What is the translation of " 大数据应用程序 " in English?

• big data applications

Examples of using 大数据应用程序 in Chinese and their translations into English

大数据应用程序的设计和构建（4天）.
Designing and building big data applications(Day 2) Training.

对于大数据应用程序也是如此。
This is also true for big data applications.

利用大数据应用程序来实时监测和管理网络。
Leverage big data applications to monitor and manage networks in real-time.

大数据应用程序根据它们的特定需求使用不同的平台。
Big data applications are using different platforms based on their specific requirements.

这说明了多种方法对大数据应用程序的重要性。
This illustrates the importance of multifaceted approaches to big data applications.

大数据应用程序和服务的经验和案例研究.
Experiences and case studies of big data applications and services.

这些Hadoop和大数据应用程序在帮助众多企业管理和分析大量数据。
These Hadoop and Big Data applications are helping enterprises manage and analyze large stores of data..

传统上，结构化数据对大数据应用程序来说更容易消化，但如今的数据分析解决方案正在这方面取得重大进展。
Structured data is traditionally easier for Big Data applications to digest, yet today's data analytics solutions are making great strides in this area.

但不要忘记，大规模和大数据应用程序也会生成大量的分析和监控数据。
But don't forget that large scaling and big data applications also generate huge quantities of analytics and monitoring data..

组织的现有基础设施、大数据应用程序、遵从性需求和专业知识水平可能比其他组织更具吸引力。
Your organization's existing infrastructure, big data applications, compliance needs and level of expertise may make one more attractive than the others.

Python可用于许多领域-Web应用程序，自动化，科学建模，大数据应用程序等等。
Python finds use in many spheres- web applications, automation, scientific modelling, big data applications and many more.

可用性-组织还应该考虑他们打算购买的任何大数据应用程序的“学习曲线”。
Usability- Organizations should also consider the"learning curve" for any big data applications that they intend to purchase.

这些软件驱动的系统和智能代理包含高级数据分析和大数据应用程序。
These software-driven systems and intelligent agents incorporate advanced data analytics and Big Data applications.

OpenSourceEnginesMapR打包了大量的Apache开源生态系统项目，可以启用大数据应用程序。
MapR packages a broad set of Apache open source ecosystem projects that enable big data applications.

有趣的是，40％的受访者还表示，他们已经在其容器中部署了大数据应用程序工具，如Spark和Hadoop。
Interestingly, 40% of respondents also said they had already deployed big data applications tools, like Spark and Hadoop in their containers.

IBM使得利用Hadoop从大数据中获取价值并构建大数据应用程序变得更加简单。
BigInsights makes it simpler for Hadoop to get value out of big data and building big data applications.

Python在许多领域中被使用-例如：Web应用程序，自动化，科学建模，大数据应用程序等等。
Python finds use in many spheres- web applications, automation, scientific modeling, big data applications and many more.

机器学习取决于IT、数学和自然语言的交集，在大数据应用程序中会通常用到机器学习。
Machine learning lies at the intersection of IT, mathematics, and natural language, and is typically used in big-data applications.

而且，大数据应用程序还有一个特征，就是注入不同格式的数据。
Also, one of the characteristics of big data applications is ingesting data in different formats.

因此，作为大数据应用程序的架构师和设计者，我们要积极主动地创造出保障措施，防止对这些大数据库存的滥用。
Therefore, our role as big data application architects and designers is to be proactive in creating safeguards to prevent abuse of these big data stores.

大数据应用程序最佳选择：是SQL还是NoSQL？?
What's better for your big data application, SQL or NoSQL?

观点】大数据应用程序最佳选择：是SQL还是NoSQL？?
What's better for your big data application, SQL or NoSQL?

离线大数据应用程序的例子包括：基于Hadoop的工作负载；现代数据仓库；.
Examples of offline Big Data applications include Hadoop-based workloads; modern data warehouses;

相反，您可以精确地预置支持大数据应用程序所需的资源类型和大小。
Instead, you can provision exactly the right type and size of resources you need to power big data analytics applications.

Lambda架构是构建大数据应用程序的一种很有效的框架，但它还不够好。
The Lambda architecture is a helpful framework for building big data applications, but it is not sufficient.

近年来，我们看到了搜索引擎正在成为复杂大数据应用程序输出和交付的首选机制。
In recent years, we have seen a shift toward search engines becoming the preferred mechanism for the output and delivery of complex big data applications.

因此，我们必须在了解隐私法规及推荐实践的情况下开发大数据应用程序。
Therefore, we must develop big data applications with an understanding of privacy principles and recommendations.

Hadoop有非常复杂的索引算法，因此它可以提取以前无法为大数据应用程序使用的数据。
Hadoop has very sophisticated indexing algorithms, so it can extract data that was previously unattainable for many big data applications.

快速构建高度可扩展且安全的大数据应用程序。
Build highly scalable and secure Big Data applications fast.