DATA LAKES in Chinese translation

• 数据湖

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

Vendors are marketing Data Lakes as a panacea for Big Data projects, but that's a fallacy.”.
供应商将DataLakes作为大数据项目的灵丹妙药进行营销，但这是一个谬论。

It provides you the tools to develop queries against databases, data warehouses and data lakes, whether on-premises or in Azure.
提供了针对数据库、数据仓库和DataLake（无论是在本地，还是在Azure中）开发查询的工具。

Even new data lakes will get rolled out in a much more deliberate manner with clear initial use cases and usage and governance policies.
新的数据湖将以一种更严谨的方式推出，具有清晰的初始用例、使用和管理策略。

The tools can also link to Hadoop clusters and data lakes to access information in the Hadoop Distributed File System and the related data repositories.
该工具还可以链接到Hadoop集群和数据湖泊，获取存储在Hadoop分布式文件系统和相关的数据存储库中的数据。

He never intended data lakes to describe a huge Hadoop repository that pulled data from all enterprise applications.
他从来就没有打算用数据湖来描述从所有企业应用程序获取数据的巨大的Hadoop存储库。

Data Lakes blocks containing the complete history of all financial transactions, all available for review.
其庞大的数据湖包含了所有金融交易的全部历史记录，并且全部可供分析。

For example, 78% maintain their corporate data in centralized data lakes, compared with only 37% and 43% of European and U.S. pioneers, respectively.
例如，78%的公司数据保存在集中的数据池中，而欧洲和美国的先锋公司分别只有37%和43%。

The rise of IoT will increase the number of data sources and formats, making data lakes the only reliable solution.
物联网的兴起将增加数据源和格式的数量，使数据湖成为唯一可靠的解决方案。

Using Azure Event Hubs, customers can also wire-in additional Azure services like Azure Stream Analytics and Azure Data Lakes.
通过使用Azure事件中心，用户们能够接入其他Azure服务，如AzureStreamAnalytics和AzureDataLakes。

Data is more and more coming from a diverse array of systems, including cloud platforms, analytics tools and Hadoop-based data lakes.
数据越来越多来自各种系统，包括云平台，分析工具和基于Hadoop的数据湖。

To further understand the difference between the two, Data Lakes is unfiltered body water while Data Warehouse is more of a collection of bottled water.
为了进一步了解两者之间的区别，不妨打个比方：数据湖如同未经过滤的河水，而数据仓库更像是一堆瓶装水。

Data lakes and data warehouses are two ways that a brand can collect and manage all that data, but what's the difference between the two?
数据湖和数据仓库是品牌可以收集和管理所有数据的两种方式，但两者之间的区别是什么？与从业者交谈，了解他们如何区分这两者。?

Through 2018, 90% of deployed data lakes will be rendered useless, as they're overwhelmed with information assets captured for uncertain use cases.”.
到2018年，90%已部署的数据湖将失效，因为以不确定的使用案例为目的而收集的信息资产会让它们不堪重负。

In fact, data lakes are designed for big data analytics if you want and, more important than ever, for real-time actions based on real-time analytics.
事实上数据湖是为大数据分析而设计的，更重要的是，它是为基于实时分析的实时操作而设计的。

Azure web apps and connected services, including Azure Data Lake.
AzureWeb应用和连接的服务，包括AzureDataLake.

The answer for today's forward-looking organizations increasingly relies on a data lake.
如今，较具前瞻性的企业都越来越依赖数据湖。

We call it the data lake.
我们称此为百景湖。

I call this a data lake.
我们称此为百景湖。

Do you need a data lake?
你真的需要数据湖吗？?

We hesitate to call it a data lake.
我们称此为百景湖。