Ed Sandoval

Databricks Unity Catalog is the industry’s only unified and open governance solution for data and AI, built into the Databricks Data Intelligence Platform. With Unity Catalog, organizations can seamlessly govern both structured and unstructured data in any format, as well as machine learning models, notebooks, dashboards and files across any cloud or platform. Review Kiran Sreekumar's blog below on the top 10 Data Governance tips for Unity Catalog! Thanks Kiran Sreekumar! #databricks #unitycatalog #datagovernance

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Check out HealthDataViz's latest blog article "Improve the UX of Tableau Filter Selections with a Dynamic Error Message" https://hubs.li/Q02Bm-ml0. In this blog Katie Bueno shares a trick for handling user messaging when a chart goes blank due to advanced filtering. #Tableau #dataviz #BlogPost

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There's still time to book! Semantic Data 2024: Taxonomy, Ontology, and Knowledge Graphs on 27 June features a fantastic line up of leading practitioners from well-known businesses sharing valuable insights into the latest developments and best practices in the field of semantic data. This is your opportunity to dive into the future of knowledge engineering, AI, and data management with our esteemed speakers and comprehensive agenda. And we will be there too! Find out more and register today! https://buff.ly/3yoMeAS #taxonomy #semanticdataLDN #ontology

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Friday... it's time to spend some time onto learning fundamental things.... Today - we're talking about BigQuery Data Manipulation Language (DML). 📚 Highlights: • Introduction to Data Manipulation Language • Detailed Examples for Inserting, Updating, and Deleting Data in the Tables • Change Data Capture (CDC) and DML 💡 Whether you’re new to data analysis... or looking to enhance your skills, this guide will help you leverage DML and improve data workflows. 📝 Read the full article here: https://www.owox.com/c/5ng #BigQuery #DML #dataanalytics #OWOXBI #GoogleBigQuery #datamanipulation

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EK's Lulit Tesfaye and Jeff Jonas of Senzing teamed up on EK's latest blog, in which they discuss typical problems that would necessitate Entity Resolution, how to unify enterprise data with a Semantic Layer, and the role of entity-resolved knowledge graphs. #semanticlayer #knowledgegraph #entityresolution https://lnkd.in/ePujrbve

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🗞 Read two new blog posts by Joe Massey and Elena Simperl from Open Data Institute, and Vinay Narayan from Aapti! 1️⃣ How can we empower data communities in the era of generative AI? This blog looks at how generative artificial intelligence (GenAI) is altering the ways communities function online! 🔗 https://lnkd.in/gJbZ7JN3 2️⃣ Why the UN Global Digital Compact needs to get serious about participatory data This blog explores the potential of the Global Digital Compact and seeks to unpack how participation in the data economy is an important part of achieving its aims. 🔗 https://lnkd.in/g8wa9ftH #tech #globaldigitalcompact #data #participation

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WorFBench: A Benchmark for Evaluating Complex Workflow Generation in Large Language Model Agents Large Language Models (LLMs) have shown remarkable potential in solving complex real-world problems, from function calls to embodied planning and code generation. A critical capability for LLM agents is decomposing complex problems into executable subtasks through workflows, which serve as intermediate states to improve debugging and interpretability. While workflows provide prior knowledge to prevent hallucinations, current evaluation benchmarks for workflow generation face significant challenges. Read the full article: https://lnkd.in/eqv7pQCt Paper: https://lnkd.in/eWDxh6Vz

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Back in March, #Databricks launched #DBRX—a super-advanced state-of-the-art open language model that's truly next-level. This new model marks a major step forward for #OpenSource #LLMs. What’s really cool is that DBRX outperforms nearly all established open source models and even rivals #ClosedSource giants like #GPT4, #Gemini, and #Mistral across various benchmarks. Want to know what makes #DatabricksDBRX so awesome? We've got you covered! Check out the full article below to learn everything you need to know about it. https://lnkd.in/g3w845G7

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Stay up to date with the latest data news 🧙‍♂️ https://lnkd.in/e6YA3YMg Some crackers this week 🧠 Why we switched our Python ELT integrations to Go @Jack P 🧠 Using Iceberg tables in Snowflake from Aida 🧠 A useful comparison of Snowflake vs. Databricks Hugo Lu 🧠 Validating data in Pandera Conal Henderson 🧠 5 Lessons from 5 Data Teams Tim Webster 🧠 The Snowflake questions people asked me on my Udemy course Cristian Scutaru LinkedIn🕴 🕴EHR Data 101 Phil Ballentine, MSc 🕴Video explainer of the Databricks Snowflake war Dan Williams #dataengineering #startup #growth #analytics

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Check out the latest blog from one of our Data Surgeons, Nathan Rayens, PhD, as he discusses 5 Key Elements for Responsible AI. At Data Surge, we believe this topic is so important in our fast-paced world. Interested in learning more, email us at [email protected]. #AI #ML #ResponsibleAI #DataModernization

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Unlocking AI Potential! Snowflake partners with Meta to bring Llama 3.1, a powerful multilingual large language model, to Snowflake Cortex AI. This collaboration enables enterprises to build scalable AI applications with: ▶ Optimized performance ▶ Advanced safety features ▶ Seamless access and deployment Empowering businesses to drive innovation and growth with AI. Read more : https://lnkd.in/eQAkp2Z6 #Snowflake #Meta #AI #Techxmedia

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Open data, communities, and the role of gamification Sam Milsom and Pauline Roche led a discussion at Open Data Camp on how open data can work for communities, and people who are not data people. This blog captures their views and covers suggested techniques for best practice. https://buff.ly/4bQQmb5

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This is what a real-world AI workload looks like 🌐 #theCUBE is live at #SASInnovate In this keynote analysis, John Furrier, David Vellante & Rob Strechay discuss SAS’ role in the emerging AI stack model. “You’ve got SasS for AI, and AI for SaaS infrastructure,” says John Furrier, spotlighting some key moments from SAS CTO Bryan Harris’ keynote. “He had real meat on the bone, real use case production,” Furrier recalls. “He called up production workloads and all those were based upon Amazon infrastructure. So again, back to who wins here? Amazon’s got the models but they’re running infrastructure on top of that. SAS has their intelligent decision engine next layer up. “That’s their core layer, and next is modules for real-time data. Knowledge bank and process models. Then the gen AI layer on top. Then the interface. This is a real world production workload running in the AI stack,” Furrier concludes. 📺 Tune in live, now! theCUBE.net #LiveNews

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Heading to Databricks's #DataAISummit? Connect with fellow attendees interested in improving LLM evaluations and feedback techniques by grabbing the last available spot for Arjun Bansal's braindate at the event ⬇️ https://lnkd.in/gAT6PTYt If you didn't get a spot in the group, you can still learn about Log10's approach in Arjun's conference session, AutoFeedback: Scaling Human Feedback with Custom Evaluation Models, or at Log10.io #LLMOps #LLMs

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In today's Fortune #CIO Intelligence newsletter via John Kell, Collibra CEO Felix Van de Maele shared insights from the latest survey with The Harris Poll that found a majority of #AI decision-makers don't trust the U.S. government's current approach to AI regulation. #datagovernance #dataquality #TSEclientwork Collibra CEO Felix Van de Maele tells Fortune that ''the more the U.S. can create a regulatory framework that gives those organizations the visibility, the clarity, and the predictability'' to oversee the technology as it develops, ''the faster organizations can actually move AI use cases into production.'' Read the full newsletter below👇: https://lnkd.in/g5ZQADc7

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The TetraScience team joined the 60,000 other data practitioners at last week’s Databricks #DataAISummit in San Francisco. (In case you missed it, TetraScience announced a strategic partnership with Databricks a few weeks ago to accelerate the Scientific AI revolution.) We had some great conversations at the summit with leaders in data and analytics in the life sciences. The intel we gained from our discussions and what we heard during the keynotes and breakouts can boil down into three essential takeaways worth sharing with the TetraScience community. The tl:dr? - Every business wants to be an AI business - Nearly all organizations are still in the early stages of their AI journey - The state and quality of enterprise data continues to be the big stumbling block Read more takeaways from Naveen Kondapalli, SVP Product & Engineering at TetraScience, including insights from sessions with Sander Timmer, PhD at GSK and Pushpendra Arora at Merck: https://lnkd.in/eGq7NJ_p

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