate. The flow is triggered by email notifications when a new expense is added or when an expense exceeds a certain amount. We also created a workflow to update a status column when an expense is approved or rejected. \n \n \n Diagram 7: Expense Tracker Workflow 1/2 \n \n An email is sent to a manager for approval. \n \n Diagram 8: Expense Tracker Workflow 2/2 \n \n Upon approval, a confirmation email is sent to the user. \n \n Diagram 9: Expense Tracker Email Trigger Notification \n \n On the Approval button the status of the expenses is displayed whether it has been approved or rejected. \n \n Diagram 10: Expense Tracker Notifications List \n \n Data Analytics with Power BI \n We utilized Power BI to generate dynamic visualizations and reports using our expense data. By connecting to the SharePoint list, we developed a dashboard containing interactive charts and graphs that allow for detailed analysis of our spending patterns. The visuals can be easily filtered based on various parameters such as Employee Name, Travel Destination, Travel Mode, Date, Hotel Name, Amount, Other Spends, Status, Created By, and Attachment. \n \n \n Diagram 11: Power BI Interactive Dashboards \n \n Summary \n Creating an expense tracker app using Power Platform was a seamless and efficient process. With the help of Power Apps, SharePoint list, Power Automate, Power BI, and Outlook, we were able to design a custom user interface, connect to our data source, implement business logic, analyze our expenses, and integrate with Outlook. By tracking our expenses, we could easily stay on top of our finances and make informed decisions. With the help of Microsoft Power Platform, anyone can create a custom expense tracker app that suits their personal or business needs. \n One of the key highlights of the Expense Tracker App is its ability to create interactive visualizations and reports using Power BI. Users can leverage this feature to gain valuable insights into their spending patterns. The dashboard showcases charts and graphs that can be customized and filtered based on different parameters such as employee names, travel destinations, dates, and more. This flexibility allows for a granular analysis of expenses, helping users identify trends, outliers, and areas where cost optimization is possible. \n \n Furthermore, the Expense Tracker App incorporates advanced filtering options, making it easier to navigate and explore expense data. Users can quickly filter expenses based on specific criteria such as employee names, travel modes, and attachment availability. This enables targeted analysis and a deeper understanding of expenditure in specific areas. \n \n Overall, the Expense Tracker App empowers users to take control of their finances by providing a comprehensive platform for expense management. Its integration with Power BI facilitates data-driven decision-making through interactive visualizations, while its robust filtering capabilities ensure efficient exploration of expense data. With this app, individuals and businesses can optimize spending, improve budgeting, and ultimately achieve their financial goals. \n 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with Power BI","conversation":{"__ref":"Conversation:conversation:4225560"},"id":"message:4225560","revisionNum":3,"uid":4225560,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:1825911"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" Technology has been rapidly evolving to help users from different backgrounds achieve their goals with maximum efficacy. \n Imagine unlocking the secrets hidden within your data, where every chart and visualization tells a story yet to be discovered. \n What if the key to better business decisions lies just beyond one click, thanks to one of the features of Power BI? \n In this blog, we will dive into the world of analytics with Power BI where insights are uncovered. we will discover how Power BI can transform raw data into more comprhensive useful one. \n Ready to discover what your data isn't telling you yet? ","introduction":"","metrics":{"__typename":"MessageMetrics","views":6288},"postTime":"2024-08-29T00:00:00.044-07:00","lastPublishTime":"2024-08-29T00:00:00.044-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Data Analytics \n Analytics can transform raw data into an extensive collection of information that categorizes data to identify and analyze behavioral data \n and patterns. Data analytics consists of converting raw data into actionable insights. \n Although having data analytics competencies may be required for some job and optional for others, it makes all data related work easier. If you are a data scientist, for example, a quick and informative analysis could give you an idea related to preprocessing and to the modeling algorithm. \n Data analytics has several benefits for different segments such as: \n \n Organization: By examining historical data and recognizing trends, businesses can gain a better understanding of their customers, market conditions and products. Analytics has capacity to help with informed decision-making leading to cost effectiveness. \n \n \n Developers: data analytics help in getting insights into how to develop the business. \n \n \n Product: data analytics may help in product design and feature development. \n \n Previously, data analytics was a complex task. However, thanks to technological advancement, new tools were developed to support accessibility and its comprehension by, many people across all teams despite their technical backgrounds. One of these tools is Power BI developed by Microsoft. \n \n \n Power BI for Data Analysis \n Power BI is an exceptional tool for quickly pulling actionable insights from data. It allows you to build visuals (as well as specifying new measure metrics) for your data in reports and dashboards which could be shared to gather insights at a high level to get more detailed information. We have: \n \n Power BI Desktop: Desktop is a complete data analysis and report creation tool that is used to connect to, transform, visualize, and analyze data. \n \n \n Power BI service: a cloud-based service, or software as a service (SaaS). Teams and organizations should use it because it facilitates report editing and collaboration. You can connect to data sources in the Power BI service, too, but modeling is limited. \n \n In this blog, we are going to work with Power BI Desktop: Download Power BI Desktop \n \n The data can be downloaded from: Financial Data or imported directly from Power BI Desktop available samples. \n \n \n Analyzing data has been always correlated with statistics that show distribution or helps in detecting outliers, for example. Exploring the statistical summary gives you a high-level view of the available data, where you can remarque clusters, discover patterns on behavioral data, calculate data averages, min, max and more. Based on this need, Power BI has many functions that guide in conducting a statistical analysis, such as Data Analysis Expressions (DAX) functions and visuals (histograms and bell curves…). \n The list below presents some types of visualizations: \n \n Histograms can be used to depict the frequency distribution of variables in a dataset. For example, we use the column chart visual to present a histogram that determines the sum of sales per country. \n \n \n 2. Charts Bar or column chart visual in Power BI relates two data points: a measure and a dimension. It only visualizes a single data point and to compare discrete or categorical variables in a graphical format. \n \n Histograms and bell curves (distribution charts) are the most common way to display statistics about the semantic models. In Power BI, you can represent a histogram with one of the bar or column chart visuals and represent a bell curve with an area chart visual, as illustrated in the following image. \n \n \n \n \n 3. Statistical functions| Data Analysis Expressions (DAX): calculate values related to statistical distributions and probability, such as standard deviation (StdevP) and max (Max) (👉 statistical_functions and function-aggregates) TOPN: one of the most known DAX functions. It returns the top N rows of a specified table(dataset). The Top N analysis is a great way to present data that might be important, such as the top 10 selling products, top 3 employees in an organization, or top 1 dangerous contamination. On the other hand, it may present the bottom N items in a list such as the worst sellers. It depends on your perspective and business requirements. In this example, we visualized respectively the top 10 countries by sales and top 10 countries by discounts \n \n \n \n \n \n Also, you can apply a new customized filter in the Filter section. In this example, we visualized the countries with Sum of Gross Sales (Variable) greater than (Operation) 25M (threshold). \n \n \n Outliers Identification with Power BI Visuals \n We define an outlier as a type of anomaly in the data, something unexpected or surprising, based on historical averages or previous normal results. It is important to identify outliers to isolate data points that significantly differ from other data points to not bias the future model and insights. Then, we need to take action to investigate the reasons for the presence of those outliers. The results of this analysis can make a significant impact on business decision making. \n \n Let’s consider our scenario, where we are analyzing units sold by country. The countries that stand out in terms of units sold are the ones we want to take note of. \n To that point, Power BI allows you to identify outliers in your data. The process involves: \n \n Segmenting data into two groups: the outlier data | normal data \n \n \n Use calculated columns to identify outliers à results would be static until à refresh the data. Solution: use a visualization or DAX function. These methods will ensure that your results are dynamic. \n \n \n After identifying outliers, you can use slicers or filters to highlight them. \n \n \n Add a legend to your visuals so that the outliers can be identified among the other data. \n Dive deeper into the reasons for outlier’s presence to gain more insights. For example, in our case sum of units sold and discounts by country. Why has the sum of units sold in the country been different from others? What are the reasons behind the difference? Was there any inflation or economic perturbation during a specific period in this country? Why, despite discounts, was the sum of units sold not important? What is the specificity that may impact the value of the units sold? We can also use a DAX function to add information related to variance. \n \n Clustering Techniques in Power BI \n Clustering is used to identify groups of similar objects in datasets with two or more variable quantities. It outputs a segment (cluster) of data that is like each other but dissimilar to the rest of the data. \n \n \n The Power BI clustering feature allows you to analyze your semantic model to identify similarities and dissimilarities in the attribute values, and then it separates the data that has similarities into a subset of the data. These subsets of data are referred to as clusters. \n In our example, we look for patterns in our financial data, such as sales overview. We segmented the countries into clusters according to their similarities: Sum of units sold by segment. \n \n Start by adding the scatter chart visualization to the report. \n Add the required fields to the visual. In this example: sum of units sold field to the x-axis, the sum of sales Sales field to the y-axis and Segment to the Legend field. The following image shows clusters in the scatter chart, so it is difficult to discern any natural groups. Here we plot sum of units sold and sum of sales by segment. \n \n \n \n \n Time Series Analysis with Power BI \n For as long as we have been recording data, time has been a crucial factor. In time series analysis, time is a significant variable of the data. Times series analysis helps us study our inputs and learn how we progress within it :right_arrow: Dynamic data. \n \n Time series analysis often involves visuals like Gantt charts, project planning, and stock movement semantic models. In Power BI, you can use visuals to view how the data is progressing over time, which in turn allows you to make observations like whether any significant occurrences affected your data. \n Suitable visualizations in Power BI for Time Series analysis: line chart, area chart, or scatter chart because they are particularly useful for representing cumulative data over time and can be customized to highlight specific aspects of the time series. \n Additionally, Microsoft AppSource has an animation custom visual called Play Axis that works like a dynamic slicer and is a compelling way to display time trends and patterns in your data without user interaction. In our example we: \n \n Add a scatter visual to the report page to show the sales data by product during the months. \n Import the animation custom visual from Appsource to use with the visuals. Visualizations pane :right_arrow: Get more visuals icon :right_arrow: Get more visuals. On the Power BI Visuals window :right_arrow: search Play axis :right_arrow: Add Play Axis (Dynamic Slicer) visual. \n Select the field Quarter (e.g., Month) that you want to use as the slicer in the Play Axis animation. \n Animation controls become available on the visual. An animation will be displayed such showing in our examples: \n \n \n \n Analyze Feature in Power BI \n The Analyze feature provides you with additional analysis that is generated by Power BI for a selected data point. This feature is useful to discover the insights provided by PowerBI that you may miss. It may be considered as a starting point for analyzing why your data distribution looks the way that it does. \n Instead of exploring the data manually, you can use the Analyze feature to get fast, automated, insightful analysis of your data. To use the Analyze feature: \n Click a data point on the visual à hover over the Analyze option to display two further options depending on the data point selected: \n \n \n Explain the increase: when your focus is on understanding the reasons behind a change in a specific metric. This is especially relevant when a single data point has changed noticeably, and you want to know why. for exploring reasons behind specific changes in data points \n Find where the distribution is different: when your focus is on comparing how data is distributed across different categories or groups. This is more about understanding differences in patterns or behaviors across subsets of your data, rather than focusing on a single change for analyzing and comparing distributions across categories or groups. In our example where we analyze sum of sales by country: \n \n \n \n If you find any of the provided analysis useful, you can add it to your report so that other users can view it. Here, we found that segment analysis is useful, because it demonstrated the sum of sales of government per country. \n \n \n What to Explore Next? \n AI and Power BI \n Power BI includes several specialized visuals that provide a considerable interactive experience for report consumers. Often, these specialized visuals are called AI visuals. \n Why? \n Because Power BI uses machine learning (ML) to discover and display insights from data. These visuals provide a simple way to deliver an interactive experience to your report. \n For further reading, the three main AI visuals are: \n Key influencers \n Decomposition tree \n Q&A \n \n References: \n Benefits-of-data-analytics. \n What is Clustering?. \n How-To-create-Distribution-Chart-Bell-chart-in-Power-BI \n Grouping-and-binning-PowerBI \n PowerBI Service vs Desktop \n 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to use Azure Open AI to Enhance Your Data Analysis in Power BI","conversation":{"__ref":"Conversation:conversation:4041036"},"id":"message:4041036","revisionNum":16,"uid":4041036,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:1269304"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" Learn how to take your data analysis to the next level with Azure Open AI. This article provides step-by-step guidance on how to integrate Open AI with Power BI and Azure Machine Learning. Enhance your data insights and make better-informed decisions. Read now to take advantage of the latest innovations in data analysis. \n \n ","introduction":"","metrics":{"__typename":"MessageMetrics","views":24589},"postTime":"2024-01-29T12:11:32.415-08:00","lastPublishTime":"2024-02-01T03:27:40.147-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Data is the new currency of the modern world, and to succeed in this competitive field, you need to master data concepts and tools. This blog will show you how artificial intelligence (AI), especially Azure Open AI, can transform your data decision-making process within Power BI. Azure Open AI is a cloud-based AI service that uses pre-trained models to generate new content. You can pay for the service with tokens and benefit from features like cloud security and identity management. Azure Open AI has many applications, including content generation, sentiment analysis, machine translations, and automation. Whether you are a business analyst, a researcher, or a data enthusiast, Azure Open AI can help you achieve your data goals. Join us as we dive into these fantastic possibilities in the next section. \n \n 1. Architecture \n \n \n \n 2. Azure Open AI creation \n \n Creating Azure OpenAI involves a series of steps that build on the principles of Cloud Native architecture. Here's a simplified guide on how to create Azure OpenAI: \n \n Set up Azure Cloud: Start creating an Azure account if you haven't already. Sign in to the Azure portal using your Azure account credentials. \n Create a Resource: To deploy an Azure service, you must create a resource. A resource represents a service or component in Azure, such as a virtual machine, a storage account, or a database. Click on the \"Create a resource\" button in the Azure portal. \n Select Azure OpenAI Service: You'll see a list of available Azure services in the resource creation wizard. Choose Azure OpenAI Service by browsing the categories or searching the search bar. \n Configure the Resource: Once you've selected Azure OpenAI Service, you'll be taken to a configuration page where you can specify the settings for the resource. Fill in the required information, such as resource name, region, pricing tier, and other relevant settings. \n Review and Create: After configuring the resource, review the settings to ensure they are correct. Once satisfied, click the \"Review + Create\" button. \n Validation and Deployment: Azure will validate the configuration settings and check for potential issues. If everything is in order, click the \"Create\" button to initiate the deployment process. \n Monitor the Deployment: Azure will start provisioning the resources based on your configuration. You can monitor the deployment progress in the Azure portal. The deployment may take a few minutes to complete, depending on the service. \n Access and Manage the Deployed Service: Once the deployment is finished, you can access and manage the deployed service through the Azure portal. You can view its properties, make changes to its configuration, monitor its performance, and perform other administrative tasks as needed. \n \n 3. Azure OpenAI Service Building Blocks \n \n The Azure OpenAI Service Building Blocks are the core components and tools for creating and managing generative AI solutions. They include: \n \n Visual Interfaces: Azure OpenAI Studio and Playground offer user-friendly interfaces for testing, customizing, and deploying AI models without coding. \n Development Interfaces: APIs and SDKs enable the integration of Azure OpenAI's advanced capabilities into any application. \n Management Features: Deployments, Content Filters, Models, Data Files, and Quotas, which provide users with control over various aspects of their AI implementations. \n \n In this blog, we will focus on using the Visual Interfaces of the Azure OpenAI Service, namely Azure OpenAI Studio and Playground, which offer user-friendly interfaces for testing, customizing, and deploying AI models without coding. \n \n 3.1. Azure OpenAI Studio and Playground \n \n Azure OpenAI Playgrounds are applications within the service that let users interact and customize various AI models, including chat-based models like ChatGPT, non-chat language models, and image generation models. These interfaces simplify generative AI models, especially for non-technical users. \n \n \n \n You can access each Playground (and their related management features) from the left panel of the Studio or visit them directly by following URLs linked in the following sections. \n \n 3.2. Chat Playground \n \n The Chat Playground is a feature within the Azure OpenAI Studio. It provides an interactive interface for users to test and configure the behavior of the chat-based AI models. The main components of the Chat Playground include: \n \n Assistant Setup: This area allows users to configure the chatbot's behavior. Users can choose from templates or create their custom system messages. \n Chat Session: The main interaction point between the user and the chatbot. Users can type their queries here, and the chatbot responds accordingly. \n Deploy to: This option allows users to deploy their chatbot to a specific platform or environment. Azure OpenAI Studio enables direct deployments of both Azure Web Apps and Power Virtual Agents. \n Configuration: This area provides options to access deployment and session settings. Users can also clear the chat history and manage parameters related to the chatbot's deployment. This Playground is handy for developing and refining chatbot applications, as it allows users to test and adjust the chatbot's performance and responses iteratively. \n \n \n \n 3.3. Deployments \n Deployments provide endpoints to the Azure OpenAI base models, or your fine-tuned models, configured with settings to meet your needs, including the content moderation model, version handling, and deployment size. You can view your deployments from this page, edit them, and create new ones. \n \n \n 4. Retrieve key and endpoint. \n \n You need an endpoint and a key to make a call successfully against Azure OpenAI. \n \n \n \n \n Variable name \n \n \n Value \n \n \n \n \n ENDPOINT \n \n \n This value can be found in the Keys & Endpoint section when examining your resource from the Azure portal. Alternatively, you can find the value in the Azure OpenAI Studio > Playground > Code View. An example endpoint is https://xxxxxxxxxx.openai.azure.com/. \n \n \n \n \n \n \n \n 5. Python script \n We can copy the Python code from the Playground to use our model API in our Python code (JSON and CURL are also available). This code will import the required library and export our parameter settings. We will also create a Power BI report and use Azure Open AI to generate insights from the data. Before we begin, we need to complete some steps: \n \n Install Python and enable Python in Power BI: \n \n First, install Python if you have not done so already. Please visit the official website (https://www.python.org/downloads/) to download it. We recommend versions 3.9 and 3.10. \n Once Python has been installed, enable Python scripting in Power BI. To do so, open Power BI Desktop. Then, click File > Options and go to Settings > Options > Python scripting. Select the checkbox and click OK. \n Next, set the Python path in Power BI. Go to File > Options and Settings > Options > Python scripting. Here, click Detect. This selects the Python installation path automatically. You can do this manually by clicking the ellipsis (…) and selecting the Python executable file. \n Restart Power BI Desktop for the changes you made to take effect. \n Install the SDK with a package manager such as pip: \n \n \n Pip install openai \n 2. Now, we need to create a dataset to analyze. Follow these steps: \n 1. Import your data and choose Transform Data \n \n \n 2. You can check the column quality to see if there is something wrong with data quality or empty cells, which can lead to false insight \n \n \n 3. Add Run Python script to the Applied Steps section. \n 4. Now, we can run the code in the next section directly into Power BI. \n 1. To start, import the necessary Python libraries \n \n # Import Libraries\n import os\n import openai\n \n \n # Set OpenAI API for Azure\n openai.api_type = \"azure\"\n openai.api_base = \"https://xxxxxxxxxx.openai.azure.com/\"\n openai.api_version = \"2023-07-01-preview\"\n openai.api_key = \"xxxxxxxxxxxxxxxxxxxxxx\"\n \n \n # Loop through each row in Renamed Columns & concatenate the data into a single string. Pass resulting string to the API\n for index, row in Renamed_Columns.iterrows():\n messages = [\n {\n \"role\": \"system\",\n \"content\": \"For each company, I will give you the followwing information: Company, Price to Earnings, Price to Book, Return to Equity%, Debt to Equity, Current Ratio, Gross Margin%. Then, I will analyze the ratios and write a brief summary using the company name \"\n },\n {\n \"role\": \"user\",\n \"content\": ''.join([str(col) for col in row])\n }\n ]\n # Make a chat completion Request for the API\n chat = openai.ChatCompletion.create(\n engine = \"GPT-35-turbo\",\n messages = messages,\n temperature = 0.7,\n max_tokens = 800,\n top_p = 0.95,\n frequency_penalty = 0,\n presence_penalty = 0\n )\n # Process the response from API\n reply = chat.choices[0].message.content\n # Write the response Back to the Report\n Renamed_Columns.at[index, \"reslt\"] = reply\n \n \n \n \n This script runs a Python code that iterates over the Power BI table rows and builds a prompt for ChatGPT using the report data. The prompt is sent to ChatGPT, and the API response is returned to the Power BI DataFrame and table for each row (company). \n 2. Expanding the table means turning a column with tables inside it into multiple columns and rows. This can help you flatten your data and make it easier to analyze. \n \n \n \n 6. Build the report with Power BI \n In the Power BI desktop, you can use the slicer visual to select the company and the table visual to view the generative insight of the data according to the field you choose. \n \n \n \n \n Congratulations on completing this tutorial blog on How to use Azure Open AI to Enhance Your Data Analysis in Power BI; you have learned how to use Azure Open AI to enrich your data analysis in Power BI. You have discovered how Azure Open AI can create new content based on the dataset using a Python script. Azure Open AI is a versatile tool that can help you leverage your data and make smarter decisions. Whether you are a business analyst, a researcher, or a data enthusiast, Azure Open AI can help you gain data skills and insights. We hope you found this blog helpful and informative. \n \n 7. Resources \n \n \n Azure OpenAI Service fine-tuning gpt-3.5-turbo - Azure OpenAI | Microsoft Learn \n Run Python scripts in Power BI Desktop - Power BI | Microsoft Learn \n Visualization types in Power BI - Power BI | Microsoft Learn \n 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to build an End-to-End Analytics Solution with Lakehouse in Microsoft Fabric","conversation":{"__ref":"Conversation:conversation:4029704"},"id":"message:4029704","revisionNum":6,"uid":4029704,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:1835800"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" Discover the seamless integration of Lakehouse architecture within Microsoft Fabric to revolutionize your analytics from start to finish. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":10580},"postTime":"2024-01-16T00:00:00.050-08:00","lastPublishTime":"2024-01-16T00:27:50.882-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Architectural Setup \n \n \n \n Introduction Data is the new oil, and data analytics is the key to unlocking its value. Data analytics can help organizations to gain insights, make decisions, and optimize outcomes. However, data analytics is not a simple task. It involves various challenges, such as data quality, data integration, data processing, data modelling, data visualization, and data governance. \n To address these challenges, Microsoft Fabric offers a comprehensive suite of services for data engineering, data science, data warehousing, real-time analytics, and business intelligence. \n \n \n Scenario Imagine you are a chef who wants to create delicious dishes using various ingredients and recipes. You have a kitchen with all the tools and appliances you need, such as a stove, an oven, a blender, a mixer, etc. You also have access to a pantry where you can store and retrieve different kinds of food items, such as grains, fruits, vegetables, meats, dairy, etc. You want to share your culinary creations with your customers and get their feedback and ratings. Microsoft Fabric is like your kitchen and pantry, where you can cook up data solutions using various tools and services, such as Azure Synapse, Azure Data Factory, Power BI, etc. You can also store and access different kinds of data items, such as structured, unstructured, batch, streaming, etc. You can also share your data insights and reports with your stakeholders and get their feedback and ratings. In this blog, you will learn how to use Microsoft Fabric to create an end-to-end analytics solution using Lakehouse. You will also learn how to address some of the common challenges and considerations when working with data, such as: \n \n How to create and manage a Lakehouse that can store and process data of any scale, type, and structure \n How to ingest, transform, and load data from various sources and formats into your Lakehouse \n How to perform data engineering and data science tasks \n How to query and analyze data using SQL and Spark \n How to create and share interactive reports and dashboards using Power BI \n \n \n Pre-requisites \n \n A Microsoft 365 Developer Account with Admin rights. \n A Microsoft Fabric Free Trial \n \n How to create and manage a Lakehouse \n The following steps are the steps to setup a Lakehouse in Microsoft; 1. Create a Fabric workspace: A workspace is a place where colleagues collaborate to create items such as Lakehouse, warehouses, and reports. From the experience switcher located at the bottom left, select the Data Engineering Experience. \n \n \n \n “My Workspace” is your own default workspace, it’s where you will always be the sole Owner of the content and experimenting how items work without affecting items that the rest of collaborators have access to, for now ignore that and Select workspaces and new workspaces. \n \n \n \n Fill out the create workspace form with the following details: \n \n Name: Enter a unique name for your workspace \n Description: Enter an Optional description for your workspace \n Advanced: Under License mode, select Premium capacity and then choose a premium capacity that you have access to. Select apply to create and open the workspace. \n \n \n \n Note: Every fabric item you create will be stored in the open workspace by default, be sure to change to another workspace if you want the item to be stored to a different workspace by navigating to the workspaces tab and selecting the workspace into which you want to store your fabric items. \n \n 2. Create a Lakehouse: Navigate to the workspace you created earlier and from the top navigation ribbon, select new, from the item drop down menu, select Lakehouse. \n \n Congratulations, you now have your Lakehouse set up. Next, you will ingest the Sample Data \n 3. Ingest Sample Data: If you don’t have OneDrive Configured, sign up for the Microsoft 365 free trail. Download the dimension_customer.csv file from the Fabric Samples repo. In the Lakehouse explorer, you see options to load data into Lakehouse. Select New Dataflow Gen2. On the new dataflow pane, select Import from a Text/CSV file. \n \n On the Connect to data source pane. Drag and drop the dimension_customer.csv file that you download. \n \n \n 4. Build a report: From the preview file data page, preview the data and select create to proceed and return to the dataflow canvas. In the Query settings pane, update the Name field to dimension customer. Note Fabric adds a space and number at the end of the table name by default. Table names must be lower case and must not contain spaces. \n \n \n In case you have other data items that you want to associate with the Lakehouse, from the menu items, select Add data destination and Select Lakehouse. If needed, from the Connect to data destination screen, sign into your account and select Next. \n \n \n From the dataflow Canvas, we can transform our data based on your business requirements. Once done, select Publish button at the bottom of the screen or publish later from the drop-down menu of the publish button \n \n \n \n \n \n \n \n A spinning circle next to the dataflow’s name will indicate publishing is in progress in the item view \n \n \n \n When publishing is complete, select the ellipse (…) \n \n \n \n Select Properties. Rename the dataflow to Load Lakehouse Table and select Save \n \n \n Once the dataflow is refreshed, select your new Lakehouse in the left navigation panel to view the dimension-customer delta table. Select the table to preview its data. The SQL analytics endpoint of the Lakehouse enables you to query the data with SQL statements. Select the SQL analytics endpoint from the Lakehouse drop-down menu. \n \n \n Select the dimension-customer table to preview the data and select New SQL query at the top of the Fabric interface. \n \n \n The above sample query aggregates the row count based on the BuyingGroup column of the dimension_customer table. To run the script, select the Run icon at the top of the script. \n \n \n In the item view of the workspace, select the “yourlakehouse” default semantic model \n \n \n From the semantic model pane, You can view all the tables. You can create reports either from scratch, pignated report, or let Power BI automatically create a report based on your data. \n \n Notice that the report is generated in a couple of seconds, Click on view report to view the automatically generated report. \n Save the report by selecting the save from the top ribbon. Notice there is a right navigation bar that you can use to make more changes to the report to meet your requirements by including or excluding other tables or columns. \n \n To share your report, head back to the item view for your workspace, click on the share icon to share the report within your organization. \n \n \n Congratulations, you have just created an end-to-end Analytics solution with Microsoft Fabric in a matter of minutes. Well done! To manage your storage and costs effectively, don’t forget to clean up your resources after you are done. \n \n Further study guides Microsoft Fabric Learn Together STARTING JANUARY 23, 2024 THROUGH FEBRUARY 8, 2024 (18 EPISODES) Expert-led live walk-throughs covering all the Learn modules to prepare you for the the upcoming DP-600 exam leading to the Fabric Analytics Engineer Associate certification. 9 episodes delivered in both India and Americas timezones.Register now for this exclusive live learning experience. Also, sign up for the Fabric Cloud Skills Challenge at https://aka.ms/fabric30dtli and complete all the modules to become eligible for a 50% discount on the DP-600 exam. \n Learn how to use copilot in Microsoft Fabric, your data insights AI assistant Join the Fabric Community to stay updated on the latest About Microsoft Fabric Consider joining the Fabric Career Hub so you won’t miss out on any Careers in Microsoft Fabric \n \n \n \n \n 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OneLake Architecture: The OneDrive for Data","conversation":{"__ref":"Conversation:conversation:4054747"},"id":"message:4054747","revisionNum":4,"uid":4054747,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:1835800"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" Learn how OneLake simplifies data engineering. Data engineers face many difficulties every day. Data sources are diverse and fragmented, containing different file types and data quality levels. Finding specific files, determining their owners and access permissions, can be frustrating. OneLake helps you overcome these challenges. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":6437},"postTime":"2024-02-14T00:00:00.030-08:00","lastPublishTime":"2024-02-14T00:00:00.030-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" As data engineers, we grapple with numerous challenges daily. Data is often scattered across various sources, residing in a multitude of file types with varying data quality. The time spent locating specific files—figuring out which tenant they belong to and deciphering access rights—can be exasperating. This is where OneLake steps in. OneLake streamlines data management, breaks down silos, and ensures that your data resides in one unified home—just like OneDrive for files! \n \n \n A Basic Setup would be; \n \n What is OneLake? \n OneLake is essentially the OneDrive for data within the Fabric ecosystem. Just like OneDrive, it’s automatically provisioned for every Fabric tenant, requiring no infrastructure management. \n Key benefits of OneLake include: \n \n Unified data storage across different domains and tenants. \n Support for both managed and unmanaged data storage. \n Full Delta support using VertiParq (a powerful feature for tracking changes in data). \n Distributed ownership of data and security. \n Integration with DirectLake, providing robust Power BI support \n \n How does OneLake work? \n The architecture of OneLake allows seamless connectivity to multiple cloud providers. Let’s explore the basics: \n \n Symbolic links (Shortcuts): Using symbolic links, you can connect to both Azure and Amazon storage. These shortcuts enable data from these providers to be accessible within the same OneLake, without having to copy the data \n Unified management: All personas—data engineers, real-time analysts, and BI developers—can directly access data stored in OneLake. \n Delta file format: Data within OneLake uses the open-source delta file format, which optimizes storage for data engineering workflows. It supports efficient storage, versioning, schema enforcement, ACID transactions, and streaming. \n Ingestion methods: You can get data into OneLake via Shortcuts or data pipelines. Shortcuts create symbolic links to external storage locations, simplifying navigation. Data pipelines, familiar to Data Factory or Synapse users, link external lakes into the managed tables area. \n \n Managed Data: Tables \n Tables play a crucial role in managing and organizing data within the lakehouse architecture. Once set up in the managed section of the lakehouse, you have several options: \n \n Browse tables using the Lakehouse Explorer. \n Query and analyze data efficiently. \n \n Connecting External Data to Microsoft Fabric OneLake Now that you’ve grasped how the oneLake works, let’s get some data from an External source into oneLake. For this, we will be using the Data Engineering Experience, feel free to choose any other Experience. \n \n Create a workspace: Begin by creating a workspace within your Microsoft Fabric environment. This workspace will serve as the container for your data-related activities. \n Select lakehouse item from the drop-down menu and give it a name \n \n \n Setup a Lakehouse: \nNext, create a lakehouse item within your workspace by following the following steps; \n \n Select the workspace into which you want to create the lakehouse. \n In the open worspace, select new. \n Select lakehouse item from the drop-down menu and give it a name. \n \n \n 3. Ingest the Data from an Extenal source into the Lakehouse. Use any of the following options to create a shortcut, which is allows you to point to other storage locations, which can either be internal or external to oneLake. \n \n \n That will launch up a shortcut wizard, select the source you want to pull your data from. For this demo select OneLake to create an internal shortcut. \n \n Find and connect to the data you want to use with your shortcut. And click next. Your data will be loaded in the files section of your lakehouse \n \n Preview the Loaded data by clicking on the files section \n \n 4. Transform the Data into Delta Tables Once your data is in the Lakehouse, create a new notebook and associate it with the Lakehouse created. Drag and drop the file into the notebook. \n \n 5. Transform it into delta tables using Spark within the Fabric notebook. Delta tables provide efficient change tracking and management. \n \n 6. Build Reports and Analyze the Data From the table view, click on Lakehouse and select SQL analytics endpoint. \n \n From the SQL endpoint view, select new visual to create a simple visual \n \n You can create the visuals manually, or let co-pilot do the magic for you. \n \n \n Clean Up Resources: After completing the task, remember to clean up any temporary or test data. \n \n \n \n \n Conclusion OneLake aims to give you the most value possible out of a single copy of data without data movement or duplication. You no longer need to copy data just to use it with another engine or to break down silos so you can analyze the data with data from other sources. \n Further Guides Signup for the Microsoft Fabric Global AI Hack, a virtual event where you can learn, experiment, and hack together with the new Copilot and AI features in Microsoft Fabric! Sign up for the Fabric Cloud Skills Challenge at https://aka.ms/fabric30dtli and complete all the modules to become eligible for a 50% discount on the DP-600 exam. Learn how to use copilot in Microsoft Fabric, your data insights AI assistant. Join the Fabric Community to stay updated on the latest About Microsoft Fabric Consider joining the Fabric Career Hub so you won’t miss out on any Careers in Microsoft Fabric \n \n 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Copilot Summary Visual in Power BI","conversation":{"__ref":"Conversation:conversation:3886081"},"id":"message:3886081","revisionNum":2,"uid":3886081,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:1379718"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n Working as a Power BI Data Analyst will never be the same after using this copilot summary visual in Power BI. Let's have a sneak peek into this visual. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":15865},"postTime":"2023-07-28T00:36:57.129-07:00","lastPublishTime":"2023-07-28T00:36:57.129-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" \n \n \n Get Ready for Your Magical Moments \n Power BI Data Analysts can boost their productivity with the help of Artificial Intelligence (AI). Copilot, a new AI feature in Power BI, allows Data Analysts to create reports and insights faster and easier. Copilot uses natural language to understand what the user wants and generates the best visuals and summaries for their data. \n \n In this Article, we will highlight another copilot feature in Power BI - summary with copilot visual card. \n \n Before we proceed, watch this short clip \n \n \n \n Isn't this magical! Tell us in the comment how you will use this feature once available. \n What is Summary with Copilot Visual \n With the “summary with Copilot” visual in Power BI, you can get a quick and easy summary of the viduals in your Power BI report. This visual card uses Copilot, an AI assistant that can understand natural language queries/prompts and generate report summary with relevant insights. You have the option to select a particular visual or all the visuals in the report and summary with copilot will get the work done. \n \n \n Benefits to Power BI Data Analyst \n \n Time Saving: Using AI tools can help you achieve more in less time. The summary with copilot visual card is an AI tool that can create a summary of your Power BI report in seconds1. You can select the visuals you want to include and ask copilot to summarize them for you. This way, you can focus on the most important insights and communicate them effectively. \n Relieve Mental Workload: Creating a Power BI Report can be a challenging task that requires a lot of effort and attention. Sometimes, you may feel too tired to write a summary after finishing the report. That’s why the summary with copilot visual is a great tool to help you out. It can automatically generate a summary of your report based on the visuals you select. This way, you can save time and energy and focus on the key insights of your data. \n Becomes Easier to make it a Practice: Including Summary in your Power BI report is a best practice as it makes it easier for your audience to easily digest the insight in your report. With the time saving and mental workload relieving capability of \"summary with copilot\" visual card, it now easier to make including summary in your report a everytime practice. \n \n \n Note: This feature is currently in private preview. \n \n Drop a Comment \n We will appreciate your comment on how you plan to use this feature \n \n \n Additional Resources \n Participate in the Microsoft Learn AI Skills Challenge Here \n \n 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