Dominik Classen

Join us on September 30th to discover how Skai leveraged the power of #Cortex #GenAI together with AI21 Labs and Bright Data! https://lnkd.in/dagx5ztg

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Tableflow effortlessly converts streaming data in #Kafka into #ApacheIceberg tables with a single click, feeding any data warehouse or datalake.

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Snowflake: Iceberg Dynamic Tables https://lnkd.in/gtCpgHgu

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Interested in a preview of Airflow 3.0 (Airflow 2.0 was 4 years ago). Take a look at Julian LaNeve talking about the latest release and a preview of what is coming. https://lnkd.in/eFPvwbHZ

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Databricks + Slalom + Amperity will share the virtual stage on Wednesday (4/24) at 10a PST. Learn how to turn raw, disconnected customer data into business value.

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The Snowflake #DataCloudSummit 2024 is just around the corner so it's a good time to build your agenda. Are you interested in #DataEngineering? Curious about Snowflake Native Apps? Eliott Pourrat and myself will present how we turbocharged our Maxa Native App with Snowpark Container Services and Dynamic Tables. Register here: https://lnkd.in/eWTN_-ef #snowflake #SnowflakeDataCloud #datacloud #snowflake_advocate #DataSuperHero Howard Lio Elsa Mayer Monique Lupu Unmesh Jagtap Eduardo Laureano Xuewei (Phoebe) He

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#DatabricksSQL warehouses provide up to 12x improved price performance over standard interactive clusters. You can now use Databricks Notebooks on SQL Warehouses to write and schedule Git-backed, multi-statement, and parameterized SQL👇 https://dbricks.co/4agOeJo

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Augmenting data lakes/warehouses, for speed at scale, has always been our forte... and now it's even easier than ever - for any datastore using Iceberg tables. Technical overview below.

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If you manage #R models and need a way to streamline deployment while boosting performance, join our session on November 27 at 11 a.m. ET! We’ll show you how #Snowflake and #Posit work together to optimize your workflow, from model training to real-time inference, so you can make secure, data-driven decisions without leaving Snowflake. During the demo, we’ll cover: - How to fit an R model using Snowflake data for direct, seamless integration - Versioning and evaluating your model to ensure consistency and reproducibility - Performing fast model inference directly in Snowflake, saving time and computational power - Storing and accessing models in Snowflake so they’re available to other users and tools (like Snowsight and Python) 📅 Reserve your spot today: https://lnkd.in/eDWrgxyV

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Exciting news! Snowflake Cortex Analyst is now available for everyone to try out. This service makes it super easy to chat with your structured data in Snowflake, helping business users create their own analytics apps without hassle. Plus, you can count on top-notch accuracy! Want to know more? Check out the blog https://okt.to/WYgxh0

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🎯 Special session report #SnowflakeWorldTour #Berlin: At the exclusive Snowflake engineering session, Ismail Oukid shared in his talk a great deal of information about Snowflake “Automatic Performance: A Story of Continuous Innovation” with around 200 customers, partners + a few Snowflakes. “#AutomaticPerformance" is a guiding principle of Snowflake's engineering team for improving the product and implies  ➡️ Ease of use ➡️ Best price/performance out of the box ➡️ If tuning is required, the system auto-tunes itself Performance improvements in query duration experienced by customers over time, is measured and reported via the #SnowflakePerformanceIndex (SPI). As of now, Snowflake improves performance by 27%, according to the SPI https://lnkd.in/ePY9_y8X But how does the engineering team identify areas for improvement and takes action? Here are some examples: ➡️ Customer feedback!! (from the field, PoC's, surveys, events like Summit, Build conference, World Tour, and day-to-day biz/issues) ➡️ Telemetry Analysis (Snowflake's own data warehouse, hot spots, repeating patterns, benchmarks) ➡️ Disruptive innovation (with focus on long term value) Since there is no recording of Ismail's presentation, I would like to highlight some engineering blog resources instead that provide detailed insights into how continuous performance improvements are achieved at Snowflake: ➡️ Snowflake Speeds Up Workloads With Hierarchical Selectivity Estimates - https://lnkd.in/e8WS9nq3 ➡️ Continued Investments in Price Performance and Faster Top-K Queries - https://lnkd.in/exX8TKuR ➡️ Adaptive Network Optimizations for Faster Query Performance - https://lnkd.in/eJSVSuTK And finally, it is highly recommended that you regularly check the release notes documenting the latest performance improvements (2024) - https://lnkd.in/eWajKni2 My tip: join the #SnowflakeWorldTour next year (especially in Berlin) and don't miss the engineering sessions if you want to know more about the Snowflake platform internals!

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Introducing the Secrets of Apache Spark to Snowflake Migration Success! This book highlights 9 real-world customer stories that illustrate the value of migrating from Databricks to Snowflake — from Travelpass saving 65% in costs to the New York Stock Exchange cutting costs in half for its regulatory reporting workload to Swire Coca-Cola, USA accelerating time to market for its products. This book also includes 5 compelling reasons why companies are moving from Databricks to Snowflake — ease of use/time savings, cost savings, performance, governance and data sharing — and supports each reason with concrete customer examples, quotes and/or metrics.

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Start talking to your data, in natural language, in your context. No need to be a data specialist. Democratizing Data+AI....

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Databricks AI/BI Dashboards now offers even more intuitive ways to interact with your data to get new insights. New features include: ✅ Cross-Filtering ✅ Static Widget Parameters ✅ Filter Default Values ... and more. See them in action👇

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