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  • The ultimate Guide to Data Engineering.
    The ultimate Guide to Data Engineering.
    Data engineering is the practice of designing and building systems for collecting, storing, and analyzing data at scale. It is a broad field with applications in just about every industry. This article aims at providing a step by step guide on how on
    Python Tutorial.cloudera 611 2024-08-27 06:05:05
  • Cloudera announces new vice president of Greater China
    Cloudera announces new vice president of Greater China
    Beijing, China, April 9, 2024 - Cloudera, an enterprise big data and artificial intelligence platform company, today announced the appointment of a new vice president of Greater China. This move aims to further focus on customer success and business transformation, and help enterprises adapt to the development of big data and artificial intelligence applications and accelerate the digital transformation process by providing hybrid multi-cloud big data and big model capabilities. Cloudera now appoints Mr. Liu Fuchun as Vice President (RVP) of Greater China. He will be responsible for promoting Cloudera's further expansion in China and leading strategic sales, channel development and localization strategy. The appointment of Liu Fuchun, Vice President of Cloudera Greater China, as a new executive further demonstrates Cloudera’s commitment to
    AI.cloudera 531 2024-04-09 15:07:10
  • Accelerating enterprise GenAI innovation end-to-end, NVIDIA NIM microservices have become a highlight for software companies!
    Accelerating enterprise GenAI innovation end-to-end, NVIDIA NIM microservices have become a highlight for software companies!
    Software development company Cloudera recently announced a strategic partnership with NVIDIA to accelerate the deployment of generative AI applications. The collaboration will involve integrating NVIDIA's AI microservices into the Cloudera Data Platform (CDP) and is designed to help enterprises more quickly build and scale custom large language models (LLMs) based on their data. This initiative will provide enterprises with more powerful tools and technologies to better utilize their data resources and accelerate the development and deployment process of AI applications. This collaboration will bring more opportunities to enterprises, helping them make more efficient data-driven decisions and drive business development. The collaboration between Cloudera and NVIDIA will provide enterprises with more choice and flexibility,
    AI.cloudera 474 2024-03-22 08:00:23
  • Cloudera launches multiple functions integrating NVIDIA microservices: unlocking data potential and accelerating enterprise generative AI applications
    Cloudera launches multiple functions integrating NVIDIA microservices: unlocking data potential and accelerating enterprise generative AI applications
    Remus Lim, senior vice president of Cloudera Asia Pacific, emphasized the complementary relationship between NVIDIA's leading position in artificial intelligence computing and Cloudera's expertise in data management. He said that the cooperation between the two will help customers build models that can provide highly accurate data and insights. These models will run in a secure machine learning (ML) environment, trusted by the enterprise, and able to meet changing needs. Lim emphasized that they are excited to assist customers in accelerating their AI journey, achieving a seamless transition from the AI exploration and experimentation stage to large-scale deployment across the entire organization. Beijing, March 20, 2024 - Recently, Cloudera, a trusted enterprise artificial intelligence data company
    AI.cloudera 696 2024-03-20 16:50:48
  • To improve skills, what professional certificates do Java engineers need to obtain?
    To improve skills, what professional certificates do Java engineers need to obtain?
    With the continuous development of the Internet and information technology, Java engineers have become one of the core positions in the IT industry. As a Java engineer, if you want to improve your skills, it is very important to have some professional certificates. This article will introduce some common professional certificates that Java engineers need to obtain. OracleCertifiedProfessional,JavaSEProgrammer(OCP-JP)Java provided by Oracle
    javaTutorial.cloudera 682 2024-02-02 18:00:07
  • What are the server management software?
    What are the server management software?
    Server management software includes vCenter Server, Microsoft Server Management Studio, IBM Tivoli, HP OpenView, Dell OpenManage, Red Hat Satellite, Canonical Landscape, Apache Hadoop, Cloudera Manager and Microsoft SQL Server.
    Common Problem.cloudera 1434 2023-10-20 09:55:19
  • How Redis speeds up Spark
    How Redis speeds up Spark
    ApacheSpark has gradually become a model for the next generation of big data processing tools. By borrowing from open source algorithms and distributing processing tasks across clusters of compute nodes, Spark and Hadoop generation frameworks easily outperform both in the types of data analysis they can perform on a single platform and in the speed with which they can perform these tasks. over traditional frameworks. Spark uses memory to process data, making it significantly faster (up to 100 times faster) than disk-based Hadoop. But with a little help, Spark can run even faster. If you combine Spark with Redis (a popular in-memory data structure storage technology), you can once again significantly improve the performance of processing analysis tasks. This is due to Red
    Redis.cloudera 1233 2023-06-03 11:45:36
  • By 2032, the artificial intelligence platform market will reach US$254.14 billion
    By 2032, the artificial intelligence platform market will reach US$254.14 billion
    According to FutureMarketInsights, the global artificial intelligence platform market is expected to be worth US$10 billion in 2022, growing at a CAGR of 38.2% and worth US$254.14 billion by the end of the 2022-2032 forecast period. The market is worth US$9.6 billion in 2021 and is expected to grow 4.2% year-on-year between 2021 and 2022. According to FMI, the artificial intelligence platform market has grown as decision-making is a critical point for service providers and various manufacturers in the market. The AI platform market is booming as players are now focusing on creating AI platforms and targeting niche solutions that solve specific enterprise problems, which has led to its growth. AI
    AI.cloudera 962 2023-04-17 14:37:03
  • Data and Artificial Intelligence Technology Forecast for the Second Half of 2022
    Data and Artificial Intelligence Technology Forecast for the Second Half of 2022
    Based on what we've seen so far in 2022, Datanami is confident it can make these five predictions for the rest of the year. Data Observability Continues The first half of the year has been huge for data observability, allowing customers to better understand what is happening with their data flows and develop relevant metrics. As data becomes more important to decision making, so does the health and availability of that data. We’ve seen a number of data observability startups raise hundreds of millions of dollars in venture capital, including Cribl ($150 million Series D); Monte Carlo ($135 million Series D); Coralogix ($135 million Series D) US$142 million); and
    AI.cloudera 1188 2023-04-12 21:34:06
  • To accelerate AI development, how can companies use MLOps to improve production efficiency?
    To accelerate AI development, how can companies use MLOps to improve production efficiency?
    When companies first deploy artificial intelligence and build machine learning projects, they often focus on theory. So is there a model that can provide the necessary results? If so, how do we build and train such a model? According to IDC data, it takes more than nine months on average to deploy artificial intelligence or machine learning solutions. Mainly because the tools data scientists use to build these proofs of concept often don’t translate well to production systems. IDC analyst Sriram Subramanian said: "We call the time required for the R&D process 'model speed', that is, how long it takes from start to finish." Enterprises can use MLOps to solve the above problems. MLOps(Machine
    AI.cloudera 957 2023-04-12 12:31:07
  • Enterprises are leveraging machine learning operations to gain business benefits
    Enterprises are leveraging machine learning operations to gain business benefits
    When companies first begin deploying AI and launching machine learning projects, the focus is often on a theoretical level. Is there a model that can provide the necessary results? How to build this model? How to train this model? But the tools used by data scientists to develop these proof-of-concepts often do not translate well to production systems. As a result, it takes more than nine months on average to deploy an AI or machine learning solution, according to IDC. “We call it ‘model velocity,’ which is the time it takes for a model to go from start to finish,” said Sriram Subramanian, an analyst at IDC. This is where MLOps come into play. MLOps (machine learning
    AI.cloudera 795 2023-04-10 08:51:05
  • What are the three types of databases?
    What are the three types of databases?
    Database types can be divided into hierarchical, network and relational types. A hierarchical database presents data according to a hierarchical structure (tree structure); a network database is a database that uses network principles and methods and is based on a network data model; a relational database uses a relational model to A database that organizes data.
    Common Problem.cloudera 60404 2023-02-13 16:01:42
  • What is the big data learning route?
    What is the big data learning route?
    Big data learning route: java (Java se, javaweb); Linux (shell, high concurrency architecture, lucene, solr); Hadoop; machine learning (R, mahout); Storm; Spark; Python; cloud computing platform.
    Common Problem.cloudera 7504 2019-07-25 17:34:30
  • How many tools are needed for big data analysis?
    How many tools are needed for big data analysis?
    Big data analysis requires many tools, such as Hadoop, Ambari, Disco, Avro, HPCC, Lumify, Pandas, Storm, Blazegraph, MongoDB and other tools.
    Common Problem.cloudera 4145 2019-07-25 17:25:41
  • Big data learning route
    Big data learning route
    java (Java se, [mysql]), Linux (shell, high concurrency architecture, lucene, solr), Hadoop, machine learning (R, mahout), Storm (Storm, kafka, redis), Spark, Python
    Common Problem.cloudera 2522 2019-06-05 10:59:37

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