Paul Gupta

Thank you Databricks for hosting our folks at the Data+AI Summit. The team has been so excited to attend. The topics shared at the event reminded me of a Databricks article from 2021 that celebrated the progress of Arrow: “Apache Arrow has recently become the de-facto standard for columnar in-memory data analytics, and is already adopted by a plethora of open-source projects.” (Read it here: https://lnkd.in/gUEcsgRZ) Arrow recently crossed the 1 BILLION annual download mark. Voltron Data is the leading maintainer and contributor to the Arrow project, and numerous other open standards, and we are incredibly proud to see this. Arrow is actively used for building new integrations with #GPU acceleration that are driving forces for Machine Learning Pre-Processing and Analytics at scale, thanks to the amazing foundation of RAPIDS.ai. Our query engine, Theseus, is built with Arrow and RAPIDS and is a prime example of how powerful tools built with Open Standards are. Theseus can process 100TB queries in SECONDS. Check out the numbers in our benchmarking report: https://lnkd.in/gMKbxcrU

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This week marked a watershed moment for Snowflake: We launched #SnowflakeArctic, a state-of-the-art large language model uniquely designed to be the most open, enterprise-grade LLM on the market. Arctic not only outperforms many leading open models, but we brought it to market at one-eighth of the cost and in less than three months compared to other models. Arctic will significantly enhance our ability to deliver reliable, efficient AI to our customers. By delivering industry-leading intelligence and efficiency in a truly open way to the AI community, we are furthering the frontiers of what open-source AI can do. https://lnkd.in/eueT5Wcs

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There are rumors coming out of Snowflake Summit this week that Snowflake’s launching a semantic layer. Standardizing key metrics like revenue is crucial for streamlining analytics and reporting. DBT and Snowflake's semantic layer products will make this concept mainstream. But metrics aren't the only thing companies lack a standard definition for. Companies care about customers (hopefully) but often don't have a consistent customer definition. Consider a B2C company with customer interactions across multiple channels: 1. Anonymous (guest) visits from multiple devices 2. Logged-in users 3. Physical store interactions Are these interactions considered as one customer or multiple? Is there alignment on this definition between different teams? Is product measuring the funnels for the same set of customers that marketing is targeting with email campaigns? Is data science building life-time-value or churn models for the same customers who are receiving marketing emails? Without a consistent customer definition, teams can't have a shared understanding of the customer's journey. This results in a disconnected experience across product and marketing channels. There's a pressing need for a customer 360 semantic layer. That's what we're building with RudderStack Profiles.

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Using Kumo.AI in your Snowflake environment is like peanut butter and chocolate - better together! Check out this webinar to learn more.

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If you are ingesting data from Kafka/Kinesis into Snowflake you should watch this short video by Charles Tan and Shawn Gordon on how you can use DeltaStream to shift left your workloads to reduce cost and latency! #Flink #Kafka #Snowflake #ShiftLeft https://lnkd.in/gnZ45MTa

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Come meet us at the Snowflake summit in SF next week and learn how we're applying specialized models (large, small, expert, etc.) to enterprise data giving your teams super data powers. #SnowflakeSummit #DataCloud #SanFrancisco #Networking #Data #BI #AI #GenAI #LLMs

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We'd like to show you what Veza can do for critical enterprise systems, please reply in comments for systems you'd like to see and we'll start sharing some! Starting with ... "who can take what action on what data in Snowflake" Permissions unlocked on Snowflake! https://lnkd.in/gSxhH43f #cybersecurity #identitysecurity #IAM #IGA #PAM #VEZA

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https://lnkd.in/gRfUsJbB 🚨 Critical Alert: Snowflake Data Theft Incident 🚨 Recent investigations have revealed that while there's no direct evidence linking Snowflake's products to the recent Ticketmaster breach, there are signs that an account of a former employee was accessed. This highlights a crucial aspect of the importance of managing access controls, especially for former employees. #reinventIAM #CyberSecurity #AI #TechInnovation #AccessManagement #DataProtection Happy to connect if you want to know, how our AI application could have prevented this attack 🤕 #CyberSecurity #CloudSecurity #DataBreach #Snowflake #AI #ThreatDetection #MachineLearning #ZeroTrust #Encryption

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Big announcement today- we’re unlocking Snowflake data for everyone!  With Snowflake Native Amplitude, you get all the benefits of Amplitude without your data ever leaving Snowflake. That means one single source of truth for all your enterprise, financial, and behavioral data to inform better product decisions. Learn more:

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Huge news! Proxet is proud to announce its strategic partnership with Palantir Technologies to deliver an unmatched suite of data solutions. We work with clients of all sizes across many industries: SMB through Enterprise. The power of Palantir’s software is being able to give all of them the same power and control over their data as their largest competitors. Read the full press release https://lnkd.in/ehZHM_wp and explore how Proxet can help you unlock the power of your data at https://lnkd.in/enAe7cpv #StrategicPartnership #Palantir #PalantirFoundry #Foundry #AIP #DataManagement #DataAutomation

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Just going to leave this here. If you're in search and not exploring semantic/multimodal search, you're going to get lapped by your competitor. Want to be blown away, shoot me a DM and we'll put together a custom demo/index with your data and show you instant improvements to relevance - because it's just that easy to build custom demos with Marqo. #vectorsearch #embeddings #AI

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Open has become the state-of-the-art (for now), Meta have changed the game - yet again - with the release of the Llama3.1 suite of models. The acceleration in this industry is breathtaking. The headlines: * Llama 3.1 models are immediately available in Cortex today. ✅ * 405B packs a punch - out performing other leading flagship models across a variety of benchmarks. 📈 * 8b & 70b models have been updated too. The already capable models have seen significant jumps, particularly in math and coding, in just 3 months. 🚀 * Meta's 3.1 suite will be made available for serverless fine tuning. 🤯 * We've also released Snowflake Cortex Guard (GA) to safeguard LLM applications. 🛡

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Interesting notes from Intuit's recent webinar on LLMs. What evaluation processes do you deploy? at tasq.ai our approach is to integrate the AI models with diverse, global human guidance, to support #responsibleai faster and near real time.

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I’m headed to Airflow Summit this week! Want to learn more about the state of the art of Airflow data pipeline development and how data engineers everywhere are building better data products with Airflow. If you’re going, want to catch up in SF, or just discuss the joys of healthy and stable data products, let’s meet up. Ps > the image is from a Dalle prompt to “draw me some healthy pipelines”. Everything looks right on the surface but the reality is broken pipelines, leaks, knobs that don’t seem to do anything, and pipes that run on forever. Data engineers: your jobs are safe lol

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Data storage, management, analytics, and reporting are aligning like never before. At ClicData, we see our platform not as a competitor, but as a collaborator with other vendors like PowerBI, Tableau, DOMO, and Snowflake. Our goal is to simplify processes by integrating and complementing these solutions, empowering data professionals with a comprehensive toolkit. Discover how Snowflake and ClicData work hand in hand to accelerate success for our customers: https://lnkd.in/eiVbxzb #DataAnalytics #DataManagement #SnowflakeIntegration

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Our recent discussion with Tobias Macey on The Data Engineering Podcast Data Quality, Observability and DataOps -- when will they be mainstream? https://hubs.ly/Q02KtXLn0 #dataobservabiliity #dataquiality #dataops

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We've unveiled Deep Lake 4.0 at #RetrieveX on Oct 17 to 200+ AI Data Leaders. It is already in production with Bayer, Flagship Pioneering, Matterport, and Spotter, and it's 10x more cost efficient than leading in-memory databases. Why did we release it? AI data retrieval faces five core challenges: limited modalities, accuracy issues, high costs to build it right, limited memory, and manual workflows. Deep Lake 4.0 addresses all these with the following new features: Index-on-the-Lake: Enables sub-second queries directly from any object storage and cross-cloud. 10x Cost-Efficiency: Index-on-the-lake eliminates the need for costly in-memory storage and large clusters. Deep Lake provides rapid, scalable search without the overhead. High Accuracy: Utilize multiple indexes (embedding with quantization, lexical, inverted, etc.) for rapid search on object storage with minimal caching, ready for neural search technologies like ColPali. True Multi-Modality: Supports diverse data types with enriched metadata. Enhanced Performance: Up to 10x faster reads/writes due to migrating low-level code to C++. Learn more about Deep Lake 4.0 in our release post. https://lnkd.in/guzXHiyp

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Matillion Democratizes GenAI with No-Code Cortex Components on Snowflake AI Data Cloud. The newly launched GenAI components enable powerful out-of-the-box use cases, including generating product descriptions, extracting key information from customer reviews, analyzing sentiment, summarizing lengthy reports, and translating content for global audiences. 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

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Hey, guess what? I'm presenting at the upcoming Snowflake Summit in SFO on Privacy-Preserving Data Collaboration! Even better, I'll be sharing the stage with my friend Brian Callahan of Facteus and we'll be talking about what to do when you can't just 'share the data'. (Hint: you should use PETs like #syntheticdata and #datacleanrooms). Registration link is below if you'd like to swing on by. https://lnkd.in/eX4G-pEv

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