One of the reoccurring issues that people face in Fabric (and post about here!) is the delay it can take for the T-SQL endpoint of a Lakehouse to update, when you make changes to Lakehouse data and tables (via the Lakehouse/ Spark endpoint). This is most problematic when you have a multi-step ETL/ELT process that first updates some Lakehouse table, then reads that data (via the T-SQL endpoint), using a T-SQL script in a Warehouse. Well, there is a workaround to force the update of the T-SQL endpoint, using Semantic Link. This workaround was provided initially by the Microsoft product manager for the Lakehouse T-SQL endpoint. Some links on this: - Original LinkedIn post by Mark (Microsoft) - Obvience video walking through how to implement it. Hopefully they improve the native functionality in the future, so that forced updates are not required, but in the short-term, this should help a lot of people.

Welcome to all new members, here's some links and information to help you get started! 𝗤𝘂𝗶𝗰𝗸 𝗟𝗶𝗻𝗸𝘀 𝘁𝗼 𝗴𝗲𝘁 𝘀𝘁𝗮𝗿𝘁𝗲𝗱 - For an introduction to this community → Explore the Welcome Pack - New-ish to Fabric? → Check out our Fabric Foundation module - Studying for the DP-600? → Check out the DP-600 Module and the DP-600 category - Studying for the DP-700? → Check out the DP-700 Module and the DP-700 category - Want to get hands-on? → Check out Fabric Dojo 𝗛𝗼𝘄 𝘁𝗼 𝗲𝗻𝗴𝗮𝗴𝗲 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆? - Share your knowledge and experience! Even if you're relatively new to Fabric, or the community, your opinion and experiences are valued here! A great way to earn your first point(s) is to introduce yourself in the thread below 👇😀 Thank you for engaging and joining us on this exciting learning journey! 🙏 Will