双语：为什么DAM（数字资产管理）的未来取决于大数据？

36大数据专稿，原文作者：Anand Srinivasan  本文由Tom Deng编译向36大数据投稿，并授权36大数据独家发布。转载必须获得本站及作者的同意，拒绝任何不标明作者及来源的转载！

Cloud storage business has truly taken off in the past couple of years. According to a Markets And Markets study, the public/private cloud storage industry is expected to be worth $56.57 billion by 2019.For perspective, the public cloud storage industry was estimated to be just around $21 billion a couple of years back, according to Technology Business Review.

云存储业务在过去的几年里真的很火。根据市场和市场研究，到2019年公共/私有云存储产业预期价值将高达565.7亿美元。根据商业评论指出，从发展前景来看，在接下来几年，公共云存储产业估计价值大约为210亿美元。

Besides cloud computing, one of the popular applications of cloud is in digital asset management, or DAM for short. For the uninitiated, DAM refers to the process of storing, cataloguing, searching and delivering of digital files, mainly audio, video, images and office documents. DAM is an extremely critical element of businesses like media and journalism that deal with lots of content. A typical media house, especially one that deals with videos, owns digital assets that are dozens of terrabytes large. In terms of data volume, it is common for these media houses to own northwards of a hundreds thousand files. Tagging every file, along with storing and retrieving them is a lot of work.

除了云计算，其中最受欢迎的云应用之一是数字资产管理（Digital Asset Management)，或者简称DAM。对于新手来说，DAM涉及数据存储过程、分类、检索和数字文件(其主要有音频，视频，图像和办公文件)分发。DAM是像媒体和新闻这些需要处理大量内容业务中一个非常关键的因素。一个典型的传媒公司，尤其是那些拥有几十TB视频数字资产的公司。就数据量而言，这些媒体公司拥有成千上万的文件是很常见的事情。标记每个文件并对它们进行存储和检索是一项浩大的工程。

Despite the volume of content that DAM works with, this is still not the realm of big data analysts. It is not difficult to see why. Most small and medium sized business houses still make do with in-house CMS tools for managing their digital assets. Even the larger businesses that pay for dedicated DAM services have not more than a million or two files to store and process. Big data is typically used for data volumes that are much higher.

尽管DAM工作的内容量大，但还不是大数据分析。这不难理解，因为大多数中小型企业仍用内部的CMS（内容管理系统）工具来管理他们的数字资产。即使是大企业，支付专用DAM服务不超过一百万个或只存储和处理一两个文件。大数据通常用于更大的数据量。

That could be changing in the near future though. Lately, the scope of digital asset management tools has been growing from merely storing and cataloguing data to integrate with transactional business intelligence and analytics tool to provide more useful information. According to Ralph Windsor, a senior partner at consulting firm DayDream, one utility of big data in digital asset management is for marketers to apply analytics tools on DAM to identify and interpret actionable information – like using sales data to identify the kind of images or content that works versus ones that do not.

这一切可能会在不久的将来有所改变，最近，DAM工具的范围已经从单纯的存储和规类数据转向整合交易商业智能（BI)和分析工具，以提供更多有用的信息。根据DayDream咨询公司资深合伙人Ralph Windsor说，大数据在DAM的一个应用是营销人员在DAM上运用分析工具来识别和解释的可操作的信息–像用销售数据来识别某类图像或内容在工作与销售中区别。

What is driving this evolution of digital asset management is the metadata that accompanies every digital asset. For instance, consider the two images of Steve Jobs below.

伴随着每一个数字资产的元数据推动了数字资产管理的这种演变.例如，考虑以下两幅关于史蒂夫·乔布斯图片。

At the outset, they are not too different. However, there are pretty distinctive differences between the two images. The one on the left was taken during the launch of iPhone 2G, while that on the right was during the iPhone 3G launch. In addition to this, there are other differences like the one on the left being a black&white image with Steve Jobs smiling. A sophisticated media management system would include all these minor details in the metadata. This way, it is easier to retrieve a particular image from a repository of millions of images at a later stage.

咋一看，他们是没有太大的不同。然而细看，他们之间有很明显差异。左边的是iPhone 2G推出时拍摄的，而右边是iPhone 3G推出时。除此之外，还有其他的差异，左边是黑白图像，史蒂夫·乔布斯面带微笑。一个先进的媒体管理系统将所有这些细节包括在元数据中。这样，在将来，可以很容易从数以百万计的图像库中检索出一个特定的图像。

A DAM system that is integrated with big data analytics tools will be able to analyze the marketability of different images and track other details like conversion rates, social shareability. Such intelligence would be paramount for a company that wants to craft a business strategy for their future product launches – should the press release for an automobile company include the image of the vehicle or that of their popular CEO? A PR agency that uses DAM tools integrated with big data will be able to offer the right answer to such a client.

一个整合了大数据分析工具的DAM系统将能够分析不同的图像适销性，并能跟踪其他细节，如市场转化率，社会共享性。这些信息对于那些想在将来为他们的产品发布制作一个商业策略的公司来说是非常重要的， 如一家汽车公司的出版刊物上是否包含车辆的图片或其受欢迎的首席执行官的(CEO)图片？像这样的问题，那些采用DAM工具与大数据集成的公关机构就能够给你提供正确的答案。

原文标题：Why the Future of Digital Asset Management Hinges on Big Data