Paige Bailey

Looking to activate your data and analytics for closed-loop operations? Discover how Palantir Foundry, the ontology-powered operating system for the modern enterprise, seamlessly connects data, models, and decisions: https://hubs.ly/Q02VM5fF0 PVM's Palantir Foundry services include: - Set up - Data connection and pipeline building - Ontology and app development - Use case enablement - Use case support - AI/ML and OPT #Palantir #Foundry #DigitalServices Palantir Technologies

2

The world of open-catalogs like Nessie, Gravitino and now Polaris just keep demonstrating the open nature of the Apache Iceberg ecosystem. All these catalogs can be self-managed and connect to any engine that supports the REST catalog specification. Open table formats and Open Catalogs = No Vendor Lock-in

10

Say goodbye to complex data systems and hello to simplicity with Snowflake's Polaris Catalog! 🌐 The first of many exciting announcements from the Snowflake Data Cloud Summit 24. Polaris is a new open-source Iceberg catalog that offers unparalleled flexibility. Seamlessly integrated with Snowflake or your preferred environment, it delivers enhanced choice, control, and enterprise-level security. Stay tuned for more such exciting updates from the Snowflake Data Cloud Summit 24 keynotes happening shortly! 🚀 #datamanagement #dataquality #data #DataCloudSummit24

5

We’re constantly pushing the envelope to bring accurate, real-time grid forecasting to the energy industry. In this blog post, we explore how we leverage Snowflake to enhance our short-term grid forecasts. Learn how this partnership enables us to deliver more precise insights, optimize energy use, and support a resilient and sustainable future for the grid.💡 https://hubs.li/Q02L1cqj0

28

Matillion + Databricks = AI We're excited to announce our AI components are now available for Databricks users. 👉 Native integrations with Databricks and push-down capabilities for AI 🔎 Unity Catalog integration to gain visibility into data and AI workflows 📊 Low-risk investment with consumption-based pricing and zero infrastructure to manage 📚 A wealth of resources from Matillion's partners and internal experts to help you understand what's possible and unlock new use cases Read more https://lnkd.in/ewxeBBHD #DataEngineering #DataEngineer #AI #Databricks #DataAISummit

42

1 Comment

Explore the path to interoperability with Michael Armbrust, the original creator of #DeltaLake, and Ryan Blue, co-creator of #ApacheIceberg. Many organizations face challenges in choosing the correct table format, which can hinder lakehouse adoption and impact their data + AI strategy. There’s a better way forward! Join us to delve into the evolution of open table formats and discover how Databricks is tackling interoperability, data governance, and more. https://dbricks.co/47IvBha

185

6 Comments

Struggling to ingest unstructured data into Databricks? Datavolo provides the fastest and easiest path to secure, continuous ingest and processing of all your unstructured data into Databricks. https://lnkd.in/g6xS_PQZ

16

Are you struggling with sky-high lead costs and low conversions? You're not alone. Cribl, a leading observability pipeline company, faced it head-on and won. They needed to capture demand affordably but couldn’t break free from high lead costs and poor conversions. Our two-fold approach: 1. Together, we launched a multi-channel game plan. By warming up audiences with LinkedIn awareness ads before diving into lead generation, we changed the narrative. 2. In addition, we developed an “engaged session” metric, combining page engagement, scroll rate, and firmographic data. Integrating insights from 6sense and Google Analytics let us create compelling ads that hit the mark with Cribl's ideal customers. What did we achieve? - 31% reduction in remarketing lead costs - 35% boost in lead gen form completions - 14% hike in brand-aware conversions - 23% YoY surge in branded Google searches If Cribl could reshape their lead generation landscape, so can you! If you are struggling to do it alone, let's talk. #vertodigital #cribl #clientsucess

17

3 Comments

I presented about Apache XTable (Incubating) & how it brings interoperability to #lakehouse table formats at Dremio's Subsurface. Check out the recording of the talk in comments! #dataengineering #softwareengineering

48

3 Comments

We've distilled our popular article on optimizing recommender systems with sparse metadata into a quick, info-packed video. Learn how to: - Leverage dummy nodes for better recommendations - Increase precision by up to 20% - Implement the technique with minimal code Watch now for a rapid-fire explanation of this powerful technique. Your recommender system will thank you! 🔗 Check out the video here: https://buff.ly/3WKOsDl 📚 For a deeper dive, read the comprehensive article: https://buff.ly/4fHI2gS #DataScience #MachineLearning #RecommenderSystems

7

1 Comment

Llama3 on Databricks. Databricks is changing the game with making open models easily usable.

1

Curious about the technical journey from Redshift to Databricks? Part 2 of our migration series just dropped! Dive deep into discovery, data evaluation, and secure implementation. This detailed guide lays out each step to make the transition as seamless as possible. Read on to see if Databricks is the future. ✒ Nicanor Medina | Kailash ( Kai) Thapa | Josue A. Bogran | Jeronimo Acosta #DataMigration #Databricks #Redshift #SunnyData https://lnkd.in/d6zksx8j

29

2 Comments

Getting value from customer data shouldn’t be a huge burden for data teams. If you’re spending too much time writing custom code to unify data, build and maintain connections, and keep the tech stack working together, then something isn’t working right. That’s why Amperity upgraded its CDP to work directly with any Data Lakehouse, taking advantage of the open format so users can easily share customer data among tools and platforms without having to copy data or spend time on integrations. The next evolution of customer data is here. Learn more 👉 https://lnkd.in/gX8B8CRD #DataLakehouse #CustomerData #CDP

23

Now on Databricks Runtime 14.3: the State Reader API, a new capability that allows users to access and analyze Structured Streaming's internal state data. Discover how this new capability is providing much-needed transparency, accessibility, and ease of use: https://dbricks.co/3UeoF6l

214

Palantir Foundry is the ontology-powered operating system for the modern enterprise. Learn how PVM's Palantir Foundry services can active your data and analytics for closed-loop operations: https://hubs.ly/Q02GRp9n0 #Palantir #Foundry #BusinessIntelligence #BigData

3

Kumo helps data scientists build highly accurate predictive AI models that predict user and customer behavior by combining graph learning over enterprise data and generative AI models trained on public data—all entirely within Snowflake. If you want to create better machine learning models faster with Kumo, try our Snowflake Native App now. 🔗 You can request a free trial at the following link: https://hubs.ly/Q02HgQ1P0. If you need additional support and more details, contact us. We'd love to get in touch with you and help you query the future: https://hubs.ly/Q02HgGvG0. #AI #MachineLearning #PredictiveModels #DataScience #GraphLearning #GenerativeAI #Snowflake #TechInnovation #KumoAI #FutureOfData

8

Analyzing streams shouldn’t break the bank. 💰 But as volume balloons, so does the cost of observability tools like Datadog, ELK, CloudWatch or Loki; SIEMs like Splunk or Sumo Logic; and data warehouses like Snowflake or BigQuery. That’s because the architectures of these solutions were not built to efficiently ingest and analyze streams at scale. But ChaosSearch is, which allows our customers to realize 50-80% savings with unlimited retention. 💸 ChaosSearch delivered 90% cost savings to Equifax vs. their legacy tools. Try our pricing calculator for your guaranteed savings: https://bit.ly/427wXOq

1

Analyzing streams shouldn’t break the bank. 🏦 But as volume balloons, so does the cost of observability tools like Datadog, ELK, CloudWatch or Loki; SIEMs like Splunk or Sumo Logic; and data warehouses like Snowflake or BigQuery. That’s because the architectures of these solutions were not built to efficiently ingest and analyze streams at scale. But ChaosSearch is, which allows our customers to realize 50-80% savings with unlimited retention. 💸 Achieve an industry-leading price with guaranteed savings at scale: https://lnkd.in/dC26BrTX

5