Thomas Palm

Have you made your schedule for Snowflake's #DataCloudSummit yet? Be sure to join Philipp Unterbrunner and Daniel Odievich’s session to learn how Observe enables all types of observability workloads — logs, metrics, traces, application performance and security — as well as complex business data analytics, over a single connected data lake. Session details 👇 ❄️ Building Observe — The Observability Platform Powered by Snowflake (AD233)  📅 June 6  🕚 11 AM PDT Add it to your schedule ☑️ https://lnkd.in/gHJ7eAzq 

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Tomorrow is the day, the Databricks Roundtable is taking place in Cologne.🚀 Join us for an exclusive hands-on session where Philipp Schwartenbeck will present a multi-agent system and Felix Xaver Krisch will demonstrate the complete lifecycle of a data product directly in Databricks! In the live demo, we will take you through the entire journey of a data project - starting with data exploration, followed by incremental data processing, workflow scheduling and scaling. We'll also show you how to implement CI/CD pipelines and monitoring tools to ensure seamless project delivery in Databricks. In the second live demo, we'll dive into the world of LLM-based multi-agent systems. See how autonomous collaboration between agents can solve complex tasks in real time, helping organisations improve the efficiency of their data processing and decision making! Find all the event details and register now... there are only 3 places left❗ 🔗https://lnkd.in/g_EyDuHp Looking forward to seeing you tomorrow! #databricks #dataengineering #AI #multiagent #LLM #cloudmigration #datagovernance #realtimedata #dataplatform #changemanagement

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Join Databricks on November 7th for Data + AI World Tour Munich! Discover how leading companies like Fraport AG, Deichmann SE, Bayer AG, and CARIAD SE (A Volkswagen Group Company) are taking control of their data and building custom AI on the Databricks Data Intelligence Platform. Register now!

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Let’s have a sneak peek of track #2: Data & Storage at the upcoming Data Conference Switzerland on 25th October in Zürich. 🎤Heini Ilmarinen - Super Smash: Microsoft Fabric vs. Databricks Compare the capabilities of Microsoft Fabric and Databricks to see which one can dominate in lakehouse solutions. 🎤Charley Hanania - The Parquet File Format: Under the Hood Explore the structure, encoding, and optimization of Parquet files and alternatives like Delta Lake Tables. 🎤Nikola Ilic - 50 Shades of Direct Lake Discover Microsoft Fabric’s Direct Lake mode, its architecture, and when to use it over Import mode. 🎤Andy Cutler - Microsoft Fabric Warehouses for the DBA Learn the essential aspects of administrating Fabric Warehouses as a cloud-based SQL service for data warehousing. 🎤Paul Andrew - Real-time Intelligence with Microsoft Fabric: What, Why & How Understand how to build real-time analytics solutions with Fabric’s Real-time Hub using SQL and KQL. Don’t miss out on the chance to learn from industry experts and dive into the latest innovations. Visit Data Conference Switzerland for more details! #DataConference #MicrosoftFabric #DataStorage #RealTimeAnalytics #PowerBI

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📷 New on YouTube: In his 2023 #SAGconf session, Matthias Niehoff delves into the latest developments in modern data architectures, including Data Mesh, Data Lakehouse, and the integration of analytics with operational systems, offering insights into their practical implementation. 👀 Watch now: https://lnkd.in/eHs3EkZa #SoftwareArchitecture #SoftwareArchitectureGathering #SoftwareArchitectureConference #DataArchitecture #DataMesh #DataLakehouse #ELTPattern #CloudDataWarehouse #ModernDataStack #DataStrategy #SoftwareEngineering

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❄️ 𝐄𝐱𝐩𝐥𝐨𝐫𝐢𝐧𝐠 𝐒𝐧𝐨𝐰𝐩𝐚𝐫𝐤'𝐬 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬 𝐟𝐨𝐫 𝐏𝐲𝐭𝐡𝐨𝐧 𝐃𝐞𝐯𝐬 𝐨𝐧 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞 🐍 Ever wondered how to leverage the scalable compute power of Snowflake’s virtual warehouses to empower your data applications using your favourite programming language? In this blog post, we will take a deeper look into the Snowpark API and explore how you can efficiently build scalable #Python-based data applications including third-party and custom dependencies on the Snowflake Data Cloud. 🔍 𝐖𝐡𝐚𝐭 𝐘𝐨𝐮'𝐥𝐥 𝐋𝐞𝐚𝐫𝐧 · Introduction to Snowpark: Discover how Snowpark simplifies querying and processing large datasets in your favourite programming languages like Python. · Setting Up: Step-by-step guide on how to create a Snowpark session and connect to Snowflake. · Advanced Features: Dive into User-Defined Functions, utilizing third-party packages, and integrating custom libraries. · Practical Examples: Real code snippets on setting up your environment, creating and using UDFs, and handling dependencies. 💡 Explore how to enhance your data pipelines and make the most out of Snowflake's computing power using Python: https://lnkd.in/e7_isjD3 📚 This is blog post #8 in our inovex GmbH Snowflake series. Check out our previous articles here: https://lnkd.in/ew9pPBDk #DataEngineering #Snowflake #Snowpark #Python #BigData #CloudComputing

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𝗪𝗵𝗮𝘁 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗶𝗮𝘁𝗲𝘀 𝗢𝗿𝗮𝗰𝗹𝗲 𝗶𝗻 𝘁𝗵𝗲 𝗔𝗜 𝘀𝗽𝗮𝗰𝗲? I explored this fascinating topic in a conversation with The Recursive, a leading European tech media title. Three important parameters are critical for enterprises to have a successful AI journey. They are: 𝗮 𝗴𝗼𝗼𝗱 𝗮𝗺𝗼𝘂𝗻𝘁 𝗼𝗳 𝗱𝗮𝘁𝗮, 𝗮 𝘀𝘁𝗿𝗼𝗻𝗴 𝗰𝗹𝗼𝘂𝗱 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲, 𝗮𝗻𝗱 𝗮 𝘀𝗼𝗹𝗶𝗱 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗼𝗳 𝗵𝗼𝘄 𝘁𝗼 𝘂𝘀𝗲 𝗱𝗮𝘁𝗮 𝗲𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲𝗹𝘆. #Oracle has been a pioneer in handling enterprise data for the last 45+ years. We understand data architecture better than any other provider in the world. Couple that with our vast experience in servicing all types of customers and helping them use #data to solving countless problems. This wealth of knowledge is a key differentiator for Oracle, making it well-positioned to be EMEA’s AI hyperscaler of choice. Learn more about how Oracle is driving #AI transformation in EMEA, leading the industry with our EU Sovereign Cloud offering, and powering the AI-driven growth of the region’s startups. https://lnkd.in/dYkPfu4E

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💠 "Vectorizing data will be part of all common cloud data warehouses in the future." In our last episode of #MetaDAMA, Pedram Birounvand and Winfried Adalbert Etzel talked about the possibilities of AI, Vector databases, and RAG beyond its current use. Data Management as a profession has potential of advancement and scale by introducing new ways of working. The idea and identified need for automating Data Management as well as Vector Databases are already present in Gartner Hypecyle on Data Management. Pedram is connecting these to. And there are a couple good reasons here: 💡 #VectorDatabases provide semantic structure. 💡 Vector Databases store data through numerical representation. 💡 Vector Databases can due to the high-dimensional number of vectors represent structured, semi-structured and unstructured data. 💡 Vector Databases provide #vectorsearch functions that naturally return semantically similar terms. 💡 Vector search can ensure faster data retrieval due to the indexing possibilities of embeddings. 💡 Vectorizing data can potentially change semantic data modeling. 💡 The need for #datamodeling as a profession can be disrupted on the conceptual, semantic level. What do you think is the potential of Vector Databases for Data Management? Listen in to the episode here: https://lnkd.in/dgJdG2i9 Data Management Association Norway (DAMA) Den norske dataforening (DND)

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Webinar Alert: Setting the Standards for Semantics in AI and BI Webinar 📊 On Dec 11th, watch AtScale Founder and CTO, David P. Mariani join Databricks EMEA CTO, Dael Williamson for an in-depth discussion on the new open source Semantic Modeling Language (SML).    Topics covered in this webinar:   - How SML speeds up analytics adoption, simplifies migrations between proprietary vendor solutions, and expands access to data and analytics for a wider audience - How to integrate your Semantic Layer with Unity Catalog Metrics, Lakehouse Federation, AI/BI, and more! Don’t miss your chance to register here 👉https://lnkd.in/dN7aTaSJ #DataDriven #DataAccessibility #Analytics #ArtificialIntelligence #AI #BusinessIntelligence #AtScale #Databricks #SML #OpenSource #SemanticLayer

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Join Databricks on November 7th for Data + AI World Tour Munich! Discover how leading companies like Fraport AG, Deichmann SE, Bayer AG, and CARIAD SE (A Volkswagen Group Company) are taking control of their data and building custom AI on the Databricks Data Intelligence Platform. Register now!

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📊 Simplify Data Modeling with Bold Data Hub Effortlessly process, clean, and transform data from multiple sources. ✅ Seamless integration with Bold BI ✅ Flexible loading options (SQL, cloud, Apache Doris) ✅ Customizable data extraction ✅ Automated workflows & large file handling Explore more: https://lnkd.in/eqfubwFY #DataIntegration #DataModeling #BusinessIntelligence #DataTransformation

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📊 Simplify Data Modeling with Bold Data Hub Effortlessly process, clean, and transform data from multiple sources. ✅ Seamless integration with Bold BI ✅ Flexible loading options (SQL, cloud, Apache Doris) ✅ Customizable data extraction ✅ Automated workflows & large file handling Explore more: https://lnkd.in/eqfubwFY #DataIntegration #DataModeling #BusinessIntelligence #DataTransformation

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“Teradata's new integration with DataRobot enables organizations to simplify combining data with AI and machine learning by applying DataRobot's prebuilt models to their data in VantageCloud.” How does this new integration enhance your organization? 🔶 Data scientists require flexibility with tools for innovation. DataRobot, a full AI platform, supports both predictive and generative AI models, offering choice and flexibility. 🔶 Enterprises seek secure, accountable model deployment with cost control. Teradata VantageCloud enables scalable deployment of DataRobot AI models directly where data resides, across cloud providers and on-premises. 🔶Through BYOM, VantageCloud users access DataRobot AI models seamlessly within their environment. This integration includes importing models for efficient, cost-effective scaling using ClearScape Analytics' scoring functions, eliminating extra licensing costs. Read more with TechTarget: http://ms.spr.ly/6040lVsIu

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Snowflake introduces Arctic LLM, a generative AI model tailored for enterprise needs #AI #AItechnology #ArcticLLM #artificialintelligence #CEO #Efficiency #enterprise #GenerativeAImodel #llm #machinelearning #Ramaswamy #Scalability #Snowflake

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Join Databricks on November 7th for Data + AI World Tour Munich! Discover how leading companies like Fraport AG, Deichmann SE, Bayer AG, and CARIAD SE (A Volkswagen Group Company) are taking control of their data and building custom AI on the Databricks Data Intelligence Platform. Register now!

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In a previous video, I demonstrated how to Mirror Snowflake Database [https://lnkd.in/ewEmc26X] exactly 1 hour after the public preview announcement of the feature! This new video shows how to Mirror Azure Cosmos DB in Fabric Warehouse: Watch Here: https://lnkd.in/eXUu94dN If you like the video, give it a thumps up, share and comment in the section below #MicrosoftFabric #Mirroring #AzureCosmosDB

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Data trends 2024: Strategies for an #AI ready foundation Join Snowflake experts to discover best practices for building a modern data foundation to prepare for success with advanced #AI. https://okt.to/GUTHi8

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