Jeff Hollan

evolv has had a blast so far at #DataCloudSummit! Watch the recap from Snowflake for a quick highlight reel of the first two days!

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Stream from sources like Kafka and Kinesis with Upsolver and run Lakehouse Analytics with Dremio. This is an end-to-end Apache Iceberg Data Lakehouse tutorial. https://lnkd.in/deSwKsEB

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Fresh out of the oven 🔥 Rudol now supports Databricks! Classify, Document and massively Validate the Quality of your Databricks data, now available in all our Plans (including the Free tier 😁).
 Try now at http://rudol.ai

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🌐 While our single-tenant model is incredibly valuable, it does present some challenges when it comes to observability. Because all of our metrics are localized to customer-specific GCP instances, managing and viewing metrics across the entire fleet becomes complex. Bridget Went breaks down recent enhancements to our observability capabilities and our journey towards establishing a unified control panel for monitoring the health and performance of our service. Read the full article here ➡ https://lnkd.in/gY8m6fg7

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#ApacheIceberg was built to solve a problem - deliver data warehouse behavior on a cloud object store - but is now disrupting an industry. To learn more, check out this 20 min talk Daniel Weeks gave at last month's #datauniverse conference. https://lnkd.in/gH5ZA4kS

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JFrog announced a new machine learning (ML) lifecycle integration with MLflow, the open-source platform from Databricks. https://lnkd.in/esaHBnt3 #JFrog #MLflow #MachineLearning #MLOps #DevOps #AI #Datbricks

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Join PyTorch at Snowflake's #DataCloudDevDay on June 6 in San Francisco to learn how to accelerate GenAI performance with Native PyTorch. Register: https://hubs.la/Q02xQStt0

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Learn about the intricacies of Adobe's migration from a NoSQL database to #DeltaLake, the custom solutions the Adobe Real-Time Customer Data Platform (CDP) team implemented, and the surprising performance benefits they gained along the way. Read here 👉 https://lnkd.in/emhpGzg8 cc Yeshwanth Vijayakumar, Director of Engineering at Adobe #opensource #oss #lfaidata #adobe

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NetApp’s unique positioning to support AI strategies 🤖 Here is NetApp’s take on AI from Michelle Rudnicki, the company’s president of the U.S. Public Sector. Join #theCUBE at #NetAppDataStorage to gather first-hand insights. “AI today is like the cloud was 10 years ago. It's a really big landscape, and different customers are doing different things within that. With the University of Albany, we help them build a high speed and high performance environment because they're going to be a shared service center to support customers doing AI,” shares Rudnicki. “Data is the fuel that powers AI, and we've been in the data business. We provide our customers with secure environments with governance to enable them to take their data from anywhere, any place. Our connectivity to the cloud allows us to help customers, whether they're doing their applications, and data is resident in the cloud or on-prem,” she adds. 📰 More:  https://lnkd.in/gvYvtJKH #NetAppDataStorage #EnterpriseTech #UnifiedData #AIinfra #ITpros

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New blog post by Alex Monahan: Benchmarking Ourselves over Time at DuckDB The DuckDB team's philosophy is to ensure correctness first, then iterate and optimize to improve performance. This blog explores how this happened over the last three years when DuckDB became approximately 3-25x faster and 10x more scalable. Read more at https://lnkd.in/dnQ7Nya8

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Say goodbye to vendor lock-in! Dremio now supports the Apache Iceberg REST Catalog Specification, championing an open, vendor-agnostic ecosystem. 🌐🔓 Our latest update empowers customers with unmatched flexibility and control over their data, driving enterprise interoperability at scale. 🔗 Dive into the details here: https://lnkd.in/gmZKkSTa #ApacheIceberg #OpenSource

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Exploring Scale AI’s data-centric approach and more ⚡ #theCUBE reports on-site at this week’s #AWSSummit NYC In this exclusive, we’re joined by Vijay Karunamurthy, the Field CTO of Scale AI, to discuss the company’s data-centric approaches, collaboration with OpenAI, and three types of customers. “We took the data-centric approach to computer vision and partnered with some cutting-edge research labs like OpenAI. Today, we have three big buckets of customers. One is the OpenAIs of the world, the research labs that are building the next cutting-edge models. We're helping make those models more trustworthy across a range of new capabilities, like writing code or doing multimodal data, explained Karunamurthy. “The second is enterprises or private companies that are adopting gen AI. They have really unique needs because they have private data that needs to be kept in a VPC in Stockholm, and it can't leave the bounds there. If it does, there has to be really strict role-based access control around how that data is used, even if you have derived data from that data. So, we've built this gen AI platform around that,” he added. “The third big bucket of customers is the public sector. We have a range of agent-driven workflows; it's called Agent Donovan. It helps people with really mission-critical objectives accomplish their work by talking to that commander in the way that they expect to be talked to,” Karunamurthy concluded. 📰 More:  https://lnkd.in/gYmdfKi3 #EnterpriseTechNews #GenAI #theCUBE

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"To ingest the incremental data from Kafka to S3, we considered three excellent data lake and ingestion solutions: Apache Hudi, Apache Iceberg, and Delta Lake. In the end we chose Hudi for its excellent performance with our update-heavy workload and its open-source nature & native integration with Debezium CDC messages." Excellent blog by Notion's data platform team on how they built their data lake (house) to meet the surge in 10x data growth due to user & content growth to cater to AI, Search, and other product use cases. 🔗 Blog: https://lnkd.in/dEYxAZDQ #dataengineering #softwareengineering

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So, what's new in dbt Cloud for June? Quick answer: a lot 🚀 From support for staging environments across various platform experiences, to our Snowflake native app, to the GA of dbt Explorer, dbt Mesh, and the Cloud CLI (oh my!)… there’s something for everyone. We've consolidated an overview of all of the latest features in one easy-to-read blog post. Dive in, below👇 https://lnkd.in/g_mqSgwn

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Matillion x Cortex components now GA 👀 "We are excited to announce that Matillion now supports all of the major Snowflake AI capabilities, in a no-code, easy-to-use platform providing a complete and powerful AI solution that integrates with existing data workflows." Get all the details here (or swing by booths 1517 and 2502 at #DataCloudSummit) https://lnkd.in/eQ3dHm7i #AI #DataEngineering #DataEngineer

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Hugging Face is now part of our ML Connector line-up. Now you can seamlessly integrate your Hugging Face models directly into Domo's secure, controlled environment. Here's what makes it so great: 🛡️ Enhanced security: Keep your data safe within Domo’s trusted platform 👀 Model transparency: Gain insights into how your models are trained and build trust in their outputs 👍 Streamlined workflow: Connect your Domo environment with Hugging Face model endpoints for efficient deployment 🧠 Actionable insights: Turn complex algorithms into practical business intelligence 🔋 Boost organizational efficiency: Connect Hugging Face models to custom Domo apps and solutions Learn more about Domo’s ML Connectors and AI Solutions: https://okt.to/AmhqLv #HuggingFace #Data #AI #BusinessIntelligence #DataDrivenBusiness

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