What is the translation of " BIG DATA APPLICATIONS " in Chinese?

• 大数据应用
• 大数据应用程序

Examples of using Big data applications in English and their translations into Chinese

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

Big data applications are moving toward cross-border integration.
第四，大数据的应用正在走向跨境集成。

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

The project's goal is to simplify the development of big data applications.
该项目的目标是简化大数据应用的开发。

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

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

This is because big data applications act on historical snapshots of data..
这是因为大数据应用工作在数据的历史快照上。

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

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

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

Big data applications help improve ad targeting amid increasingly complex content consumption behavior.
大数据应用有助于在日益复杂的内容消费行为中改善广告定位。

And one of the key characteristics of big data applications is that they demand real-time or near real-time responses.
而大数据应用的关键特征之一是它们需要实时或接近实时的响应。

Artificial Intelligence and Machine Learning- Finally, consider how innovative the various big data applications vendors are.
人工智能和机器学习-最后，考虑各种大数据应用供应商的创新。

These Hadoop and Big Data applications are helping enterprises manage and analyze large stores of data..
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。

MapR packages a broad set of Apache open source ecosystem projects that enable 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。

Today, big data platform, big data analysis, big data applications have been developed in full swing.
如今大数据平台，大数据分析、大数据应用已经发展得如火如荼。

These software-driven systems and intelligent agents incorporate advanced data analytics and Big Data applications.
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 circuits are, therefore, ideal for complex routing and big data applications, where an exact match is rarely necessary.
因此，这些电路非常适用于复杂路由和大数据应用，其中很少需要精确匹配。

Big data applications are not just a technology matter- they bring us great potential when combined with content and business needs.
大数据应用不仅仅是技术层面的事务，在结合内容和业务需求之后，它能够为我们带来巨大的潜力。

Usability- Organizations should also consider the"learning curve" for any big data applications that they intend to purchase.
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”。

However, big data applications have matured in the past several years, and the enterprise's use of business analytics has matured as well.
但是，大数据应用在过去的几年里已经日趋成熟，企业所使用的业务分析功能也随之日臻完善。

Just as SaaS and the cloud completely revolutionized the way businesses operate, so will Big Data applications(BDAs).
正如SaaS和云技术一样完全变革了企业的运作方式一样，大数据应用(BDA)也同样可以。

But don't forget that large scaling and big data applications also generate huge quantities of analytics and monitoring data..
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。

Python finds use in many spheres- web applications, automation, scientific modelling, big data applications and many more.
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。

Your organization's existing infrastructure, big data applications, compliance needs and level of expertise may make one more attractive than the others.
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。

CDAP(Cask Data Access Platform) is a framework running on top of Hadoop that abstracts away the complexity of building and running big data applications.
CDAP（CaskDataAccessPlatform）是一个在Hadoop之上运行的框架，抽象了建造和运行大数据应用的复杂性。

To make industrial big data applications, you must first have a rigorous logic reasoning, data at the same time, also have a platform and tools.
因为，要想做好工业大数据应用，首先必须有一套严谨的数据推理逻辑，同时，还要有平台和工具。

Structured data is traditionally easier for Big Data applications to digest, yet today's data analytics solutions are making great strides in this area.
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。

Cloud and big data applications are placing new challenges on systems, just as the underlying chip technology is facing numerous significant physical scaling limits.
云计算和大数据应用又对系统提出了新的挑战，这是因为底层的芯片技术正面临着众多显著的物理极限。