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Rivery Launches Snowflake as a Source and Amazon Q Data Integration Solution

Rivery Launches Snowflake as a Source and Amazon Q Data Integration Solution

Rivery推出snowflake作爲來源和亞馬遜Q數據集成解決方案
PR Newswire ·  00:00

Enterprises can fully harness their internal data to power GenAI applications,
and generate precise and up-to-date business insights

企業可以充分利用其內部數據來支持GenAI應用程序。
並生成精確和最新的業務洞察。

NEW YORK, Dec. 3, 2024 /PRNewswire/ -- Rivery, the complete data integration platform accelerating data pipeline creation, announced today the launch of two new integrations of its comprehensive ELT platform with Amazon Q and Snowflake. The integrations will help enterprises use their internal data to effectively develop specially designed AI tools, and enable fresh and complete business insights.

紐約,2024年12月3日 /PRNewswire/ -- Rivery.完整的數據集成平台Rivery加速數據流水線創建,今天宣佈了將其全面ELt平台與亞馬遜Q和snowflake的兩個新集成的推出。這些集成將幫助企業利用其內部數據,有效開發專門設計的人工智能工具,並實現新鮮和完整的業務洞察。

"With the launch of these integrations, Rivery continues to enable seamless data management across platforms, empowering organizations to deploy powerful AI applications with fewer hallucinations and derive actionable insights," said Rivery CEO Itamar Ben Hemo. "With Snowflake as a Source and Amazon Q integration, we're enabling our users to unlock the full potential of their data — from streamlining migrations to building data-driven, GenAI solutions that meet today's business needs with flexibility and security."

「發佈這些集成後,Rivery繼續實現跨平台無縫數據管理,讓組織能夠部署功能強大的人工智能應用程序,減少幻覺,獲得可操作的見解,」Rivery首席執行官Itamar Ben Hemo表示。「通過將Snowflake作爲源並與Amazon Q集成,我們幫助用戶釋放其數據的全部潛力——從簡化遷移到構建基於數據驅動的GenAI解決方案,以滿足當今靈活和安全的業務需求。」

Amazon Q Integration
Rivery's integration with Amazon Q allows users to create personalized GenAI chat assistants based on the full range of data available within the enterprise. Large language models trained on the internet don't tap into proprietary data, lack security, and are highly susceptible to hallucinations. By quickly and easily leveraging Retrieval Augmented Generation (RAG) workflows in Amazon Q, companies can set up enterprise-specific GenAI chatbots that can securely answer questions, provide summaries, and generate content with fewer hallucinations.

亞馬遜Q集成
Rivery與亞馬遜Q的集成允許用戶基於企業內可用的全部數據創建個性化的GenAI聊天助手。在互聯網上接受訓練的大型語言模型不會利用專有數據,缺乏安全性,極易產生幻覺。通過快速且輕鬆地利用亞馬遜Q中的檢索增強生成(RAG)工作流程,公司可以建立企業特定的GenAI聊天機器人,能夠安全地回答問題,提供摘要,並減少虛幻的內容。

Capabilities

能力

  • Sync all enterprise data sources to create effective AI apps based on a full range of internal data
  • Easily prep enterprise data for LLM usage with an optimized structure to handle RAG workflows
  • Trigger Amazon Q syncs that ensure users' AI apps run on the freshest data
  • Build data flows securely with users' own S3 file zones without exposing data to third parties
  • 同步所有企業數據源,基於全面的內部數據創建有效的人工智能應用程序
  • 通過優化結構輕鬆爲LLm使用準備企業數據,以處理RAG工作流程
  • 觸發亞馬遜Q同步,確保用戶的人工智能應用程序在最新數據上運行
  • 通過用戶自己的S3文件區域安全構建數據流,而不會將數據暴露給第三方

Rivery Snowflake as a Source
Rivery Snowflake as a Source empowers data engineers and analysts to seamlessly replicate or migrate data from Snowflake to simplify cross-platform data management. Organizations can migrate and sync data as needed, regardless of the data's source or destination. This is particularly significant given that data from warehouses is increasingly fed back into operational systems to enable more informed decision-making with tighter integration between data insights and business operations.

作爲數據源的Rivery Snowflake
Rivery Snowflake作爲數據源,賦予數據工程師和分析師從Snowflake無縫複製或遷移數據的能力,以簡化跨平台數據管理。無論數據來源或目的地如何,組織都可以按需遷移和同步數據。這尤爲重要,因爲從數據倉庫獲得的數據越來越多地被反饋到運營系統中,以實現更明智的決策,並在數據洞察和業務運營之間實現更緊密的整合。

Capabilities

能力

  • Syncing data between multiple data warehouses
    • Easily sync datasets across platforms such as BigQuery, Databricks Lakehouse, Amazon Redshift, or between Snowflake accounts
  • Migrating data from Snowflake to another data lake or data warehouse
    • Accelerate complex migrations by implementing an easily deployed lift and shift approach
  • Activate Snowflake data in transactional databases or AI applications
    • Simplify data activation or reverse ETL and sync data into AI applications such as Amazon Bedrock. Snowflake data can be replicated into an Amazon S3 dedicated dataset to serve downstream AI applications
  • 在多個數據倉庫之間同步數據
    • 輕鬆同步數據集,例如在BigQuery、Databricks Lakehouse、亞馬遜Redshift之間,或在snowflake帳戶之間
  • 從snowflake遷移數據至另一個數據湖或數據倉庫
    • 通過實施易於部署的搬遷和遷移方法來加速複雜的遷移
  • 激活snowflake數據到事務性數據庫或人工智能應用程序
    • 簡化數據激活或反向ETL,並將數據同步到人工智能應用程序,例如亞馬遜Bedrock。snowflake數據可以複製到亞馬遜S3專用數據集,用於爲下游人工智能應用程序提供服務

"Our team needed to migrate Google Search Ads 360 data to Snowflake and consolidate with older data from the same source, already stored in Snowflake," said Destinei Simpson, a data analyst at digital marketing agency Good Apple. "With Rivery Snowflake as a Source, it took us just a few clicks to set up a pipeline to replicate the data from one Snowflake dataset into another that would have otherwise required manual scripting and management. This made our job much easier and helped speed up our delivery time dramatically."

"我們的團隊需要將Google Search Ads 360的數據遷移到snowflake,並與已存儲在snowflake中來自同一來源的舊數據進行 consoli"、"dation,"Good Apple數字營銷機構的數據分析師Destinei Simpson說。"使用Rivery Snowflake作爲源,我們只需要點擊幾下就能設置一個管道,將數據從一個snowflake數據集複製到另一個數據集,否則需要手動腳本和管理。這使我們的工作變得更加輕鬆,並顯著加快了交付時間。"

About Rivery
Rivery simplifies data integration for businesses of any size to build strong, secure, and unified data infrastructures, bringing together over 200 fully managed data services into a single platform. Eliminating the complexities of integrating unstructured and structured data sources, Rivery enables organizations to focus on innovating products, services, customer experiences, and growth strategies. Founded in 2019, the company has over 400 customers including top brands Bayer, AI21 Labs, American Cancer Society, and EMAAR Properties. Learn more about Rivery at rivery.io.

關於Rivery
Rivery簡化數據集成,適用於任何規模的企業,構建強大、安全、統一的數據基礎設施,將超過200種全面託管的數據服務集成到一個平台。通過消除集成非結構化和結構化數據源的複雜性,Rivery使組織能夠專注於創新產品、服務、客戶體驗和增長戰略。該公司成立於2019年,擁有超過400家客戶,包括拜耳、AI21實驗室、美國癌症協會和EMAAR Properties等知名品牌。詳細了解Rivery,請訪問 rivery.io.

SOURCE Rivery

來源:Rivery

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