Mohamed Ashour

10 𝙋𝙤𝙬𝙚𝙧 𝘽𝙄 𝙞𝙣𝙩𝙚𝙧𝙫𝙞𝙚𝙬 𝙌𝙪𝙚𝙨𝙩𝙞𝙤𝙣𝙨 𝙖𝙣𝙙 𝘼𝙣𝙨𝙬𝙚𝙧𝙨 𝙖𝙨𝙠𝙚𝙙 𝙞𝙣 𝙧𝙚𝙘𝙚𝙣𝙩 𝙄𝙣𝙩𝙚𝙧𝙫𝙞𝙚𝙬 1. Q: What is the difference between calculated columns and measures in Power BI? A: Calculated columns are computed for each row in a table and stored in the data model, while measures are dynamic calculations performed at query time based on the current context of the report. 2. Q: Explain the concept of DAX (Data Analysis Expressions) in Power BI. A: DAX is a formula language used in Power BI for creating custom calculations in calculated columns, measures, and row-level security rules. It's designed for working with relational data and performing complex calculations. 3. Q: What is the difference between FILTER and CALCULATE functions in DAX? A: FILTER is used to apply filters to a table, returning a subset of the data. CALCULATE is used to modify the context in which an expression is evaluated, often used with filter arguments to change the result of measures. 4. Q: How do you optimize Power BI reports for better performance? A: Key optimization techniques include: - Reducing the data model size - Using measures instead of calculated columns where possible - Avoiding unnecessary visuals and complex DAX calculations Implementing incremental refresh for large datasets - Using query folding to push calculations to the data source 5. Q: What is the purpose of the star schema in Power BI data modeling? A: The star schema is a data modeling technique that organizes data into fact and dimension tables. It improves query performance and simplifies data relationships, making it easier to create reports and analyze data. 6. Q: Explain the concept of bi-directional relationships in Power BI. A: Bi-directional relationships allow filtering to propagate in both directions between tables. While they can be useful in specific scenarios, they should be used cautiously as they can lead to ambiguous filter contexts and impact performance. 7. Q: What is the difference between import mode and DirectQuery mode in Power BI? A: Import mode loads data into Power BI's in-memory engine, allowing for faster performance but with data size limitations. DirectQuery mode leaves data in the source and queries it in real-time, enabling access to larger datasets but with potentially slower performance. 8. Q: How do you implement row-level security (RLS) in Power BI? A: RLS is implemented by creating roles in the Power BI Desktop, defining DAX expressions to filter data based on user credentials 9. Q: What is the purpose of the BLANK() function in DAX? A: BLANK() is used to handle null values in DAX expressions.. 10. Q: How do you create a date table in Power BI, and why is it important? A: A date table can be created using DAX functions like CALENDAR() or CALENDARAUTO(), or by importing from an external source. Follow Prem Mandal For More #powerbi #interview #questions

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Power BI % Curve from EXCEL Timesheet - - using Variables to achieve the value of " Show values as Percentages " - Default. Variables Makes the Formula Shorter, Easier & Such complex calculation you can do using Data Analysis Expression So , Multiple complex Time intelligence you can do as % from overall or % from Filtered Data , whatever have a nice day #Dashboards #PowerBI #DataAnalysisExpression

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Sopra Steria | Exp: 5 years | Power BI Developer | Power BI Q1: Could you provide a brief introduction of yourself, including an overview of the most recent project you've worked on? Q2: What DAX measures did you use in your last project, and how did they support the project's objectives? Q3: What approach would you take to execute an end-to-end Power BI project? Q4: Describe the steps you would follow to engage with clients during the requirements gathering and understanding phase. Q5: Which databases have you connected to Power BI in your experience? Q6: Can you describe the most challenging problem you've encountered in your projects and how you resolved it? Q7: A client has 20 years of data stored in MySQL, but the requirement is to work with only the most recent 2 years of data. How would you approach this? Q8: What is the distinction between duplicating and referencing a table in Power BI? Q9: How do Merge and Append operations differ in Power BI? Q10: If you have two fact tables and no dimension table, how would you connect them in Power BI? Q11: Where would you place columns like Invoice ID and Order ID when designing a data model? Q12: What process would you follow to set up alerts in Power BI? Q13: How would you implement write-back functionality in Power BI? Q14: Which SQL functionalities have you utilized over your five years of experience? Q15. What are the different file extensions used in Power BI? Follow Prem Mandal For more

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🔄 Following up on my previous post about hierarchical data transformation in Excel, I'm excited to share a more automated approach using Power Query! In this comprehensive video tutorial , I demonstrate how to transform complex hierarchical data structures into analysis-ready databases using Power Query. The tutorial breaks down the process into three main stages:  ✨Understanding header levels within your data structure,  🎯Implementing strategic column splits, and  🔄Utilizing fill-down operations to maintain data integrity. For those working with regularly updated datasets, you'll also discover a bonus Power Query trick that significantly streamlines the refresh process. 📽️You can watch the video from the following link : https://lnkd.in/ekxeTX9r While Excel formulas can handle this task effectively, Power Query offers enhanced capabilities for repeatable data transformations, especially when dealing with large datasets that require frequent updates. The solution presented combines custom column creation with group by operations to create a robust, maintainable data transformation process. This approach is particularly relevant to our ongoing discussion about construction data analytics maturity. As many of us in the industry recognize, the current state of construction data often requires significant preparation before we can implement advanced analytics or AI solutions. It's crucial to acknowledge that establishing robust data transformation processes is a fundamental step toward digital transformation. Through the Construction Data Analytics Initiative, we're advocating for a measured, practical approach to digital advancement. While AI presents exciting possibilities, our immediate focus should be on building strong data foundations. As the saying goes, we need to walk before we can run – and mastering tools like Power Query, Power BI and advanced Excel helps us take those essential first steps. Drop your data challenges in the comments or DM me. Every week, we'll tackle a new problem and share the solution with our growing community.   Who's with me on this data analytics journey? 🚀   🔗 Resources: ⚫Visit My Website: APC Mastery Path - https://lnkd.in/eSxVAzA3 – AI resources tailored for the construction industry ⚫GitHub Repos: Access the files and tools featured in this video for a hands-on experience. You can access all my repositories by visiting the following link: https://lnkd.in/ewyq-NCS ⚫Previous Excel tutorial: https://lnkd.in/enQygRfZ #ConstructionAnalytics #DataTransformation #PowerQuery #DigitalConstruction #ConstructionInnovation #BusinessIntelligence #DataScience #PowerBI #ExcelTips #DataAnalytics #RICS #DatabaseManagement #DataCleaning #ExcelTutorial #ExcelForConstruction #ConstructionIndustry #DigitalTransformation #DataDriven #BuildingAnalytics #DataStrategy #DataArchitecture #BusinessEfficiency #ProcessAutomation #DataManagement #ConstructionTechnology #DigitalSkills

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Repetitively Asked powerbi interviews questions ( 0-3yrs ) 1. What techniques can be used to reduce the file size of a Power BI report? 2. Describe the different layers involved in Power BI architecture. 3. How do you implement data lineage in Power BI? 4. What is the role of the M language in Power BI? 5. How do you create a gauge chart in Power BI? 6. What is the difference between a heat map and a filled map in Power BI? 7. Explain the concept of data masking in Power BI and its use cases. 8. What is the function of the "Append Queries" feature in Power Bl, and how is it used? 9. How can you ensure that Power BI recognizes a specific column as a date column if it doesn't do so automatically? 10.Describe the process Power BI uses to handle large datasets exceeding the in-memory capacity. 11 Can you explain the role of the Power BI service in the overall Power BI architecture? 12. What are the key components of data modeling in Power BI? 13. What is the purpose of the VertiPaq engine in Power BI? 14. How do you create a stacked area chart in Power BI? 15. What is the difference between a clustered bar chart and a stacked bar chart? 16. Explain the concept of role-based access control (RBAC) in Power BI. 17. What is a calculated column in Power BI, and how is it different from a measure? 18. How can you create and apply a custom data category in Power BI? 19. What are the different methods to optimize data load performance in Power BI? 20. Can you outline the Power Bl ecosystem and its major components? 21. What is the difference between a dataflow and a dataset in Power BI? 22. How does the DirectQuery mode work in Power BI, and when would you use it? 23. How do you create a waterfall chart in Power BI? 24. What are the advantages and disadvantages of using a scatter plot in Power BI? 25. Explain the concept of incremental refresh in Power BI. 26. What is the purpose of the "Group By" feature in Power BI, and how is it used? 27. How can you handle time zone conversions in Power BI? credit- Rituraj Singh Gour Follow Prem Mandal For more #powerbi #interview #questions

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So Llama 3.2 just got released. Comparing output of LLama 3.2 vs LLama 3.1. The question though , is it really happening behind the scenes or is Llama 3.2 just mimicking LLama 3.1 ? Yes, testing can be done using model loads and then running the summarization but that's another scope of discussion. #GenerativeAI #LLama3.2 #NewLLM

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Power Bi summary …,

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#𝐈𝐁𝐌 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 1. How can you create and configure a data gateway in Power BI? 2. Explain the process of creating a dynamic tooltip in Power BI. 3. How does Power BI handle real-time data streaming, and what are its use cases? 4. What are the different types of data relationships in Power BI? 5. Describe the purpose and usage of Power BI Premium. 6. How do you create a sunburst chart in Power BI? 7. What are the differences between a line chart and an area chart in Power BI? 8. Explain the concept of Data Analysis Expressions (DAX) in Power BI. 9. What is the significance of the "Drillthrough" feature in Power BI? #Capgemini Power BI Interview Questions 1. How do you implement row-level security (RLS) in Power BI? 2. What are the best practices for designing a Power BI dashboard? 3. Can you explain the Power BI report lifecycle? 4. How does Power BI handle data refresh and scheduling? 5. What is the role of the Query Editor in Power BI? 6. How do you create a funnel chart in Power BI? 7. What is the difference between a measure and a KPI in Power BI? 8. Explain the concept of hierarchical slicers in Power BI. 9. How do you use bookmarks in Power BI to enhance report interactivity? #Deloitte Power BI Interview Questions 1. How can you configure and use custom visuals in Power BI? 2. What techniques can be employed to improve query performance in Power BI? 3. Describe the integration capabilities of Power BI with other Microsoft services. 4. What is the difference between Import mode and DirectQuery mode in Power BI? 5. How do you create a pareto chart in Power BI? 6. What are the advantages of using Power BI templates? 7. Explain the concept of dataflows in Power BI. 8. What is the purpose of the "Merge Queries" feature in Power BI, and how is it used? 9. How do you create and manage data alerts in Power BI? best interview resources to crack Power BI Interviews 👇👇 https://lnkd.in/gbvhuDf2 Follow Prem Mandal For More #powerbi #datanalyst #powerbideveloper #python #dataanalytics #data #DataAnalytics #Free #LearnFromHome #ExperienceMatters #DigitalLearning #IndustryGiants #meriskill #interncareer #pwc #GE #KPMG #tata #tcs Shashank Singh 🇮🇳

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This will be useful in a whole lot of applications.

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𝐓𝐡𝐢𝐬 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧 was 𝐀𝐬𝐤𝐞𝐝 𝐢𝐧 𝐦𝐲 𝐥𝐚𝐬𝐭 𝐏𝐨𝐰𝐞𝐫 𝐁𝐢 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 #𝐩𝐨𝐰𝐞𝐫𝐛𝐢 ✅QUESTION: 𝐇𝐨𝐰 𝐲𝐨𝐮 𝐜𝐚𝐧 𝐫𝐞𝐝𝐮𝐜𝐞 𝐭𝐡𝐞 𝐬𝐢𝐳𝐞 𝐨𝐟 𝐲𝐨𝐮𝐫 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐦𝐨𝐝𝐞𝐥 𝐚𝐧𝐝 𝐞𝐧𝐡𝐚𝐧𝐜𝐞 𝐢𝐭𝐬 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 ✅MY ANSWER: To reduce the size of your Power BI model and enhance its performance, you can follow these steps: 1. 𝐂𝐫𝐞𝐚𝐭𝐞 𝐚 𝐃𝐚𝐭𝐞 𝐓𝐚𝐛𝐥𝐞:  Always create a date table manually and turn off the auto date/time option in your file. This will boost performance. 2. 𝐔𝐬𝐞 𝐚 𝐒𝐭𝐚𝐫 𝐒𝐜𝐡𝐞𝐦𝐚: Instead of using flat tables, organize your data into a star schema. This structure will improve query performance and make your model easier to manage. 3. 𝐏𝐫𝐞𝐟𝐞𝐫 𝐒𝐢𝐧𝐠𝐥𝐞 𝐅𝐢𝐥𝐭𝐞𝐫 𝐃𝐢𝐫𝐞𝐜𝐭𝐢𝐨𝐧:  Use single-direction filters over bi-directional ones. This simplifies your data model and reduces complexity. 4. 𝐎𝐩𝐭 𝐟𝐨𝐫 𝐃𝐢𝐫𝐞𝐜𝐭 𝐐𝐮𝐞𝐫𝐲: For large datasets, use Direct Query mode instead of Import. Just remember, if you're using the free desktop version, there's a 1 million row limit. 5. 𝐑𝐞𝐦𝐨𝐯𝐞 𝐔𝐧𝐧𝐞𝐜𝐞𝐬𝐬𝐚𝐫𝐲 𝐃𝐚𝐭𝐚: Streamline your dataset by removing columns and rows that you don’t need. 6. 𝐔𝐬𝐞 𝐂𝐮𝐬𝐭𝐨𝐦 𝐂𝐨𝐥𝐮𝐦𝐧𝐬 𝐢𝐧 𝐏𝐨𝐰𝐞𝐫 𝐐𝐮𝐞𝐫𝐲: Whenever possible, create custom columns in Power Query instead of using calculated columns in the model. This will give you better performance. 7. 𝐃𝐢𝐬𝐚𝐛𝐥𝐞 𝐐𝐮𝐞𝐫𝐲 𝐋𝐨𝐚𝐝 𝐟𝐨𝐫 𝐔𝐧𝐧𝐞𝐞𝐝𝐞𝐝 𝐓𝐚𝐛𝐥𝐞𝐬: In Power Query, disable the query load for any tables that aren’t necessary for your final model. ***Mention atleast 5 points for better. Implementing these strategies will help you manage your Power BI model more efficiently and improve overall performance. Interview Resources: https://lnkd.in/gKbf2rmr Follow Prem Mandal For More #powerbi #interview #questions #dataanalyst

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The star schema design is a proven approach for building Robust, user-friendly, and high-performance analytic models. Here’s a quick guide to implementing one in Power BI. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗦𝘁𝗮𝗿 𝗦𝗰𝗵𝗲𝗺𝗮? 𝘾𝙤𝙣𝙘𝙚𝙥𝙩: Star schema classifies model tables as either fact or dimension tables. 𝙎𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚: In a diagram, the fact table forms the center, while dimension tables radiate around it like points of a star. 𝗙𝗮𝗰𝘁 𝗧𝗮𝗯𝗹𝗲𝘀 𝙋𝙪𝙧𝙥𝙤𝙨𝙚: Store rows representing specific business activities (e.g., sales orders, stock movements). 𝘾𝙝𝙖𝙧𝙖𝙘𝙩𝙚𝙧𝙞𝙨𝙩𝙞𝙘𝙨: Accumulate numerous rows over time, summarizing data to produce metrics like sales and quantity. 𝗗𝗶𝗺𝗲𝗻𝘀𝗶𝗼𝗻 𝗧𝗮𝗯𝗹𝗲𝘀 𝙋𝙪𝙧𝙥𝙤𝙨𝙚: Describe business entities (e.g., people, places, products). 𝘾𝙝𝙖𝙧𝙖𝙘𝙩𝙚𝙧𝙞𝙨𝙩𝙞𝙘𝙨: Contain key columns (unique and non-null) as well as other descriptive columns for filtering and grouping (e.g., product name, category). 𝗠𝗢𝗦𝗧 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗧 - 𝙒𝙃𝙔 𝙎𝙃𝙊𝙐𝙇𝘿 𝙔𝙊𝙐 𝘾𝙊𝙉𝙎𝙄𝘿𝙀𝙍 𝙎𝙏𝘼𝙍 𝙎𝘾𝙃𝙀𝙈𝘼 ? → Improves query performance by optimising joins & data retrieval. → Makes it easier for users to understand and interact with. 𝗛𝗼𝘄 𝘁𝗼 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗦𝘁𝗮𝗿 𝗦𝗰𝗵𝗲𝗺𝗮 𝗶𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 1. 𝙄𝙙𝙚𝙣𝙩𝙞𝙛𝙮 𝙁𝙖𝙘𝙩 𝙖𝙣𝙙 𝘿𝙞𝙢𝙚𝙣𝙨𝙞𝙤𝙣 𝙏𝙖𝙗𝙡𝙚𝙨 → Determine the central business activities (fact tables). → Define business entities (dimension tables). 2. 𝘿𝙚𝙨𝙞𝙜𝙣 𝙁𝙖𝙘𝙩 𝙏𝙖𝙗𝙡𝙚𝙨: → Collect and store event data. → Include key columns to link with dimension tables and numeric columns for metrics. 3. 𝘿𝙚𝙨𝙞𝙜𝙣 𝘿𝙞𝙢𝙚𝙣𝙨𝙞𝙤𝙣 𝙏𝙖𝙗𝙡𝙚𝙨: → Include unique key columns and descriptive attributes. → Use these columns for filtering and grouping data. 4. 𝙀𝙨𝙩𝙖𝙗𝙡𝙞𝙨𝙝 𝙍𝙚𝙡𝙖𝙩𝙞𝙤𝙣𝙨𝙝𝙞𝙥𝙨: → Create one-to-many relationships between fact and dimension tables. → Ensure no direct relationships between fact tables. By adopting the star schema design, you can enhance your Power BI data models, making them scalable, easy to use, and efficient for analytics. P.S Follow me for more such insights and strategies, based on my daily learning at work, trainings & conversations from industry professionals on my podcast. #powerbi #datamodelling #starschema #datatips

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The Top 18 Most Common Issues when Troubleshooting the Performance of a Data Model in Power BI ➡️ Non Optimised Data Loads ➡️ Slow Report Interactions ➡️ Complex Calculations Affecting Performance ➡️ High Memory Usage ➡️ Inaccurate Data Display ➡️ Inconsistent Row-Level Security ➡️ Excessive Visual Load Times ➡️ High Cardinality Slowing Model ➡️ Frequent Full Refreshes Overloading System ➡️ Excessive Measures ➡️ Managing Data Security Across Roles ➡️ Inefficient Use of Hierarchies ➡️ Calculations Not Matching Business Logic ➡️ Difficulty Understanding DAX Formulas ➡️ Need for Aggregated Data for High-Level Views ➡️ Trouble Identifying Table Purpose or Structure ➡️ Unexpected Relationships or Data Linkage Errors #PowerBI

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Can ChatGPT generate IFC models by programming? Yes. User-friendly way. [EXPERIMENT]     GPT can generate IFC schema directly - we proved it in previous experiments. This time, I took a different approach. I asked GPT to provide a Python programming code (based on IfcOpenShell, That Open Company) to generate an IFC model. The approach had both potential and risks. On one side, GPT is better at coding Python than "coding" IFC directly. On the other, will it know IfcOpenShell?     Results? Impressively, GPT provided a valid model-generating code in two messages, after only one correction. The code is user-friendly, so even a newcomer can analyze and edit it - easier than tweaking IFC itself.     Then, GPT iterated – in a reverse-engineering way – improving the code and the model.   How did it go?   Check out the whole experiment on my blog: https://lnkd.in/dNudw9TF

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🚀 Power BI Cheat Sheet For Beginners 🚀 Looking to create impactful reports and dashboards with Power BI? Check out this cheat sheet covering essential topics from connecting data to exporting options: 🔹 Connecting Data: - Import Data - Direct Query 🔹 Data Transformation: - Power Query Editor - Remove Columns - Split Columns - Replace Values 🔹 Data Modeling: - Create Relationships - Edit Relationships 🔹 DAX Calculations: - New Measure - Common DAX Functions 🔹 Creating Visuals: - Select Visualization - Bar Chart - Pie Chart - Map Visual 🔹 Formatting Visuals: - Change Colors - Customize Titles - Adjust Axis 🔹 Filters: - Visual Level Filter - Page Level Filter - Report Level Filter 🔹 Slicers: - Add Slicer - Customize Slicer 🔹 Drillthrough: - Add Drillthrough - Back Button 🔹 Publishing & Sharing: - Publish Report - Share Report 🔹 Dashboards: - Create Dashboard - Pin Visuals 🔹 Export Options: - Export to PDF - Export Data like this post if you want more from this Power BI series! 👍♥️ Hope it helps! Follow Prem Mandal for more #PowerBI #DataAnalytics #BusinessIntelligence

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I received many questions on how to add progress photos to Power BI and present them in an interactive way. It is really easy and straightforward, especially if you have been using Power BI for a while. Here are the steps. 1- Run a script to change a binary to an image. I will type the script at the end of this post. 2- Store your progress photos in a folder. 3- Create a new connection source from this folder. 4- Invoke the function created in step 1 above. 5- Format the new function field as "image URL". 6- Map each photo with any identifier of your choice (e.g. Activity Code ID or Activity ID). 7- Update your model relationships to introduce the link between your progress photos and the schedule. 8- The weekly update is really easy. Just delete the old photos from this folder and paste the new ones then click "refresh" inside Power BI. That's all. Here is the script. let BinaryToPbiImage = (BinaryContent as binary) as text=> let Base64 = "data:image/jpeg;base64, " & Binary.ToText(BinaryContent, BinaryEncoding.Base64) in Base64 in BinaryToPbiImage

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🔍 Power BI Tip: Mastering the CALCULATE Function! One of the most powerful DAX functions in Power BI is **CALCULATE**. It allows you to modify the filter context of your data, enabling more complex and insightful analysis. **Example:** Imagine you want to calculate the total sales for a specific year. Here’s how you can do it using the CALCULATE function: ```DAX TotalSales2019 = CALCULATE( SUM(Sales[SalesAmount]), YEAR(Sales[OrderDate]) = 2019 ) ``` This measure sums the SalesAmount column but only for the orders placed in 2019. The CALCULATE function changes the context to include only the sales from that year. By mastering CALCULATE, you can perform dynamic calculations and create more meaningful reports. Let’s connect to share more Power BI tips and tricks! #PowerBI #DAX #CALCULATE #DataAnalysis #BusinessIntelligence #Tips

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🚄 HS2 Timeline Data into Dynamic Power BI Visuals. Dual view approach covering both key decisions, developments & major events. Source - https://lnkd.in/gAkNVa7c newcivilengineer.com (2022 news) Power BI Template Idea - Bas Dohmen #DataVisualization, #PowerBI, #microsoftpowerbi #microsoft #dataviz #powerbideveloper #dax #analytics #reporting #visualization #microsoft #businessanalytics #bi #hs2 #ukgovernment #HighSpeedRail #transportation #HighSpeedTrain

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