Cloudera 年度销售启动大会 ELEVATE27 今日开幕，聚焦在混合数据环境中构建、运营、扩展并全面治理 AI 能力加利福尼亚州圣塔克拉拉, Feb. 11, 2026 (GLOBE NEWSWIRE) -- 作为业界唯一实现“数据全域 AI”化的公司，Cloudera 今日在年度销售启动大会 ELEVATE27 上公布强劲业绩，正式拉开 2027 财年的序幕。 在过去一年里，Cloudera 实现了强劲增长，赢得众多新客户，拓展合作伙伴网络，并持续推动创新，进一步巩固其作为业内唯一混合数据与 AI 平台的领先地位。 实现创纪录的财务业绩Cloudera 以强劲的第四季度表现收官 2026 财年，这一成绩得益于新业务与扩展业务同比增长逾 50%、年度经常性收入稳健增长，以及第四季度全球各区域新客户增长率突破 100%。 公司业绩凸显了企业对灵活、安全的数据与 AI 平台日益增长的需求——这些平台能够在云端、数据中心及边缘环境中实现无缝运行。 推动业界最具灵活性的数据与 AI 平台Cloudera 凭借其独特优势持续保持发展势头——作为唯一支持全场景部署并提供统一体验的数据与 AI 平台供应商。 通过助 ...

进入2026年，AI正迈入一个新的发展阶段，从试点应用走向业务规模化。近日，数据和AI平台公司 Cloudera对2026年AI的发展趋势作出预测，过去两年，AI领域的大模型、智能体（Agentic）及自动化应 用等技术，在众多企业中完成了初步探索与密集试点，从概念热潮逐步走向实践落地。如今，企业对 AI的关注核心已从"能否用AI"转向"如何让AI在可控、可持续的前提下，稳定运行并转化为可衡量的业 务成果"。在此背景下，本地化私有部署凭借对数据安全、合规可控的刚性保障，以及对系统稳定性、 长期运营能力的全面支撑，正成为金融、制造、能源、电信等关键行业企业的核心选择。 Cloudera大中华区技术总监刘隶放对《中国经营报》记者表示，无论是传统行业巨头还是新兴产业领军 者，都纷纷将本地化私有部署作为AI规模化落地的基础架构，这一趋势不仅彰显了AI产业化的深度演 进，更标志着中国AI发展从"概念炒作"迈向"硬核成果"的关键转折，为企业在AI时代构建核心竞争力奠 定了坚实基础。 本地化私有部署成主流 Cloudera大中华区技术总监刘隶放指出，如今企业在引入AI项目时，不再只谈论技术性能，而是需要向 CFO清晰呈现项 ...

Core Insights - Cloudera has announced a significant platform update integrating Trino, Cloudera SDX, and Cloudera Octopai to enhance data access, control, governance, and traceability across data assets [1][2] - The update aims to address the challenge of data accessibility for AI projects, with only 9% of IT leaders reporting all data is available and 38% indicating most data is usable for AI [1][2] - Cloudera's platform leverages AI-driven automation to unify data silos and streamline governance processes without the need to move data, thereby improving efficiency and trustworthiness [1][2] Company Overview - Cloudera is positioned as a trusted data and AI platform for large enterprises, enabling them to integrate AI with data stored anywhere [3] - The company differentiates itself by providing a consistent cloud experience through a validated open-source infrastructure, unifying public cloud, on-premises data centers, and edge environments [3] - Cloudera empowers enterprises to harness AI and gain comprehensive control over all forms of data, enhancing security, governance, and real-time predictive insights [3] Product Features - The Cloudera platform automates key data architecture operations such as data quality checks, classification, and profiling, facilitating efficient data management [2][4] - It offers natural language access to enterprise data, allowing both technical and non-technical teams to utilize data equally [2][4] - Cloudera Octopai's data source tracking feature provides end-to-end visibility and credibility for data transformations, including those from outside the Cloudera ecosystem [2][4]

Core Insights - Cloudera announced a major platform update integrating Trino, Cloudera Shared Data Experience (SDX), and Cloudera Octopai Data Lineage to enhance data access, control, governance, and lineage across enterprises [1][2][4] Data Accessibility Challenges - A recent survey revealed that only 9% of IT leaders report all organizational data is accessible, with 38% stating most data is usable for AI [2] - Many organizations face data trapped in disparate systems with fragmented governance and security policies [2] Platform Features and Benefits - The update allows organizations to unite data silos, enable self-service access, and automate governance workflows without moving data [2] - Trino's federation capabilities enable secure querying of distributed data using natural language interfaces [2] - Cloudera's centralized governance ensures consistent access control and compliance across all environments [2][3] AI-Driven Automation - Cloudera's platform automates critical data fabric operations, including data quality checks, classification, and profiling [3] - Natural language access democratizes data usage across technical and non-technical teams [3] Unified Data Management - The integration with SDX unifies metadata and access controls, simplifying management and enabling secure, self-service data access [3] - Cloudera Octopai Data Lineage tracks the end-to-end journey of data, enhancing transparency and trust in data transformations [3] Strategic Vision - Cloudera aims to empower enterprises to make trusted data available for AI initiatives, enhancing innovation and business outcomes [4] - The announcement was made during Cloudera's EVOLVE25 event in Dubai, highlighting the company's commitment to AI and data integration [4] Company Overview - Cloudera is recognized as the only data and AI platform company that large organizations trust to bring AI to their data, leveraging a consistent cloud experience across public clouds, on-prem data centers, and the edge [5] - The company focuses on improving security, governance, and real-time insights, serving some of the world's largest brands across various industries [5]

Core Insights - Cloudera has announced updates to its platform, focusing on the Cloudera Iceberg REST Catalog and Cloudera Lakehouse Optimizer, enhancing its commitment to providing the best open data lakehouse based on Iceberg technology [1][2] Cloudera Iceberg REST Catalog - Cloudera is the first and only vendor to integrate Iceberg REST Catalog into a full lifecycle data and AI platform, enabling secure, zero-copy data sharing and unified governance across any cloud environment or data center [2][3] - The new service allows third-party engines to access Cloudera-managed data without the need for data copying or movement, ensuring consistent policy enforcement and metadata intelligence [2][3] - Customers using Iceberg can connect seamlessly with leading analytics and AI engines such as Snowflake, Databricks, AWS Athena, AWS EMR, and Salesforce, while achieving ACID compliance and unified access policies [3] Cloudera Lakehouse Optimizer - The Cloudera Lakehouse Optimizer is a new intelligent service that automates optimization and list maintenance for Apache Iceberg within Cloudera's lakehouse [4] - This service eliminates the need for manual data management tasks, allowing customers to focus on deriving insights from data, and is applicable to any public cloud with Iceberg-compatible engines [4] - Internal benchmarks indicate that the service can enhance query performance by up to 13 times and reduce storage costs by 36% [4] Company Commitment - Cloudera's Chief Product Officer emphasized the company's role as a pioneer in the big data industry, continuously investing in Apache Iceberg to enhance its enterprise application capabilities [5] - The updates reflect Cloudera's commitment to providing flexible, scalable insights at critical times and locations, earning the trust of top global enterprises [5] Availability - The Cloudera Data Sharing powered by Iceberg REST Catalog and Cloudera Lakehouse Optimizer are now fully launched [6]

Core Insights - The report by Cloudera highlights the significant integration of AI into core business processes, with 96% of IT leaders indicating that AI is at least partially embedded in their operations, up from 88% in 2024 [2] - The findings suggest a shift from experimental AI applications to comprehensive integration within workflows, with 70% of respondents reporting major success in their AI projects [2] - A hybrid data architecture is becoming the norm, allowing organizations to manage AI flexibly across cloud and on-premises environments, with security being the top advantage cited by 62% of respondents [2] AI Integration and Success - 70% of IT leaders report significant success in their AI initiatives, with only 1% not seeing any results [2] - Various forms of AI are being utilized, including generative AI (60%), deep learning (53%), and predictive analytics (50%) [2] - Confidence in managing new forms of AI has increased, with 67% of IT leaders feeling better prepared compared to the previous year [2] Challenges and Limitations - Despite progress, organizations acknowledge the need for improvement in maximizing AI potential and ROI, with only 24% reporting a highly data-driven culture, up from 17% last year [3] - Key technical limitations in current data architecture include data integration (37%), storage performance (17%), and computing power (17%) [3] - Data accessibility remains a significant barrier, with only 9% of organizations stating that all their data is accessible for AI projects [3] Security and Compliance Concerns - Cloudera's CTO emphasizes the urgent need for businesses to address security, compliance, and data utilization challenges as AI becomes a critical operational component [4] - Concerns regarding AI security include data leakage during model training (50%), unauthorized data access (48%), and insecure third-party AI tools (43%) [5] - Despite these concerns, confidence in protecting AI system data is relatively high, with 24% of respondents expressing extreme confidence in their organization's capabilities [5] Company Overview - Cloudera is recognized as a leader in integrating AI into various data environments, leveraging mature open-source technology to provide a unified cloud experience [6] - The company empowers enterprises to manage diverse data types and utilize AI for enhanced security, governance, and real-time predictive insights [6] - Cloudera's solutions are relied upon by large enterprises across various industries to reshape decision-making processes and improve profitability [6]

Core Insights - Cloudera has been recognized as a leader in the 2025 IDC MarketScape Asia-Pacific Unified AI Platform Vendor Assessment, highlighting its excellence in governance, security, and innovation [1][2] - The company aims to integrate AI into various data environments, addressing the dual challenges of accelerating innovation while ensuring trust and compliance [1][2] Company Overview - Cloudera is the only company trusted by large enterprises to integrate AI into any data environment, leveraging mature open-source technology to create a unified cloud experience [3] - The company empowers enterprises to manage diverse data and utilize AI technologies to enhance security, governance, and real-time predictive insights [3] Strategic Developments - Cloudera has increased its R&D investment, with nearly half of its global workforce focused on engineering and development [2] - Recent innovations include the Cloudera AI Workbench for building and deploying AI agents, Cloudera AI Inference for large-scale generative AI, and enhanced governance capabilities for compliance and transparency [2] - Strategic acquisitions such as Verta, Octopai, and Taikun have accelerated Cloudera's ability to apply AI across various data environments [2][5] Key Strengths - Cloudera's core strengths include a comprehensive governance framework with fine-grained policies, audit trails, and compliance alignment [5] - The company offers end-to-end capabilities in operational AI and agent workflows, covering data engineering, MLOps/LLMOps, and built-in observability [5] - Cloudera has established strategic partnerships with companies like NVIDIA, AWS, and Dell to further enhance its platform capabilities [5]