Taylor Melville

Snowflake's pay-as-you-go model makes query optimization essential for eliminating inefficiencies. Understanding Cost Per Query (CPQ) can help you reduce waste and boost performance across your cloud data environment. Check out this blog to discover how you can start optimizing your Snowflake queries today! #Snowflake #CloudOptimization #DataEfficiency #CapitalOneSoftware #Slingshot

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Go Noles! 🔴🟡 Florida State University consolidated 47 disparate data sources into Snowflake and is now seeing 95% faster time to value for FSU's data consumers. Document AI is helping the university extract data from PDFs to help students get responses faster and help the university quickly surface insights. Check out case study here:

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Capital One is showing up strong at this year’s Snowflake #DataCloud Summit! 7 sessions, 11 speakers and topics from optimizing Snowflake queries and FinOps for data infrastructure, to harnessing data to prepare for #AI—don’t miss out!

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LakeFlow Connect is now in Public Preview for SQL Server, Salesforce, and Workday! These connectors provide a simple and efficient way to ingest data into the Databricks Data Intelligence Platform, allowing users to spend less time building complex ingestion pipelines and more time innovating. Learn more👇

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With over 8K analysts writing queries daily, valuable insights have been gained. Inefficient queries can have a significant cost impact on organizations. Explore our tips and tricks to enhance query efficiency. #DataAnalysis #EfficiencyTips

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Databricks Lakehouse Monitoring is now GA! A unified approach to data and AI monitoring allows you to easily profile, diagnose, and enforce quality directly in the Databricks Data Intelligence Platform. Built on Unity Catalog, Lakehouse Monitoring requires no extra tools.

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Databricks Lakehouse Monitoring is now GA! A unified approach to data and AI monitoring allows you to easily profile, diagnose, and enforce quality directly in the Databricks Data Intelligence Platform. Built on Unity Catalog, Lakehouse Monitoring requires no extra tools.

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Recent #Snowflake security incidents got you worried?     ALTR's cloud-native integration seamlessly bolsters Snowflake security, ensuring airtight protection of all your sensitive data.     Learn more at Snowflake World Tour Atlanta 👉  https://lnkd.in/ebZTJTWF     #SnowflakeWorldTour #DataSecurity #ALTR 

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Hospitals are increasing the size of their #cybersecurity teams by 30% this year in response to increased threats and recent high-profile attacks in #healthcare. #Snowflake as a security data lake gives those experts easy and affordable access to track threats and correlate information from across logs and business data rather than being limited to "the last 90-days" or a "subset of critical log entries." Make sure you're looking at the people, the tools, and the data you're giving them to protect your patients - https://lnkd.in/gk433FNi https://lnkd.in/ea4uqbzr

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Check out how Snowflake can surface insights into your customers support cases with Cortex and AI. Do you want to learn to build 1) An End-to-End Ticket summarizing data app that fetches the tickets and stages, tokenizes, splits, and processes it with Snowflake Cortex for summarization. 2) A workflow that uses LangChain and Snowflake's Cortex for scalable text analysis, ready for further customization and scaling in business use cases. https://lnkd.in/gzwRGDJM

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Snowflake launched two new features today to help customers use their platform safely. 1) allowing Admins to Enforce Mandatory MFA and 2) the GA launch of Snowflake Trust Center to give a place for admins to monitor the adherence to MFA policies. Mandatory MFA is critical for any SaaS app to be used safely. Password harvesting/reuse/stuffing provides a direct vector to the data that you store in a SaaS app. Glad to see it's coming to Snowflake Their trust center gives admins the flexibility to start their MFA enrollment process with a warning step, or jump right to enforcing MFA for all users. Thank you for releasing this feature for free with all versions. Safety isn't a place for an upsell. If you are a Snowflake admin enable a MFA policy to warn all your users without MFA enabled, and work with your internal stakeholders to set the day when it's mandatory This is great news to see https://lnkd.in/e2DpEV8W

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Container Runtime for Snowflake Notebooks is now in public preview! Snowflake is making it easier than ever before to build and deploy models while using distributed GPUs, all from a single platform. Check out the blog to learn more:

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Exciting news! IBM WatsonX.data has launched an integrated vector database in the data lakehouse, enabling customers to unify, curate, and prepare vectorized embeddings for GenAI applications at scale. This enhancement enhances the relevance and precision of AI workloads, including chatbots and personalized recommendation systems. WatsonX.data simplifies data access and unification, empowering organizations to maximize the value of their data investments across clouds and on-premises environments. By personalizing AI with vectorized embeddings grounded in trusted data, WatsonX.data ensures the accuracy and relevance of AI applications while reducing inferencing latency and overall system costs. https://lnkd.in/gE3JKY_y

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Data consistency is a huge challenge in enterprise architecture and an often forgotten benefit of event streaming. When people hear event streaming, they often hear "only" real-time. A lack of data consistency would be causing you worlds of pain ranging from different views of the truth, decisions made from old data, incomplete view of the customer - and most orgs don't have great data consistency. You need to shift your thinking on how you can have consistent data across your systems - with event streaming's loose coupling underpinning this. Kai Waehner captures this brilliantly https://lnkd.in/gWmJQzK8

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Wondering how "Data Intelligence" enhances data governance, data engineering, data streaming, data warehousing and all your data user experiences? See you in Austin at the Databricks Data Intelligence Day this Wednesday August 21st - register here:

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AI chatbots need fresh, context-rich data to generate more accurate outputs and results. Confluent Cloud for Apache Flink's "AI Model Inference feature" provides the ability to analyze the information you process with Confluent Cloud using large language models. Developers can extract the most important records from a data stream and summarizing text. It makes it possible for developers to use simple Structured Query Language statements to make calls to remote model endpoints, including OpenAI, AWS Sagemaker, Google Cloud’s Vertex AI and Microsoft Azure’s OpenAI Service, so as to orchestrate data cleaning and processing tasks in real time. Check out the Getting started Guide - https://lnkd.in/geXKDW_f

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Introducing Databricks LakeFlow, a new unified, intelligent solution for data engineering with everything you need to build and operate production data pipelines. LakeFlow simplifies data engineering—from data ingestion to transformation and orchestration—so data teams can scale to the ever-growing demand for reliable data and AI.

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Databricks Clean Rooms, powered by Delta Sharing, enables organizations across industries to collaborate with partners in a privacy-safe manner without relinquishing control over sensitive data. Key features: ✔️ Any language, any workload ✔️ Any cloud, no replication ✔️ Any scale, any trust level Learn how it works👇

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