Chaos Genius’ Post

https://lnkd.in/gw-C-zjA This is a big deal for me. If you’ve been to one of my workshops, no matter the tool, you’ve probably heard me say at least twice, “Leverage your data platform as much as you can for complex calculations.” Yet, so many people still get stuck building elaborate cathedrals of calculated fields or DAX measures instead of writing a few simple lines of code in the data platform. Now, with Databricks making it possible to publish Power BI Datasets directly from Unity Catalog, the starting point for analysts has completely shifted. When I talk about visual literacy, I always bring up how the way you're facing in the beginning creates functional momentum. This change finally gets analysts facing the right direction from the beginning. Instead of jumping straight into the reporting tool to build your calculations, you can start in your data platform, handle as much as you can there, and save the report-level tweaks for the reporting tool. Databricks has finally put the horse in front of the cart. It’s a small shift, but one that makes a huge difference. #powerbi #databricks #visualization #dataengineering

Quick Tip: Whenever you make design decision, make sure that you use the 'right tool for its purpose'. With respect to Databricks and Power BI :-- 1. Implement the 'Medallion Architecture' in Databricks and perform the following operations in the appropriate layers, Bronze Layer -- Raw data Ingestion ('As-is' source format) Silver Layer -- Cleaned/Filtered/Transformed data. Here is where you can even have your 'facts' and 'dims' (Star Schema Model) Gold Layer -- Denormalized views/ Ready for reporting / Business Aggregated data / Business specific naming conventions 2. Once the Gold layer is ready -- bring in the required 'Gold' tables into Power BI Dataset and start creating relationships/model between the Gold tables and create KPIs using DAX measures. Power BI Dataset is an area where you need to create your dynamic calculations (i.e. calculation based on the user selections of the filters/slicers in the report). Here is where DAX measures comes into place and it is a perfect use for the 'Dynamic based calculation/measures'. Power BI Dataset is also an area -- where you need to create a relationship between the Gold layer tables ( from Databricks ) to enable the filter/data flow and enable the instructiveness in the report canvas area. 3. Visualization -- Use Power BI Reports to display the insights in a meaningful visual format that can be sliced and diced with different data points/visual elements available in the report page. Conclusion: We must ensure that we use the right tool according to its purpose. We should not be creating any calculated columns / calculated tables / aggregated tables within Power BI Dataset instead it should be done at the upstream end/Databricks end (at the gold layer) which is the right area to perform the operations. Similarly, we must not create any dynamic calculations in the Databricks end as it is difficult to pre-compute the results based on the different possible selections made by the end users in the report side, instead these kinds of dynamic calculations should be created using Power BI DAX measure inside Power BI Dataset (downstream side). #databricks #powerbi #medallion architecture #gold tables #DAX measure

🔗 Unlock the Power of Your Data: Connecting Databricks to Power BI 🚀 Are you struggling to visualize your Databricks-stored data in Power BI? You're not alone! Many data professionals face this challenge, but we've got you covered. In our latest blog post, we've broken down the process of seamlessly connecting Databricks to Power BI, opening up a world of analytical possibilities. Here's what you'll discover: ✅ Step-by-step guide for first-time users  ✅ Tips for working efficiently with Databricks  ✅ Best practices for a smooth Power BI integration  ✅ Common pitfalls and how to avoid them Whether you're a data analyst, business intelligence professional, or just curious about leveraging these powerful tools together, this guide is for you. Ready to supercharge your data visualization game? Click the link here to read the blog post: https://lnkd.in/d_jDCfNV #DataAnalytics #BusinessIntelligence #Databricks #PowerBI #BigData #DataVisualization #ApacheSpark #CloudComputing #DataScience #MachineLearning #ArtificialIntelligence #DataDrivenDecisions #DataEngineering #BusinessAnalytics #DataIntegration #DataProcessing #TechInnovation #DigitalTransformation #DataMining #PredictiveAnalytics #DataWarehouse #BusinessStrategy #DataGovernance #DataArchitecture #ETL #DataModeling #RealTimeAnalytics #DataLakes #DataOps #AzureDatabricks #MicrosoftPowerPlatform #DataInsights #AdvancedAnalytics #DataStorytelling #DataEcosystem #ScalableAnalytics #DataDemocratization #SelfServiceBI #DataLiteracy #DataCulture #DataStrategy

The best #DataIntelligencePlatform with the best BI tool! What a combination!! In this blogpost Andrey Mirskiy, Yatish Anand, and I share our insights and recommendations on efficiently adopting existing Power BI semantic models on #DatabricksSQL 🚀 I truly appreciate Andrey's mentorship. With his guidance, my understanding of this topic steadily increased(and I really hope it continues like this). https://lnkd.in/dHTUC5n4 #Databricks #PowerBI #BusinessIntelligence

If you need a definitive guide to PowerBI semantic models on Databricks SQL, check out this awesome blogpost co-written by my fellow colleague Mohammad Shahedi !

Databricks Unity Catalog now integrates directly with Power BI for seamless, governed data access. Secure insights, faster analytics, and simplified governance—bridging data engineering and BI like never before. 👉 https://lnkd.in/gV32pUB3 #databricks #PowerBI #DataGovernance #Analytics

Imagine this: You’re accessing real-time insights from Delta Lake directly in Tableau, sharing data with ease, and collaborating like a pro. With the Tableau-Databricks Delta Sharing Connector, that dream is now a reality. 🌟 This integration is a big win for data teams who need to: 📊 Analyze data from diverse sources effortlessly. 🔒 Ensure data security while collaborating across platforms. 🚀 Save time and focus on delivering insights, not battling workflows. If data collaboration is a challenge you face, this solution could well be what you’ve been waiting for. 👉 Read the article here: https://lnkd.in/eviWksCP Don’t just share data—share insights that matter. I’m looking forward to seeing where “Explore in Tableau” goes… === Steve “Sharing is Caring” Adams Want great #DataFam content? Follow my LinkedIn #TableauTraining page : https://lnkd.in/eqM-_9zb 👉 Psst. I’m delivering a 2 day Tableau jumpstart course for beginners later this month. Let me know if you want to get on the waitlist for more details. #Databricks #Tableau #TableauTraining

Exploring Databricks for BI Dashboards: Is It a Game-Changer for Visualization? Databricks is expanding beyond data engineering and machine learning, offering integrated BI dashboard capabilities that may reduce the need for separate tools like Power BI or Tableau. But is it the right choice for your needs? Let’s explore. # How to Use Databricks for BI: With SQL Analytics and Databricks SQL Workbench, Databricks allows users to: - Query data using SQL and view results instantly. - Create visualizations and dashboards on existing data in the Lakehouse. - Share insights with teams in one collaborative space. # Benefits of Using Databricks Over Separate BI Tools: 1. Integrated Lakehouse Platform: No need to move data to other tools, reducing ETL efforts. 2. Cost Savings: Using Databricks’ BI features can eliminate expenses for separate tools. 3. Real-Time Insights: Databricks can pull batch and streaming data, so dashboards stay up-to-date. 4. Scalability: As data grows, Databricks handles larger datasets more efficiently than some standalone BI tools. # Potential Drawbacks: - Advanced Visuals & Customization: Power BI and Tableau offer more customization options. - User-Friendly Interfaces: Tools like Power BI and Tableau have broader ease of use, especially for non-technical users. # Final Thoughts: For Databricks users, using its BI capabilities could save time and costs. However, for specialized or highly customized dashboards, Power BI or Tableau might still be better. If you found this helpful, please repost! 🌟 Explore More: - Course: https://lnkd.in/dtATeZUP - ADE Group: https://lnkd.in/dKCwXfJM - Blog: https://lnkd.in/dXmJHvpG Follow Satish Mandale for insights on data engineering, BI, and cloud. ### Tags: #Databricks #BusinessIntelligence #DataEngineering #BigData #SQL #Lakehouse #Visualization #Azure #PowerBI #Tableau #DataScience #DataAnalytics #DigitalTransformation #CloudComputing #QuantumTechAcademy

A lot of my customers ask for two things when they are working with or evaluating Databricks: - how to easily report on their data - how to do it cost effectively With the recent GA of Lakeview Dashboards, Cody Austin Davis wrote up a great blog that answers both of those questions. *Added bonus - our AI assistant can do a lot of the heavy lifting for you. 💪🏼 Check it out! #databricks #ai

🚀 Loading Databricks Delta Tables into Power BI 🚀 As data grows, integrating Databricks Delta tables with Power BI unlocks powerful real-time insights. Let’s explore how to load Delta tables into Power BI and maximize your analytics. 🔷 Steps to Get Started: 1️⃣ Connect to Databricks: - In Power BI Desktop, go to Get Data > Azure > Azure Databricks. - Enter your Databricks URL and authenticate with your Access Token. 2️⃣ Access Your Delta Tables: - Query Delta tables stored in Databricks. Make sure the Delta tables are formatted for integration. 3️⃣ Load Data: - Load the Delta tables into Power BI. Use Power Query Editor to clean and transform your data. 4️⃣ Optimize Queries: - Leverage Databricks SQL to optimize queries. Use filters and aggregations to minimize load times in Power BI. - Delta Lake’s ACID transactions and time travel ensure data consistency. 5️⃣ Create Reports: - Build visuals and dashboards in Power BI using the data from Databricks. Set up relationships and measures for rich, interactive reports. 🔶 Why Integrate Databricks Delta with Power BI? - Unified Analytics: Combining Delta Lake’s big data architecture with Power BI’s visuals provides scalable insights. - Real-Time Data: Delta Lake’s transaction logs enable real-time data analytics, ensuring your Power BI reports are always up-to-date. - Data Integrity: Delta Lake’s ACID transactions maintain accuracy and reliability in your data pipelines, reducing reporting errors. 🔍 Best Practices: - Partition Data: Use data partitioning in Delta Lake to improve query performance. - DirectQuery: Use DirectQuery in Power BI to minimize data duplication and fetch fresh data from Databricks. - Time Travel: Leverage Delta Time Travel to access historical data for comparative analysis in Power BI. 🔗 To learn more, check out the official guide on integrating Power BI with Databricks: [Databricks Documentation](https://lnkd.in/dtWXXSPE) Bringing Databricks Delta tables into Power BI empowers data professionals with **fast, reliable, and scalable** analytics. Whether tracking key metrics or performing real-time monitoring, this powerful integration takes your analytics to new heights! 💡 #Databricks #PowerBI #DataEngineering #DeltaLake #Analytics #DataVisualization #BusinessIntelligence #BigData