Maciej Chojnacki

Here's another interview from my time at the Global Excel Summit earlier this year, just to set you off on the right path as you head off into the weekend. Gašper Kamenšek is one of the best MVPs and trainers out there in my opinion. He's an absolute master at Power BI, and we try to bring him into Full Stack Modeller as much as possible as every session he delivers is pretty mind-blowing. I caught up with him at the Summit the day before his fantastic talk on Power BI. I hope you enjoy this one! https://lnkd.in/eVZgAV6q #excel #powerbi #globalexcelsummit #financialmodelling #summit #financialmodeling

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Discover the possibilities of #Qlik AutoML. Our colleague, Milda Vitalytė Masaitė, delivered a presentation tailored for the Lithuanian 🇱🇹 audience. This session, part of the #QlikTalk virtual event organized by our partner, Day Q Analytics, Qlik partneris. Watch the recording to explore how #QlikAutoML is transforming analytics:

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Curious about the process of migrating data from one #PowerBI tenant to another? Aditya Ojha covers the business scenarios, common challenges, and steps for tenant-to-tenant migrations in this tutorial. https://lnkd.in/d7w4iByT   #Reporting #Azure #Migration

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A few months ago, we shared our collaboration with an online higher education institution. Our Senior MLOps Engineer, Bart Grasza, Data Scientist, Kamil Abram, and Senior Data Engineer, Mateusz Kijewski developed an MLOps platform that provides a foundational template. 🙌 This platform integrates MLOps best practices, automates the setup and update processes, and allows for seamless workflow adaptation across different environments. You can now see this platform in action, presented at the Databricks Data Summit: https://lnkd.in/dUbJrbVi 

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My take on PGVector is an exciting extension of PostgreSQL that allows users to store and search vector embeddings alongside traditional data, making it perfect for AI applications! 🌟 It supports similarity searches, enabling developers to find related items quickly. However, there are some challenges to consider. PGVector can struggle with complex queries, especially when handling required and negated words, leading to missed results. 🚧 Additionally, it may be slow with filtering and ordering, taking several seconds at times. Organisations may choose to use PGVector based on their use cases #ltimindtree Generative AI

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Save the date: Day Q Analytics, Qlik partneris invites you to the virtual event "Qlik Talk: 5 Success Factors That Unlock Analytics." 5 Lithuanian companies—all #Qlik users—will share their data journey experience. Who should attend? ▪Company executives ▪Finance and sales managers ▪Analysts and BI strategists If you work with data—this is for you! 📅 Date: November 26, 2024 ⏰ Time: 10:00–12:00 (local time) 💻 ZOOM (details will be sent to registered participants) 🇱🇹 In Lithuanian language Participation is free, but registration is required. Check the comments for the AGENDA and REGISTRATION link 👇. #Qlik #QlikCloud #QlikSense #QlikAutoML #QlikTalk #Qlikevent #QlikBaltics

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#Qlik certified trainings in Latvian 🇱🇻 language by Uldis P.: https://lnkd.in/dXhzZS4W 🎓 Create Visualizations with #QlikSense, a scenario-based course, addresses the fundamentals required to enable you for self-service visualization and discovery. The course combines demonstrations and hands-on exercises to teach the essential concepts for designing beautiful and effective Qlik Sense visualizations and guided stories. Additionally, you will look in depth at the different visualizations and select the appropriate one for your data and the type of questions you need to answer. #Qlik #Qliktrainings

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Data optimization is calling you! 📣 Tomasz Kostyrka will explore everything from B-Tree indexes for relational databases to cutting-edge techniques like Z-Order, Liquid Clustering, and Microsoft's V-Order for speeding up queries in Direct Lake mode. 🎯 What will you learn: 👉 Key differences between partial and linear ordering in table sorting 👉 How Morton and Hilbert's curves are used for optimizing "Data Skipping" 👉 The inner workings of Parquet files, Predicate Pushdown, and how Z-Order and V-Order complement each other And as a bonus, have you ever wondered how many dwarves can fit in a hotel with infinite rooms? Tomek will answer that, too! 😉 🗓 When: 17th October, 6:00 PM GMT+2 📍 Cracow ⛓️‍💥https://lnkd.in/dQqjiPEP #getindata #data #microsoftazure

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https://lnkd.in/dEj5h9py Really digging this capability, no need for Synapse / Databricks / Redshift / SQL / Snowflake when working with smaller use cases. Users can just leverage the framework we have built that gets their data into ADLS, and then are able to do their modeling in directly in PowerBI.

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"Qlik Baltics Online: Qlik and Snowflake: shape your data" – annual virtual event orchestrated by Infotrust on June 27, 2024. Missed it live? Catch the 11-minute highlights and immerse yourself in our vision of #Unclutter, presented by Saulius Kriukelis, Milda Vitalytė, Simas Baranauskas and Maris Svilans. #Qlik #QlikCloud #QlikSense #DataAnalytics #QlikBaltics

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Different access rights in Power BI depending on the visual? Yes✅ Meet the Visual-Level Security🛡️. Contrary to Row-Level Security, this method empowers you to define different data visibility scopes per visual, instead of always the same one in RLS. You want to show just one country in a table with raw data but more countries, just for comparison, in another table 📋? This approach has got you covered. VLS is also fully reactive to all filters. But it has more advantages than that: ✅ Quick & easy to implement ✅ Full interactivity ✅ Works in both static- and dynamic-RLS style Moreover, it doesn't have these weaknesses: ❌ Data redundancy ❌ Pre-calculated or pre-aggregated, redundant data tables ❌ Reliance on bookmarks, page navigation or hard-coded filters Link to the guide in the comments! ⬇️ Kearney #PowerBI #Modelling #DAX #VLS #RLS #Visual #Security #Role #Roles #VisualSecurity

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#PowerBI fun with scatterplot Inspired by Dimitris Angelides post with a really nice report on who's the ballon d'or winner - I decided to see if I could make the position part in Power BI - especially the combination of plotting both games and position turned out to be the biggest challenge but it could be done 😎 In this case we are plotting positions on a football field but I think there could be other interesting use cases for plotting positions using the scatterplot ... Have you ever used it for plotting positions ... Let me know in the comments 😀 #datavisualization #datavisualisation

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https://lnkd.in/d7Vh8UBN - Building Data Vault on Databricks with PySpark and Delta Live Tables using streaming/batch AutoLoader - a very performant and scalable way of building enterprise DWH in the Lakehouse ecosystem

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𝗡𝗘𝗪 𝗕𝗟𝗢𝗚 𝗣𝗢𝗦𝗧: 𝗪𝗵𝘆 𝘆𝗼𝘂 𝘀𝗵𝗼𝘂𝗹𝗱 𝘀𝘁𝗮𝗿𝘁 𝘂𝘀𝗶𝗻𝗴 𝗨𝗻𝗶𝘁𝘆 𝗖𝗮𝘁𝗮𝗹𝗼𝗴 We noticed that there are still lots of organizations that use Databricks but do not leverage Unity Catalog. Hopefully, this blog can show the added value and give these organizations an extra boost. ✅Firstly, we briefly explain the basis of Unity Catalog. ✅Secondly, some examples are given to increase data governance in Databricks by using simple SQL queries. ✅Thirdly, we display how lineage makes it possible to visually retrace your data to the source. Fourthly, the need for data exploration is stressed, enhancing the searchability of your data. ✅In addition, by limiting the amount of searchable data, it is shown how Unity Catalog can help facilitate self-service. ✅Lastly, we deep dive into one of the most recent features called Delta Sharing, which makes data sharing across organizations a walk in the park. Read the full blog post via the link below 👇🏻 https://lnkd.in/eznAqbXu #blogpost #IntellusGroup #UnityCatalog

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📢 Join Andrzej Leszkiewicz and I next Friday November 15th @ 9:30 AM (PT)! Discover how to enhance your Power BI workflow with Tabular Editor and the OpenAI API. This presentation demonstrates how, with a few simple C# scripts, you can directly access the OpenAI API from Tabular Editor to create a custom AI assistant with full access to your Power BI report’s data model—including tables, columns, relationships, measures, calculation groups, and more. Use this assistant to comment on DAX code, generate model documentation, write measures, and more, harnessing the full power of the latest OpenAI models—all without the need for Power BI Premium or Fabric capacity. An OpenAI API subscription is required, and Tabular Editor 3 is necessary. https://lnkd.in/gK3d-8yf #PowerBI #TabularEditor #TE3

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https://lnkd.in/daBNTQw6 - Metadata-driven approach for building Delta Live Table pipelines has got tons of possible applications: - you can create whole complex pipelines for your source bronze tables in fully automated way for numerous source tables on scale (e.g. from CDC files loaded into S3 buckets) - validate and monitor data quality on scale with expectations - use best patterns for loading and CDC data processing (streaming AutoLoader with checkpoints) and then aggregate and join (static frames) within single automated pipeline - adding new rules and tables require very little changes once the project is automated with config objects - you can actually isolate testable Spark code from “humble objects” (classes and functions that are difficult to test locally) in elegant way - especially when you choose PySpark over SQL (I do) - final clean tables can be distributed to clean views or catalogs as dynamic views (no redundancy and data replication) - deployment, monitoring and alerting could be fully automated with Asset Bundles and your favourite CICD tool #DataEngineering #MetadataETL #ETLonScale #Databricks #Spark #DeltaLiveTables #ChangeDataCapture #AutomatingLakehouse

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