Enable javascript in your browser for better experience. Need to know to enable it? Go here.
本页面中的信息并不完全以您的首选语言展示,我们正在完善其他语言版本。想要以您的首选语言了解相关信息,可以点击这里下载PDF。
更新于 : May 22, 2013
不在本期内容中
这一条目不在当前版本的技术雷达中。如果它出现在最近几期中,那么它很有可能仍然具有相关参考价值。如果这一条目出现在更早的雷达中,那么它很有可能已经不再具有相关性,我们的评估将不再适用于当下。很遗憾我们没有足够的带宽来持续评估以往的雷达内容。 了解更多
May 2013
试验 ? 值得一试。了解为何要构建这一能力是很重要的。企业应当在风险可控的前提下在项目中尝试应用此项技术。
The amount of data that even a relatively low volume website can generate is huge. Once you add in analytics, business metrics, demographics, user profiles and multiple devices, it can become overwhelming. Many organizations use data warehouses as a repository with data being sucked in from all parts of the organization. The challenge here is that these often turn into “Data Fortresses.” Even getting timely business metrics becomes a challenge, let alone running exploratory queries across the entire data set. Technologies like the cloud based BigQuery help. The pay-as-you-go model and the ability to do ad hoc queries lets you gain insight without buying specialist hardware and software. A data-driven business should put data in the hands of the decision makers, not hidden behind technological barriers and bureaucracy.
Oct 2012
评估 ? 在了解它将对你的企业产生什么影响的前提下值得探索
Google’s BigQuery brings data analytics to the cloud. Rather than loading data into an expensive data-warehouse with predefined indexes, BigQuery allows you to upload and investigate a data set through ad-hoc SQL-like queries. This is a great way to create a cheap proof-of-concept or even a complete application, as processing of hundreds of gigabytes of data by thousands of servers happens in seconds.
发布于 : Oct 22, 2012
Radar

下载第26期技术雷达

English | Español | Português | 中文

Radar

获取最新技术洞见

 

立即订阅

查看存档并阅读往期内容