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Integrating Anaconda's secure repository of Python and R packages with Teradata's powerful ClearScape Analytics is intended to speed delivery and use of data science, generative AI use cases SINGAPORE, April 11, 2024 /PRNewswire/ -- Anaconda Inc. and Teradata today announced a new integration to bring the most popular and widely used Python and R packages to Teradata VantageCloud through the Anaconda Repository. The integration with ClearScape Analytics, a powerful engine for deploying end-to-end artificial intelligence (AI) and machine learning (ML), is designed to provide enterprises with the ability to deploy large-scale data science, AI/ML, and generative AI use cases that can cost-effectively deliver value for the enterprise. Organizations working to leverage AI innovation need a platform that allows for the quick application of popular and secure open-source packages, but that also delivers scale, performance, and access to harmonized data and trusted AI. Anaconda and Teradata believe their partnership meets this critical need by speeding the deployment and operationalization of AI/ML developed using Anaconda's secure repository of open-source Python and R packages. "There is so much innovation happening in the open-source community, and we're thrilled to be working with Anaconda to bring their popular open-source packages to Teradata VantageCloud Lake," said Hillary Ashton, Chief Product Officer at Teradata. "We believe that the 45 million data scientists, data engineers, developers and analytics professionals that use Anaconda will have an even greater impact on their organizations by also using ClearScape Analytics to deploy and operationalize trusted AI/ML at enterprise scale and with the least cost." This integration empowers enterprise users to work with Anaconda, provider of the world's most popular platform for AI/ML and data science, and Teradata, the most complete cloud analytics and data platform for AI, to deliver breakthroughs today and in the future. Users can: Rapidly deploy and operationalize AI/ML developed using open-source Python and R packages. Unlock innovation and the full potential of data at scale with a wide variety of Python and R functionality on VantageCloud Lake. Flexibly use packages and versions of their choice for large-scale data science, AI/ML and generative AI use-cases. Securely work with Python/R models into VantageCloud Lake with no intellectual property (IP) leakage. "As AI becomes further engrained in every business, it has never been more critical to have a secure and trusted platform that mitigates risks from enterprise AI use," said Barry Libert, CEO at Anaconda. "Teradata's investment in data privacy and security aligns well with Anaconda's deep commitment to secure, trusted AI innovation, and allows us to provide a simple, rapid, and innovative open-source solution to increase AI business value." Teradata VantageCloud Lake customers will be able to download Python and R packages from the Anaconda Repository at no additional cost. Python packages are available immediately, and R packages will be released before the end of the year. For more information about Teradata ClearScape Analytics, please visit Teradata.com. Learn more about partnering with Anaconda here. About Anaconda With more than 45 million users, Anaconda is the most popular operating system for AI providing access to the foundational open-source Python packages used in modern AI, data science and machine learning through a seamless platform. We pioneered the use of Python for data science, championed its vibrant community, and continue to steward open-source projects that make tomorrow's innovations possible. Our enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness the power of open-source for competitive advantage, groundbreaking research, and a better world. To learn more visit https://www.anaconda.com. About Teradata At Teradata, we believe that people thrive when empowered with trusted information. We offer the most complete cloud analytics and data platform for AI. By delivering harmonized data and trusted AI/ML, we enable more confident decision-making, unlock faster innovation, and drive the impactful business results organizations need most. See how at Teradata.com.
多雲平台的企業級智慧資料平臺解決方案提供商 Teradata 天睿公司 (NYSE:TDC) 今(二十八)日，該公司在《Gartner 2022 年雲端資料庫管理系統關鍵能力 – 分析用例》報告（2022 年 12月 15 日發佈，分析師：Rick Greenwald、Merv Adrian、Adam Ronthal、Henry Cook、Philip Russom 和 Xingyu Gu ）的所有分析用例中均排名第一。Teradata 榮獲最高得分的四個用例——傳統資料倉儲 (4.71/5)、邏輯資料倉儲 (4.85/5)、資料湖 (4.25/5) 和串流分析 (4.25/5) ——代表了對當今企業而言最重要的一些用例。實例表明，全球前 20 大銀行中，有 17 家依靠 Teradata 的卓越分析能力來提高營運效率，減少欺詐並改善客戶體驗。 Teradata 認為，在《Gartner 2022 年雲端資料庫管理系統關鍵能力 – 分析用例》報告評估的 17 家供應商中，Teradata 憑藉 ClearScape Analytics 強大的資料庫內建功能、開放網際網路的整合以及強大的操作功能，在滿足客戶不斷成長的多元化、全方位分析需求方面展現出無與倫比的優勢。 Teradata 同時還被《Gartner 2022 年雲端資料庫管理系統 (DBMS) 魔力象限》報告（2022 年 12 月 13 日發佈，分析師：Henry Cook、Merv Adrian、Rick Greenwald 和 Xingyu Gu ）評為 「領導者」。Gartner根據願景完整性和執行力，對入選雲端資料庫管理系統魔力象限的供應商進行評估。 Teradata 天睿公司全球執行長 Steve McMillan 表示：「我們持續努力實現 Teradata 的使命——透過資料的力量改變企業的工作模式和人們的生活方式。我們相信，Teradata擁有強大的多雲平台的企業級智慧資料平臺，能夠支援大規模的資料倉儲、資料湖和湖屋設計(Lakehouse Design Patterns)模式，為客戶提供執行關鍵型任務工作負載所需的靈活性，全方位滿足客戶需求。獲得 Gartner 的肯定，進一步證實了我們與眾不同的、開放的、以客戶為中心的方法的有效性，無論客戶處於數位化轉型之旅的哪個階段，我們都能為其提供即時的洞察和優化的結果。」 他接著指出：「在此基礎之上，我們持續創新。今年早些時候，我們為 Teradata VantageCloud 平臺引進了新功能，使我們的技術不僅能覆蓋關鍵型企業業務需求，還進一步擴展到部門級、探索性和隨機性用例。我們還透過 ClearScape Analytics 大幅增加資料庫的分析功能，獲得了領先同業的強大競爭優勢。這些重大強化使Teradata 在雲端分析和資料市場上的領導地位愈加鞏固，更重要的是，也為我們的客戶創造了新的機會，使他們能夠不斷推動業務向前發展。」 瞭解有關 Teradata 在《Gartner 2022 年雲端資料庫管理系統關鍵能力 – 分析用例》中排名情況的更多資訊，請點擊此處。 瞭解有關 Teradata 在《Gartner 2022 年雲端資料庫管理系統魔力象限》中領導者地位的更多資訊，請點擊此處。 Gartner 對雲端資料庫管理系統市場的定義如下：「其核心能力包括：託管的公有雲或私有雲軟體系統，需由供應商完全提供，該軟體系統用來管理雲端儲存資料。資料存放在雲端儲存層，作為可選能力，供應商提供的系統應該可以滿足多種資料模型和資料類型，如關聯式資料、非關聯式資料（文件、鍵值、寬列、圖形）、地理空間、時間序列等。” Gartner 免責聲明 Gartner 不為其研究出版物中描述的任何供應商、產品或服務背書，也不建議技術用戶僅選擇具有最高評級或其他稱號的供應商。Gartner 研究出版物包含 Gartner 研究機構的意見，不應被理解為事實陳述。Gartner 不提供與本研究相關的任何明示或暗示的保證，包括任何適銷性或特定用途適用性保證。 GARTNER 是 Gartner, Inc. 和/或其附屬公司在美國和國際上的註冊商標和服務商標，MAGIC QUADRANT 是 Gartner, Inc. 和/或其附屬公司的註冊商標，在本文中獲准使用。保留所有權利。 關於Teradata天睿公司 Teradata天睿公司是多雲平台的企業級智慧資料平臺解決方案提供商，我們的企業分析技術可解決從初始階段到規模化的業務挑戰。選擇獨一無二的Teradata，即刻擁有靈活處理大量混合資料工作負載的能力，輕鬆決勝未來。詳細資訊，請訪問teradata.com.cn。
Together, Databricks and the BladeBridge team will support enterprise migrations to Databricks SQL, which has surpassed a $600 million revenue run rate SAN FRANCISCO, Feb. 5, 2025 /PRNewswire/ -- Databricks, the Data and AI company, today announced that it has welcomed the team behind BladeBridge, a leading provider of AI-powered enterprise data warehouse migration solutions, to Databricks. Together, Databricks and BladeBridge will help organizations streamline the code assessment and conversion process vital to data warehouse migrations to Databricks SQL from Snowflake, Teradata and other sources with a proven, LLM-driven approach. Ultimately, this enhanced migration process will help customers quickly and seamlessly transition to the Databricks Data Intelligence Platform. Organizations are increasingly looking to modernize their siloed, legacy data warehouses to Databricks SQL, Databricks' intelligent data warehouse. This shift allows them to capitalize on Databricks SQL's industry-leading price-performance, efficiency and AI innovations. Powered by AI, Databricks SQL auto-optimizes workloads to improve efficiency and performance and delivers intelligent experiences that help anyone gain insights from their data, with no SQL or technical expertise required. In the past year, Databricks SQL revenue grew more than 150%, surpassing $600 million run rate. BladeBridge + DatabricksBladeBridge has become one of the most advanced and popular automation solutions for migrating from existing data warehouses, including Snowflake, Redshift, and Teradata, to Databricks SQL. Now, organizations migrating to Databricks will gain access to BladeBridge's proven AI-driven solution to automate code analysis and conversion across more than 20 enterprise data warehouses and ETL tools, significantly reducing manual effort and ensuring consistent, high-quality code output. This transaction supports Databricks' strategy to help enterprises quickly achieve data intelligence across their entire data estate. A key technology partner to system integrators like Accenture, Capgemini, Celebal Tech, Ness Digital and Tredence, BladeBridge provides customers with clear insight into the scope of conversion, LLM-powered code refactoring, and easy validation of migrated systems. To date, BladeBridge has successfully supported hundreds of customers in their Databricks SQL migration journeys. "Databricks SQL is the fastest-growing data warehouse on the market. Over ten thousand organizations have chosen Databricks SQL thanks to its price performance and AI innovations. As more and more companies choose Databricks as the foundation for an open, flexible data architecture, we want to make it easier than ever to move from legacy data warehouses to the Data Intelligence Platform," said Ali Ghodsi, Co-founder and CEO of Databricks. "By joining forces with the BladeBridge team, we can help every organization accelerate their move to Databricks with significantly lower migration cost and effort." "At BladeBridge, we set out to solve frustrating challenges for companies looking to modernize their data stack, and today we've helped hundreds of organizations successfully migrate to cloud data platforms," said Simon Eligulashvili, Co-founder and Executive Vice President of BladeBridge. "We are thrilled to join the Databricks team to continue our mission — to help companies reach their data modernization goals — faster and at a far greater scale." "As a trusted data engineering specialist, we understand that meeting customers' aggressive project timelines is a key success metric," said Ranjit Tinaikar, CEO at Ness Digital. "Over the years, we have built a strong partnership with BladeBridge, collaborating on over a hundred enterprise data warehouse migrations. We look forward to deepening this relationship with Databricks as a strategic partner and delivering many more successful projects in the future." This announcement follows Databricks' recent $15 billion financing, which values the data intelligence leader at $62 billion. The company expects to cross $3 billion revenue run rate and be free cash flow positive in the fourth quarter ending January 31, 2025. About DatabricksDatabricks 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. To learn more, follow Databricks on X, LinkedIn and Facebook. Contact: Press@databricks.com
SHANGHAI, CHINA - Media OutReach Newswire - 15 November 2024 - Frost & Sullivan released the Emerging Asia-Pacific Big Data Market Research Report, 2024, in October 2024. The report provides an in-depth analysis of the big data market across key emerging markets in the emerging Asia-Pacific region, including Hong Kong SAR, the Philippines, Indonesia, Malaysia, Singapore, Thailand, Bangladesh and Sri Lanka. The report highlights the critical role of big data in driving digital transformation, especially in the finance, government, and telecom sectors, where real-time data processing and intelligent data lakes are leading the way. Huawei Cloud, along with AWS, Microsoft Azure, Google Cloud, and Alibaba Cloud, is distinguished for pioneering solutions that empower enterprises to harness big data for advanced analytics and operational efficiency. Definition and Constitution of the Big Data Market The report defines the big data market as encompassing the entire ecosystem involved in data collection, storage, computation, analysis, and application. In this ecosystem, businesses are leveraging data platforms that integrate hardware and software technologies to extract actionable insights from vast amounts of data in real-time. As digital economies rise in the Emerging Asia-Pacific region, particularly in sectors such as telecommunications, finance, and internet services, the demand for technologies like data lakes, data warehouses, and intelligent data lakes is growing rapidly. These platforms help enterprises store, process, and analyze large-scale data sets efficiently, thus driving innovation and improving business operations. Surge in Big Data Demand Amid Regional Digital Transformation The Emerging Asia-Pacific region is experiencing a rapid shift towards digital economies, creating widespread demand for big data solutions across multiple industries. The report highlights that industries such as finance, government, internet, and telecommunications are leveraging big data technologies to improve operational efficiency, drive innovation, and enhance customer experiences. Banks and financial institutions in countries like Singapore and Malaysia are using big data analytics to enhance fraud detection, optimize risk management, and personalize customer services. Telecom operators in Indonesia are utilizing data insights for network optimization, customer segmentation, and offering tailored services based on usage patterns. Meanwhile, government initiatives in Malaysia and Thailand are focusing on smart city projects where big data is used for urban planning, traffic management, and public safety. Additionally, large enterprises are increasingly adopting big data to address challenges such as multi-source data integration, real-time analysis, and data security. Fragmented data complicates decision-making, while delays in real-time analysis can hinder production and supply chain efficiency. Moreover, with growing cyber threats, robust data protection is critical to ensuring compliance and safeguarding sensitive information. In the internet sector, big data platforms are enabling companies to provide personalized user experiences by analyzing user behavior in real time. This helps improve user engagement, retention, and overall commercial value. Additionally, big data plays a crucial role in privacy protection and compliance, allowing companies to manage user data securely while adhering to regional data protection regulations, thereby building user trust and enhancing competitiveness. Real-Time Data Processing and Intelligent Data Lakes Lead the Market The report highlights that real-time computing combined with intelligent data lakes is driving major technological developments across the Emerging Asia-Pacific region. These solutions enable businesses to process large-scale, real-time data streams, significantly enhancing their ability to respond to dynamic market conditions and optimize operational efficiency. Industries such as finance, retail, and manufacturing are increasingly adopting real-time data processing to improve decision-making, manage risks, and enhance customer experiences. By integrating real-time computing with intelligent data lakes, companies can dynamically scale data management capabilities and enhance the precision of analytics. This combination offers greater flexibility and cost-efficiency, particularly for complex industries handling large datasets. Additionally, the fusion of edge computing with intelligent data lakes is expected to further accelerate data processing capabilities by enabling distributed computing architectures. This integration allows businesses to reduce latency, optimize resource management, and improve overall operational intelligence, particularly in sectors such as logistics and IoT-driven smart cities. Big Data Vendor Evaluation Criteria The report evaluates big data service providers based on three key criteria: Market Application, Technology Innovation, and Customer Service. Market Application assesses the business coverage and market share of service providers in the Emerging Asia-Pacific region. Special focus is placed on their adaptability and depth of application in key industries such as finance, government, and telecommunications. Providers leading in market share rankings across multiple regions, particularly in markets like Indonesia, Thailand, and the Philippines, are highlighted for their potential to meet diverse industry needs effectively. Technology Innovation examines providers' technical strengths in areas like intelligent data lakes, lakehouse integration, elastic scaling, and AI integration. Providers are evaluated on their leadership in data storage, real-time data processing, fault tolerance, and support for intelligent decision-making. High marks are awarded to vendors demonstrating robust technological innovation. Customer Service evaluates localized support within the emerging Asia-Pacific market, particularly focusing on data security, risk management, and compatibility with various systems and interfaces. The ability to provide tailored solutions that meet the complex data needs of enterprises is a key factor in this evaluation, enhancing customer satisfaction and competitive advantage. Huawei Cloud Leads the Big Data Market Competition in Emerging APAC The report identifies Huawei Cloud, AWS, Microsoft Azure, Google Cloud, and Alibaba Cloud as "Leaders" in the emerging Asia-Pacific big data market. These providers excel in areas like intelligent data lakes, lakehouse integration, and AI-driven analytics, offering cutting-edge technology for advanced data processing and application development. Huawei Cloud stands out in several markets, particularly in Hong Kong SAR, Thailand, and Bangladesh, where it holds a leading market share. In both the telecom and financial industries across the Emerging Asia-Pacific region, Huawei ranks first, thanks to its real-time data analytics and intelligent data lake solutions. These capabilities have been instrumental in driving operational efficiency and enabling data-driven transformations. The flexibility and security offered by Huawei Cloud's solutions help organizations optimize their operations while ensuring compliance with regulatory requirements, making it a preferred choice for enterprises in the region. AWS continues to lead the market in Singapore, particularly in the internet sectors, where its mature cloud ecosystem and extensive support services enable businesses to scale and innovate rapidly. Microsoft Azure has also shown strong performance in the Thailand and Malaysia, supporting enterprises with AI-driven cloud services and intelligent data analytics to accelerate their digital transformation journeys. Meanwhile, Cloudera, Databricks, Snowflake and IBM are positioned as "Challengers" in the market. These companies possess clear advantages in specific regions or industries and actively expand their market share while continuously improving their technology and service levels to meet customer needs. Oracle, Greenplum, and Teradata, recognized as "Specialists," are known for their specialized technical expertise and extensive experience in enterprise-level big data platforms and data warehouses, enabling them to offer customized solutions that meet specific business needs. Overall, vendors like Huawei Cloud, AWS, GCP and Microsoft Azure are driving the growth of the big data market in the Emerging Asia-Pacific region by offering advanced real-time analytics and intelligent data lake solutions. These providers continue to innovate and adapt to the evolving needs of industries, ensuring businesses can leverage big data technologies to enhance efficiency, optimize operations, and remain competitive in a rapidly digitalizing world. For a detailed report, please click: https://www.frostchina.com/content/insight/detail/6721967cfa1179b70e3864b9. Hashtag: #Frost&Sullivanhttp://www.frostchina.comThe issuer is solely responsible for the content of this announcement.
上海2023年6月8日 /美通社/ -- 6月7日，以「智領睿變，共建綠色數智金融」為主題的華為全球智慧金融峰會2023在上海開幕。會上，華為常務董事、華為雲CEO張平安面向全球發佈華為雲數倉3.0。華為雲GaussDB(DWS)作為新一代全場景雲數據倉庫，提供批量數倉、實時數倉以及IoT數倉三種服務，基於Shared-Nothing開放架構強化Serverless雲原生能力，簡化IT架構，使能人人用數，聚焦深化業務新場景。 華為常務董事、華為雲CEO張平安發表主題演講 華為雲GaussDB(DWS)， 構建高價值數據智能核心 數字化浪潮下，數據倉庫、容器、微服務等技術飛速發展，雲原生成為潮流。華為雲GaussDB(DWS)採用存、算、管三層分離的架構，基於雲原生能力，讓計算、存儲獨立伸縮，從而支撐企業業務的靈活擴展，讓工作負載在峰值場景下平穩運行。此外，華為雲提供分佈式處理技術，支撐用戶就近執行數據分析任務，實現對數據處理的快速響應。 在性能上，華為雲GaussDB(DWS)在傳統數據倉庫提供節點並行能力的基礎上，能夠實現算子並行、指令級並行，同時支持動態編譯，因此大大提升了數據處理效率，讓金融客戶輕鬆應對監管報送業務需求。 面對數智化時代銀行日益多樣化的數據分析場景，華為雲提供湖倉一體技術方案，數據在GaussDB(DWS)與MRS雲原生數據湖之間高效互通，支持多數據類型存儲、數據取用規則更靈活，從架構上真正實現了湖倉一體，幫助企業更好撬動數據潛能，最大化數據價值。 進入數字經濟時代，大數據與人工智能形成多方位深度融合發展趨勢，不斷加速各行業的數字化升級。華為雲GaussDB(DWS)提供數據採集、數據處理、數據管理、數據分析和可視化的能力，數據生產線與AI生產線的高效配合，可批量生產、快速開發。AI提升對異構數據的處理能力，與應用場景深度融合，實現智能預測、智能決策、智能識別等數據分析智能化。 華為雲GaussDB(DWS)，金融數倉最佳選擇 開幕當天，華為雲以「引領雲原生技術，敏捷加速智慧金融」為主題舉辦了面向全球的專題峰會，華為雲Marketing部部長董理斌在主題演講中正式發佈了面向海外的GaussDB(DWS)。GaussDB(DWS)基於Shared-nothing分佈式架構，具備MPP 大規模並行處理引擎，可並行完成大規模的數據處理工作，實現對數據處理的快速響應，為金融行業PB級海量大數據分析提供有競爭力的解決方案。 華為雲Marketing部部長董理斌發表主題演講 對銀行等金融機構來說，數據使用效率、開發效率至關重要，沒有數據就沒有運營。華為雲GaussDB(DWS)經過了國內頭部銀行高標準、大規模的嚴苛考驗和工程應用驗證，真正做到了以用戶需求為核心，在保障安全性、可用性的基礎上不斷增強平滑遷移的能力，打造更優質的產品和服務，得到了大量客戶的一致認可。截至目前，招行、交行等國內10家Top級銀行已選擇華為雲GaussDB(DWS)。 在遷移實踐方面，DWS可實現多種類型的數倉產品替換，在招行、交行等大行完成了Teradata的遷移；在廣發銀行，完成了Oracle Exadata的遷移；在中國人壽完成了SQL Server遷移；在全球最大的海關完成SAP HANA遷移；在光大銀行完成Greenplum和Teradata等多產品遷移，實現了全行數據的大集中。 在安全方面，GaussDB(DWS) 是目前中國唯一獲得CC安全認證的數據倉庫產品。同時在行業影響力方面，也是遙遙領先的。去年9月份華為雲聯合金融信息化研究所、10多家頭部銀行和合作夥伴，共同發佈了《金融數據倉庫白皮書》，推進提升金融數據應用水平。 華為雲GaussDB(DWS)，加速企業智能升級 隨著數字經濟持續發展，金融業的數字化轉型對於支持經濟長遠發展至關重要，數據倉庫也必然會發揮更大的價值與作用。GaussDB(DWS)基於華為長期的技術沉澱，厚積薄發，已成為國產數據倉庫中的佼佼者。 在未來，GaussDB(DWS)還將持續深入數據倉庫技術的研究和實踐，發揮自身優勢，以豐富的跨域業務場景和實踐經驗，為客戶構建堅實的數據底座，加速釋放企業數據資產價值。
SHANGHAI, June 8, 2023 /PRNewswire/ -- From June 7 to 8, Huawei Global Intelligent Finance Summit (HiFS) was held in Shanghai with the theme "Navigate Change, Shaping Smarter Finance Together". At the summit, Zhang Ping'an, Executive Director of Huawei and CEO of Huawei Cloud, released Huawei Cloud Data Warehouse 3.0 globally. Huawei Cloud GaussDB(DWS) is a next-generation all-scenario cloud data warehouse. It enhances serverless cloud native capabilities, simplifies IT architecture, and enables everyone to use and analyze data, focusing on in-depth exploration of new business scenarios. Huawei Cloud GaussDB(DWS) Builds an Intelligent Core for High-Value Data Cloud technologies have been developing fast since the last decade, including data warehouses, containers, and microservices. Cloud native has become a trend. Huawei Cloud GaussDB(DWS) uses an architecture that decouples storage, compute, and management. Based on cloud native capabilities, compute and storage resources can be independently scaled to meet business needs, ensuring service stability in peak hours. Huawei Cloud's distributed processing technology enables users to execute data analysis tasks on nearby nodes and quickly responds to data processing. Huawei Cloud GaussDB(DWS) greatly improves performance. In addition to the traditional node-level parallel processing capability, it supports operator-level and instruction-level parallel processing. Data processing becomes much faster, and financial companies can provide reports as required by regulatory authority in a timely manner. To help banks deal with increasingly diverse analysis scenarios in the data intelligence era, Huawei Cloud provides the lakehouse integration solution. GaussDB(DWS) and the MapReduce Service (MRS) cloud native data lake are connected, support many data types, and allow more flexible data access rules. The warehouse and the data lake are integrated in the same architecture, helping companies better explore the value of their data. This is an era of digital economy. Big data and AI are deeply integrated, accelerating the digital upgrade of a range of industries. Huawei Cloud GaussDB(DWS) provides data collection, processing, management, analysis, and visualization capabilities. The efficient collaboration between the data and AI production lines enables batch production and quick development. AI enhances the capability to process heterogeneous data, and is deeply integrated with application scenarios for intelligent data analysis, such as prediction, decision-making, and identification. Huawei Cloud GaussDB(DWS), the Better Option for a Financial Data Warehouse At the summit held in the afternoon on June 7, William Dong, President of Huawei Cloud Marketing, officially upgrades its GaussDB(DWS) in the keynote speech entitled "Huawei Cloud: Leading Cloud Native for Agile and Smart Finance". For banks and other financial institutions, data usage and development efficiency are critical to their operation. Huawei Cloud GaussDB(DWS) is rooted in customer requirements. Its capabilities have been verified in the projects of many large banks with high standards and large-scale businesses. So far, 10 top banks in China, including China Merchants Bank (CMB), and Bank of Communications (BOC), have chosen Huawei Cloud GaussDB(DWS). GaussDB(DWS) has strong migration capabilities. In CMB and BOC, they migrated workloads from Teradata. In Guangfa Bank (CGB), it migrated workloads from Oracle Exadata. In China Everbright Bank, it migrated workloads from multiple products, such as Greenplum and Teradata, centralizing data across the bank. GaussDB(DWS) guarantees high security. It is the only data warehouse that has obtained the Common Criteria security certification in China. It is also an industry leader of data warehouses. In September 2022, Huawei Cloud, together with the Financial Information & Technology Institute (FITI), more than 10 top banks, and partners, released the Financial Data Warehouse White Paper to facilitate the development of financial data applications. Huawei Cloud GaussDB(DWS) Accelerates Intelligent Upgrade Data warehouses play an important role in digital economy. GaussDB(DWS) has over 10 years of technical accumulation and extensive cross-domain practices. It will continue to develop and apply data warehouse technologies, build a solid foundation for customers, and help companies unleash the value of their data assets.
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