#PowerBI July update is out. Looks like there are some improvements to #AzureMaps reference layers 👉CSV Support: The new support for CSV files as data sources for reference layers makes it easier to integrate various data formats, alongside existing options like GeoJSON, Shapefiles, WKT, and KML files. 👉 Enhanced Customization: The ability to format reference layer shapes directly within the formatting pane. You can now customize the color and width of points, lines, and polygons without modifying your reference layer files but there is no conditional formatting yet 😢 👉 Dynamic URL Sources: Adding dynamic URL support using conditional formatting is impressive. It allows for dynamic loading of different reference layers based on data-bound conditions, such as slicer selections, enhancing the interactivity of your reports. Ring that 🔔 to stay up to date with all things #PowerBI.
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𝐃𝐚𝐲 𝟖- 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐑𝐞𝐚𝐥 𝐓𝐢𝐦𝐞 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐒𝐞𝐫𝐢𝐞𝐬 📊 My client gave me TSV files—yes, you heard right, TSV files and not CSV files. TSV stands for 𝐓𝐚𝐛-𝐒𝐞𝐩𝐚𝐫𝐚𝐭𝐞𝐝 𝐕𝐚𝐥𝐮𝐞𝐬, a type of file where data is stored in a plain text format and each field is separated by a tab character. I need to load these TSV files into Power BI to create the dashboard. 𝐇𝐞𝐫𝐞'𝐬 𝐡𝐨𝐰 𝐲𝐨𝐮 𝐜𝐚𝐧 𝐡𝐚𝐧𝐝𝐥𝐞 𝐭𝐡𝐢𝐬 𝐬𝐢𝐭𝐮𝐚𝐭𝐢𝐨𝐧: Rename File: Rename your .tsv file to .csv. Now, Launch Power BI Desktop-->"Home" tab--> "Get Data"-->Choose "Text/CSV"--->Select that file--->"Load" tab I'm mentioning this detail because many users face issues when trying to load TSV files into Power BI. By default, Power BI looks for CSV files, which can cause confusion and prevent TSV files from appearing in the file selection dialog.
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The great thing about learning Git and sharing code on GitHub, is you open it to the community to provide feedback. Thanks to https://lnkd.in/ed6SGrRD, we just updated the YAML code for the "PBIP Deployment & DAX Query View Testing (DQV) Pattern" to support different folder configurations for workspaces. If you're interested in automating the deployment and testing of Power BI semantic models/reports, please see this article: https://lnkd.in/gTMVASSp
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🤔 Are you struggling to import data from various sources into Excel? Say no more!💡 Power Query Series - Day 1 ✨💡 Introducing Power Query - the ultimate solution to your data import woes. 💪 Power Query allows you to seamlessly import data from sources like CSV, PDF, Web, Workbook, XML, JSON, and many more.✨ In this video tutorial, I've broken down the process step-by-step, making it easy for you to import your data and save valuable time.✨💡 Watch the tutorial now and unlock the full potential of Power Query! 💻🔍 Ready to take your data journey to the next level? 💼✨ Implementing the Power Query solution can revolutionize the way you handle data, providing you with valuable insights and streamlining your data processes. 💡 Share your experiences and insights as you embark on this journey. Let's unlock the power of data together! 🚀 #DataAnalytics #Excel #PowerQuery #DataJourney #DataInsights
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🎥 Today’s Video Continuing from yesterday’s Data Cleaning🎥 In this video, I’ll show you how to: ✅ Add new basic column ✅ Add new custom column ✅ Add new conditional column 👉 Watch today’s videos and take your Power Query skills to the next level. If you missed yesterday’s post, make sure to check it out too! 💡 Don’t forget to comment, like, and share if you find these tutorials useful. Let’s make data cleaning simple and efficient together! 🙌 #DataCleaning #PowerQuery #DataAnalytics #MissingValues #LearnWithMe #DataTransformation
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Facing Challenges Importing Heavy Data from Excel to Power BI? We've Got the Solution! Open the Excel file. Save it as a CSV file. Import the CSV file into Power BI. Originally loaded 2,000 rows; now successfully handling 10,000 rows
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Here’s your weekly dose of wisdom (worth a little more than 2 cents)! 💡 Ever wondered how many Sensitivity Labels you’ve got floating around? Are they all published? What about your Policies—are you sure they’re all in place? And let’s not forget, how many labels are out there pulling double duty, published more than once? Oh, and do you know which permissions are set on each of your labels? If you’re tired of clicking through the Purview Portal label by label just to check permissions, I’ve got great news for you. I’ve just released a script that lets you export all that juicy data to JSON or CSV format. And for those of you with a knack for Power BI, you can even export the data to Log Analytics and dive into it with a ready-to-use Template available on GitHub. No more manual digging—save time and get all the info you need at a glance. Enjoy! 🎉 https://lnkd.in/ekzRciwM #Microsoft365 #M365 #MPARR #MicrosoftPurview #PowerBI #LogsAnalytics #Sentinel #Reporting #Dashboards #InformationProtection #MIP #Labels #DLP #Webinar #PowerBI #DataAnalisys #Data #DataInsights #API #Office365ManagementAPI #YouTube #DataExfiltration #DataSecurity
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👨💼 Power BI scenario # 4 You receive a CSV file with inconsistent date formats in one of the columns. Some dates are in the "MM/DD/YYYY" format, while others are in the "DD/MM/YYYY" format. How you would use Power Query to standardize the date format across the entire column. #PowerBI #DataAnalytics #100DaysOfPowerBI #LearningJourney #DataScience #BusinessIntelligence #datavisualization #powerbigate
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PowerQuery is a superior choice than the traditional Excel approaches. PowerQuery, a data preparation service, can aid in data checking, cleaning, error detection, and other analysis tools.
I think I may be pushing Excel's limits with this one! Loading a 3.5 GB file into PowerQuery, ended up being over 35 million rows of data stored in a CSV. And, actually, Excel managed just fine 💪. My client only wanted a simple aggregated view, so we used PowerQuery's Group By function to create a table with 8 rows and 2 columns with a file size of 18KB. No doubt that Excel would not normally be the go-to solution for a source with this many rows, but it did what he needed in just a few minutes in the tool that he is very comfortable in. What is the biggest / trickiest data you have had to work on in Excel?
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Choosing between CSV and Excel depends entirely on your specific needs and the nature of the data you are working with. To learn more, check out our article at learninglabb.com #zelearninglab #marketingtips #zelearninglabb #digitalmarketing #datascience #dataanalysis #careergrowth #successpath #zell #zelearninglabb #learninglabb #learninglab #digitalmarketing #datasciencecourse #datascience #datanalytics #csv #excel
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I think I may be pushing Excel's limits with this one! Loading a 3.5 GB file into PowerQuery, ended up being over 35 million rows of data stored in a CSV. And, actually, Excel managed just fine 💪. My client only wanted a simple aggregated view, so we used PowerQuery's Group By function to create a table with 8 rows and 2 columns with a file size of 18KB. No doubt that Excel would not normally be the go-to solution for a source with this many rows, but it did what he needed in just a few minutes in the tool that he is very comfortable in. What is the biggest / trickiest data you have had to work on in Excel?
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