Just saw this post on LinkedIn from Jon Stjernegaard Vöge on some new Governance features which are currently being developed - I'm glad Microsoft are taking this direction - looks very promising. Jon's post: "There were a few hidden gems revealed at hashtag#FABCONEUROPE yesterday, which were not shown at the keynote: 𝐅𝐚𝐛𝐫𝐢𝐜 / 𝐎𝐧𝐞𝐋𝐚𝐤𝐞 𝐂𝐚𝐭𝐚𝐥𝐨𝐠 and 𝐃𝐚𝐭𝐚 𝐀𝐜𝐜𝐞𝐬𝐬 𝐇𝐮𝐛 Two extremely promising governance features which will help patch some of the current shortcomings.I snapped a few (poor) pictures as seen below, which might give you an idea. 1) 𝐅𝐚𝐛𝐫𝐢𝐜 / 𝐎𝐧𝐞𝐋𝐚𝐤𝐞 𝐂𝐚𝐭𝐚𝐥𝐨𝐠 At-a-glance overview of governance status by Domain, Workspace and Item with suggested actions, and easy to browse lists and lineage views of all items. All of this searchable and filterable. Also seems like Domains in general will play a larger role in your architecture 2) 𝐃𝐚𝐭𝐚 𝐀𝐜𝐜𝐞𝐬𝐬 𝐇𝐮𝐛 Are you also looking track of which people have access to what? Microsoft is planning a one-stop shop for data access, where you can browse, review and edit all your user and item permissions in your data estate. Sensitivity Labels and Endorsements appear very integrated, and will play a pivotal role in this as well 🤝🧯The exact timeline and functionality for these appears unknown at this time, but I’m personally very excited! What do you think?"

Hi Everyone, I have created the following measure on a semantic model using direct lake, which looks something like this Measure = SWITCH( TRUE(), SELECTEDVALUE(Transactions[ClassID]) IN {1234, 5678}, SUM(Transactions[Quantity]), DISTINCTCOUNT(Transactions[TransactionID]) ) The measure works perfectly fine in a PowerBI card visual, but when I try to use the same measure in a table/matrix, any resulting query would basically time out I've tried the following but nothing seems to work - Use IF instead of SWITCH, made no difference and query still times out - Tried other aggregate functions instead of DISTINCTCOUNT, such as both conditions using SUM, and also made no difference and query still times out - I even tried both conditions doing SUM(Transactions[Quantity]) and it still doesn't work. Measure = SUM(Transactions[Quantity]) works perfectly fine, of course. Without showing the entire DAX query, when I traced the query in PowerBI desktop for a simple matrix, snippets of the query looks like the below, which eventually times out VAR __DS0Core = SUMMARIZECOLUMNS( ROLLUPADDISSUBTOTAL( ROLLUPGROUP( 'Transactions'[TransactionDisplayName], 'CampaignCategory'[CampaignCategoryName], 'Item'[ItemName], 'Class'[ClassName] ), "IsGrandTotalRowTotal" ), __DS0FilterTable, __DS0FilterTable2, __DS0FilterTable3, "SumQuantity", CALCULATE(SUM('silver_Transaction'[Quantity])), "Measure", 'Transactions'[Measure] ) I'm not good at DAX, so if anyone can shed some insight on how to rewrite this measure to perform in a table/matrix that would be highly appreciated. Thanks in advance.

Yesterday, Microsoft released the AI Skill item to Public Preview. I hope I'm not going over the top here when I say: I really think there's a chance that this feature could change nearly everything we know about business analytics. If a business user can get reliable (key point) answers to their business questions, within seconds, without the need for an analyst or a dashboard... then doesn't that change quite a lot? Databricks seem to be going massively in this direction too with their recent AI/BI feature. All up for discussion, of course, and highly dependent on whether the feature actually works properly 😂 What are your thoughts?

Hello! I am trying to ingest the below JSON file into (two) tables in a Lakehouse. https://www.kaggle.com/datasets/aditeloo/the-world-dataset-of-covid19?resource=download&select=owid-covid-data.json I was trying to test Pipelines and PySpark notebooks on this task. This file is less than 50 MB, so it is fairly small. 1) Pipeline cannot handle (preview) this file as a source. I have attached two screenshots showing the error. 2) This file is fairly simple, however, its data is nested. It has countries (Dimension table), and for each country, it has daily covid cases (Fact table). This means I can attempt to load "Dim Country" and "Fact Covid" tables using PySpark. However, due to the structure of the json file, it appears that this file does not fit nicely in a Spark Data Frame. Each country code appears as a column in the Spark Data Frame instead of a row. I am looking for ways to get two Data Frames, one for "Dim Country" and another for "Fact Covid", to be saved as Delta tables in the Lakehouse. I have added two screenshots. I am keen to hear feedback from other users and if someone can try to load this file and guide me in the right direction, I am very grateful.

Does anyone have a good idea how you can get the notification when the data pipeline is failed? As far as I know, there are notification activities - Team or Outlook but its for activity level and not for the pipeline or workspace level. You need to add the notification activity per each pipeline activities if you want to monitor the entire pipeline properly. Someone suggests that you can wrap the pipeline within another pipeline and run Outlook or Team activity if the wrapped pipeline has failure. Any good idea?