What is the translation of " DATA VIRTUALIZATION " in Chinese?

• 数据虚拟化

Examples of using Data virtualization in English and their translations into Chinese

Data Virtualization.
数据虚拟.

Now is the time for data virtualization.
数据虚拟化的时候到了.

In practice, data virtualization takes on many different forms.
实际上，数据虚拟化有许多不同的形式。

This needs to include how to manage the data virtualization environment.
这需要考虑到如何管理数据虚拟化环境。

Why data virtualization is good for big data analytics.
为什么数据虚拟化适合大数据分析.

There are different types of virtualization, the first one being Data Virtualization.
虚拟化有多种类型，第一种是数据虚拟化。

How data virtualization can help government hone services and cut costs.
数据虚拟化如何帮助政府改进服务降低成本.

Part of this transition also involves using the cloud as the basis for emerging data virtualization platforms.
这种转变的一部分也涉及到使用云计算作为新兴数据虚拟化平台的基础。

Data virtualization- a data integration process in order to gain more insights.
数据虚拟化-数据整合过程，以便获得更多的洞察力。

Davis and Eve outline 6 key best practices anyone undertaking a data virtualization effort needs to consider:.
Davis和Eve概述了从事数据虚拟化工作的任何人都应该考虑的六大最佳实践：.

Data Virtualization models are described as easy to understand, easy to build, and easy to maintain.
数据虚拟化模型被认为易于理解、易于构建和易于维护。

More strategically, people might be using data virtualization to pull in social media, different marketing campaigns.
更具战略意义的是，人们可能会在社交媒体上利用数据虚拟化，以带来不同的营销活动。

Data Virtualization has recently been adapted to the Cloud and will be used increasingly, in 2018.
数据虚拟化最近已经适应了云计算，并将在2018年得到越来越多的使用。

Both of these challenges to a new enterprise data architecture strategy are addressed using data virtualization tools.
全新的企业数据架构战略所面临的这些挑战，都可以通过使用数据虚拟化工具得以解决。

Data virtualization takes varying sets of data sources and integrates them into one logical database for users.
数据虚拟化需要不同的数据源集，并将它们集成到一个供用户使用的逻辑数据库中。

While big data has become all the rage over the past few years, another technology also has entered the mainstream: data virtualization.
大数据在过去的几年里已经风靡时，另一项技术也进入了主流：数据虚拟化。

Data virtualization and federation tools provide a layer of abstraction between a set of data sources and the different data consumers.
数据虚拟化和联邦工具在一组数据源和不同的数据使用者之间提供了一个抽象层。

But where the traditional SOA approach has focused on business processes, data virtualization focuses on the information that those business processes use.
但是，传统的SOA方法把重点放在商业程序，而数据虚拟化的重点则是在这些商业程序所运用的信息上。

The Data virtualization tool sits in from of the user's different data sources and manages it by delivering data to where it is needed.
数据虚拟化工具位于用户的不同数据源中，并通过将数据传递到需要的地方来对其进行管理。

First abstract the data sources, then layer the BI applications on top and gradually implement the more advanced federation capabilities of data virtualization.”.
先对数据源进行抽象处理，然后将商业智能应用程序放到上面，最后逐步实施数据虚拟化的更高级的联合功能。

As a modern data layer, the TIBCO® Data Virtualization system addresses the evolving needs of companies with maturing architectures.
作为现代数据层，TIBCO®DataVirtualization将利用成熟架构满足企业不断变化的需求。

Graphic data virtualization allows organizations to retrieve and manipulate data on the fly regardless of how the data is formatted or where it is located.
图形数据虚拟化允许企业即时检索和操作数据，无论数据是否格式化、放置在何处。

These tools fit into a variety of categories, including data integration, data virtualization, data preparation, ETL, data quality and data governance.
这些工具适用于各种类别，包括数据集成、数据虚拟化、数据准备、ETL、数据质量和数据治理。

The primary goal in using Data Virtualization technology involves providing access to the data from a variety of data sources through a single point.
使用数据虚拟化技术的主要目标是通过单点提供来自各种数据源的数据访问。

In effect, data virtualization simplifies the ability to blend data from multiple sources via consumer-oriented data materialization rules.
实际上，数据虚拟化工具通过面向使用者的数据实体化规则，简化了将来自多个源的数据相融合的技术。

Because data sources don't have to be stored locally, data virtualization benefits anyone collecting data from several distributed sources(sensors, video cameras, third-party influencers, etc.).
由于数据源不必存储在本地，因此数据虚拟化有益于从几个分布式源(传感器、摄像机、第三方影响者等)收集数据。

Data virtualization involves using various data integration techniques to consolidate data real-time from various sources and technologies, not just structured.
数据虚拟化需要使用多种数据集成技术以对多种数据源和技术的数据进行实时整合，而不仅仅结构化数据。

The company's unique data virtualization architecture improves performance, protection, and data efficiency, while also enabling global unified management from a single console.
该公司独有的数据虚拟化架构提升了性能、保护功能和数据效率，同时可利用单一控制台实施全球统一管理。

Data Quality, Data Integration, and Data Virtualization will merge with Master Data Management to form a unified Information Management Platform for structured and unstructured data..
数据质量、数据集成和数据虚拟化将与主数据管理融合，构成处理结构化数据和非结构化数据的统一信息管理平台。