#DatabricksMarketplace offers a variety of products to support our customers’ AI and analytics initiatives. We’re thrilled to offer 2500+ listings across 250 providers – with many more to come! We want to ensure that our users are equipped to evaluate the right provider for their use cases and that our providers can maximize the reach of their offerings. Here are Marketplace tips + best practices and answers to frequently asked questions. https://dbricks.co/4hIGtAc
关于我们
Databricks is the Data and AI company. More than 10,000 organizations worldwide — including Block, Comcast, Condé Nast, Rivian, Shell and over 60% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to take control of their data and put it to work with AI. Databricks is headquartered in San Francisco, with offices around the globe, and was founded by the original creators of Lakehouse, Apache Spark?, Delta Lake and MLflow. --- Databricks applicants Please apply through our official Careers page at databricks.com/company/careers. All official communication from Databricks will come from email addresses ending with @databricks.com or @goodtime.io (our meeting tool).
- 网站
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https://databricks.com
Databricks的外部链接
- 所属行业
- 软件开发
- 规模
- 5,001-10,000 人
- 总部
- San Francisco，CA
- 类型
- 私人持股
- 领域
- Apache Spark、Apache Spark Training、Cloud Computing、Big Data、Data Science、Delta Lake、Data Lakehouse、MLflow、Machine Learning、Data Engineering、Data Warehousing、Data Streaming、Open Source、Generative AI、Artificial Intelligence、Data Intelligence、Data Management、Data Goverance、Generative AI和AI/ML Ops
产品
![点击此处查看The Databricks Data Intelligence Platform]()
The Databricks Data Intelligence Platform
数据科学与机器学习平台
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data.
地点
Databricks员工
动态
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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
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Migrating data warehouse workloads is a challenging but essential task for any organization. At Databricks, our Professional Services team works directly with customers across industries on migration projects - and they’ve gathered insights along the way. Here are 5 best practices any data professional should consider, drawn from our customers’ own migration stories. https://dbricks.co/3YE1TFT
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“The key challenges we hear about from customers are governance, compliance, security, fine tuning, and doing those things on your data. #DataIntelligence is a game changer.” At Battery Ventures’ #OpenCloudSummit, Databricks CRO Ron Gabrisko discussed the current state of enterprise #GenAI — including the biggest use cases, solving adoption bottlenecks, and more. A big thank you to Battery Ventures and Nasdaq for helping us kick off the event with a guest appearance in Times Square!
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We examined usage data from 10,000+ global Databricks customers to understand how enterprises are approaching GenAI and how trends—like the rapid adoption of vector databases—reflect their broader strategies. Databricks experts Kobie Crawford and Kunal Marwah break down these insights and other findings from the State of Data + AI report with Ravit Jain. Watch the full conversation: https://dbricks.co/3UGizeZ
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Join us at #AWSreInvent to explore the latest advancements in data intelligence with live demos and real-world GenAI success stories! We'll also be showcasing innovative solutions in our technical sessions, including a joint talk with Mastercard on building and deploying GenAI apps.? https://dbricks.co/40yE1nS
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Are you solving real-world problems with data and AI? #DataAISummit Call For Presentations is now open! Share your practical insights + solutions and show how your work is pushing the limits of AI, analytics and data engineering. This is a great opportunity to gain valuable speaking experience and inspire your peers. Submit your idea: https://dbricks.co/3YE1HGJ
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Now GA: materialized views and streaming tables on Databricks SQL. Create efficient and scalable data pipelines – from ingestion to transformation – using just Databricks SQL. Available on AWS and Azure. Learn how these tools empower analysts and analytics engineers to deliver data and applications more effectively within the DBSQL warehouse. https://dbricks.co/3UFClXX
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Tired of struggling with unstructured text data across millions of documents? Databricks makes it easy to scale and automate #LLM inference. With batch inference on #MosaicAI Model Serving: - Run large-scale inference on governed data without manual exports or complex -infrastructure. - Process millions of rows using familiar SQL queries. - Easily integrate preprocessing, inference, and post-processing into a unified workflow. Learn more: https://dbricks.co/48pltdx
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#DatabricksAssistant is your context-aware AI assistant that lets you query data through a conversational interface. For Data Engineers, Databricks Assistant helps eliminate tedium, increase productivity and immersion, and accelerate time to value. How can you get the most out of AI-assisted data engineering? Read these tips & tricks: https://lnkd.in/gaTg-nAV