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Author: Prologika - Teo Lachev

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Implementing Role-playing Dimensions in Power BI

Role-playing dimensions are a popular business requirement but yet challenging to implement in Power BI (and Tabular) due to a long-standing limitation that two tables can’t be joined multiple times with active relationships. Declarative relationships are both a blessing and a curse and, in this case, we are confronted with their limitations. Had Power BI allowed multiple relationships, the user must be prompted which path…

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Prologika Newsletter Fall 2024

When it comes to Generative AI and Large Language Models (LLMs), most people fall into two categories. The first is alarmists. These people are concerned about the negative connotations of indiscriminate usage of AI, such as losing their jobs or military weapons for mass annihilation. The second category are deniers, and I must admit I was one of them. When Generative AI came out, I…

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Generative AI: Excessive Reinforcement Learning

Do you know that without human intervention the Generative AI responses would be too toxic after training the model from the garbage on Internet? Do you know that OpenAI hired Kenyan workers to make ChatGPT less toxic? To throw in some jargon, this is called RLHF (reinforcement learning with human feedback). Not sure who Microsoft hired to cleanse copilots, but apparently they went overboard. Here…

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Fabric Direct Lake: Memory Utilization with Interactive Operations

As I mentioned in my Power BI and Fabric Capacities: Thinking Outside the Box, memory limits of Fabric capacities could be rather restrictive for large semantic models with imported data. One relatively new option to combat out-of-memory scenarios that deserves to be evaluated and added to the list if Fabric is in your future is semantic models configured for Direct Lake storage. The blog covers…

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Fabric Capacity Limits

Here is table that is getting more and more difficult to find as searching for Fabric capacity limits returns results about CU compute units (for the most part meaningless in my opinion). I embed in a searchable format below before it vanishes on Internet. The most important column for semantic modeling is the max memory which denotes the upper limit of memory Fabric will grant…

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Power BI and Fabric Capacities: Thinking Outside the Box

I’m conducting an assessment for a client facing memory pressure in Power BI Premium. You know these pesky out of memory issues when refreshing a biggish dataset. They started with P1, moved to P2, and now are on P3 but still more memory is needed. The runtime memory footprint of the problematic semantic model with imported data is 45 GB and they’ve done their best…

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Atlanta Microsoft BI Group Meeting on August 5th (Elevate Program Management with Power BI & DevOps)

Atlanta BI fans, please join us in person for the next meeting on Monday, August 5th at 6:30 PM ET. Elayne Jones and Matt Kim (Solutions Architects at Coca-Cola) will show us how to bring Azure DevOps data to life by creating data models and interactive reports in Power BI. Your humble correspondent will help you catch up on Microsoft BI latest. CloudStaff.ai will sponsor…

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LLM Adventures: RAG Apps

This post summarizes my research around the increasingly popular RAG apps, and it’s meant more as an internal memo to myself to summarize existing findings should one day a suitable project comes along. However, someone starting with RAG development might find this useful (we are all LLM rookies). RAG is a fascinating topic and presents another great case for generative AI in data analytics. RAG…

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LLM Adventures: Text2DAX

In my previous post, I covered how large language models, such as ChatGPT, can be used to convert natural queries to SQL. Let’s now see how Text2DAX fairs. But wait, we have a Microsoft Fabric copilot already for this, right? Yes, but what happens when you click the magic button in PBI Desktop? You are greeted that you need to purchase F64 or larger capacity.…

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