大数据

大数据

Many organizations struggle to manage and mine data that comes from modern technology platforms. The data arriving into the organization may be in the form of a small amount of very large files, or in the form of millions of very small files arriving every day, 甚至每一分钟. Platforms such as Apache Spark™ are seen by data scientists as preferred solutions to manage and process these vast amounts of data to quickly generate insight from data found in distributed file systems. Its ability to work in-memory with extremely large datasets is in part why Spark is included in 大数据 architectures. 澳门黄金城赌城官网 enables organizations to work efficiently with 大数据 in high-performance computing (HPC), modern processing and storage platforms, 和云环境. Don’t let difficult data be a barrier to making informed decisions.

大数据与高性能计算

澳门黄金城赌城官网®无限™ 是一个交钥匙, state-of-the-art private appliance, available in both on-premises and cloud-based formats. 澳门黄金城赌城官网 Unlimited delivers unlimited use of a wide range of 澳门黄金城赌城官网®HyperWorks® solver software for simulating mechanics, 液体, 电磁学, 以及更多——包括建模, 可视化, 和优化. To keep it all working at maximum efficiency, HPC resource management and user-friendly web portal software comes included with every system in the industry-leading 澳门黄金城赌城官网®PBS™ 包.

澳门黄金城赌城官网无限装箱软件, 系统管理, and infrastructure as a service into a single, 直观的平台.

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大数据和数据分析

作为提高效率的工具, 澳门黄金城赌城官网工作室®®知识 for Apache Spark allows users to interact with Spark using an interactive and intuitive interface to generate error-free code for use in production scripts. The ability to easily manipulate data in distributed storage architectures, including large datasets that have billions of rows and thousands of columns, is unmatched by any other solution.

One workflow is used to transform 大数据 formats and to build and deploy many different types of predictive machine learning models.

Rapid 可视化 of data and easily explaining insight found in extremely large amounts of data allow enterprise data analytic teams to make informed decisions from data sources such as Hadoop HDFS, Amazon S3, and other storage supported by Spark.

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新的原生云解决方案

数据驱动的决策

Dynamic tools and collaborative environment to solve complex problems, 加快转变, 并驱动业务价值

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特色资源

澳门黄金城赌城官网 Knowledge Studio for Apache Spark™

Knowledge Studio for Apache Spark™ is unique because it allows users scale up, scale-wide和缩小的. It not only leverage’s Apache Spark’s ability to operate on datasets with very large numbers of records, it is also capable of generating improved SparkSQL queries on datasets that have thousands of columns. 进一步, Knowledge Studio for Apache Spark provides the ability to scale down by avoiding the overhead costs of parallelization when datasets are very small.

数据表

重新定义HPC的可能性

We are seeing a mass increase in data, coming at us from all directions. Whether you are running AI-enhanced HPC applications on-premises or HPC workloads in the cloud, you need platforms and solutions that will offer the performance, 可伸缩性, and flexibility to redefine what’s possible with HPC.

网络研讨会

Overcome 大数据 Access Challenges with Knowledge Studio for Apache Spark™

In combination with its market-leading data 可视化 approach for building, 探索和分割数据, and building explainable predictive models, 澳门黄金城赌城官网 Knowledge Studio for Apache Spark&tradel enables data science teams to build machine learning models from data located in distributed file systems without having to code. Data preparation and profiling allows for easy data extraction and manipulation. Knowledge Studio’s efficient use of compute resources, 尤其是在云环境中, shortens processing cycles and reduces costs. Large datasets with billions of rows and thousands of columns can be efficiently mined for better decision intelligence.

在线研讨会

Sporting Goods Chain Fuels Results with Data

In order to compete in the fast-paced retail industry, a chain of more than 100 sporting goods stores operating across the United States needed a more efficient and accurate method for preparing and analyzing data to enable management teams to quickly make strategic operational decisions.

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