Since the country promulgated the outline of big data, the topic of data transactions has been hot all the time, and the debate on data circulation has never stopped. Controversial topics will not be discussed much, and the issues that should be resolved by the market will be left to time to deal with. The editor here tries to take you through the current situation of the major data trading platforms from an objective point of view.
1. Background
The big data trading market is exactly the same as the US oil market during the Rockefeller era, in which the government, corporate giants, and grassroots people all participate. But in general, the concentration is not high, and the transaction scale is not large. It is still a virgin land, waiting for the emergence of the hero who dominates the world.
2. Enter the topic
Each platform has chosen different tracks according to its own characteristics:
1. Government Group
Practitioners should feel fortunate to see government departments pay top-to-bottom attention to big data, so this group is the top priority.
Here are just a few representative ones:
Guizhou Big Data Exchange
Guizhou is the first to advocate big data, and has maintained a trend of prosperity
1) Pricing: agreement pricing, auction pricing, and collective pricing coexist
2) Service fee: 40% of the transaction income, the seller shall bear all
3) Transaction volume: "Cumulatively exceeded 100 million yuan" (from the official website)
4) Restriction: Adopt a membership system, "easy access and strict control", but do not allow individuals to purchase data
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Comment: Since it is difficult for me to become a member, I cannot observe the transaction situation, but as a pioneer, Guizhou Exchange has participated in many "firsts" and should win applause
Zhongguancun Shuhai Big Data Trading Platform
It is more representative and belongs to an ongoing and beneficial attempt
1) Mode: API (application programming interface) transaction
2) Positioning: "The platform itself does not store data or intercept any data, but only serves as a transaction channel"
3) Background: The establishment was initiated by the Zhongguancun Big Data Trading Industry Alliance
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Comments: Not passed after registration, site should be under construction
Shanghai Municipal Government Data Service Network
The home page is free from the serious style of government websites, and we can see the welcome changes in government departments
1) Data volume: 770 data packets (mainly free download in xls format), 73 data interfaces
2) Data sources: various government departments in Shanghai, the Bureau of Justice, the Bureau of Civil Affairs, etc.
3) Features: The "Geographic Information" column provides a visual display of data
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Comments: There are many directory data, and most of the data has a narrow application range, but it can be said to be a good start, analogous to data.gov
Changjiang Big Data Trading Center
1) Data volume: 350 data products (data package + API)
2) Features: display of big data technology and products; data requirements and technical solution requirements can be released
3) Data coverage: There are many categories, but there is no data under some categories
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评论：框架没问题，但总体感觉精品数据不多
已上线的其他交易中心在这里一并列出，但基本类型离不开上述四种：
北京市政务数据资源网、浙江省公共数据开放目录、武汉市政府公开数据服务网、武汉东湖大数据交易中心、江苏省大数据交易中心、华中数交所、哈尔滨数据交易中心、钱塘数据大数据交易中心、海南数据交易中心。
2.API组
让数据交易火起来的是一批民营企业，他们摸索出一种全新的模式——以API接口交易数据、按调用量收费，其可行性已被人民币选票证明
聚合数据
亿级收入、亿级融资(公开信息)，其他不必多说，称作数据流通行业的榜样应该并不过分
1)定位：以开发者常用的数据为主，如空气质量、车辆违章、NBA赛事等
2)模式：API接口
3)数据量：总接口维持在100上下
4)特点：单次调用价格很低，但总调用量大
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评论：聚合以经营自家数据为主，不是典型的平台类，但以自身的发展带动了整个行业
其他API接口平台
下列几家和聚合数据的定位、特点、数据量基本一致，各有特色，排名无先后
1)阿凡达数据
2)ShowAPI
3)HaoService
4)极速数据
API Store
百度旗下，背景雄厚
1)定位：服务开发者，涵盖开发、运营、推广等各阶段
2)模式：API接口为主
3)数据量：接口总数量1100(数据+服务)
4)特点：汇集了不少知名服务商
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评论：“为开发者提供最全面的API服务”，不作为单纯的数据交易市场
京东万象
总体来看与APIstore相似，但数据接口比例较大
1)数据量：接口约400
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3.淘宝组
数据交易能否走淘宝模式一直是争论的焦点，近期已有企业开始趟路，接受市场的检验
数粮
态度较开放，吸纳各类的交易商
1)定位：数据交易+大数据技术产品交易
2)模式：“接受各种交易模式”
3)数据量：5,000(数据+技术产品)
4)特点：数据源较广、质量也较高，但目前的大部分交易需要在平台外完成
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评论：值得一试的思路，能看出野心，但数粮刚起步，存在各种刚起步的问题
数据宝
贵州+政府背景+淘宝模式 = 足够的曝光率
1)模式：API交易
2)数据量：340个接口
3)特点：背景和资源充足，得到了政府高层的关注，目前在业内较活跃
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评论：“首个省部共建的大数据资产运营管理平台”，可以期待一下
4.技术组
这类企业以抓取技术起家，业务延伸到数据交易，是思路清晰的产品线拓展;
企业的原有用户群发展成为交易的卖方，有天然的优势。
数多多
背景为业内知名的八爪鱼采集器
1)模式：数据包下载、定制
2)数据量：10,000
3)特点：各类长尾数据，数据量大，上新较快，但质量参差不齐
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评论：依托八爪鱼有效带动了数据的增长，长尾路线的效果如何还有待检验
大海洋
背景为老牌的火车采集器
1)模式：数据包下载、定制
2)数据量：600
3)特点：和数多多背景类似，但有意识地控制数据的质和量，走精品路线
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评论：可以与数多多做对比观察，路线截然不同
发源地
主打SaaS云采集引擎
1)模式：数据包下载、定制
2)数据量：9,000
3)特点：数据需求方可以在平台上购买、定制或者自己动手采集数据
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评论：思路是将数据的采集、清洗和流通集中到一个平台，通过增值服务盈利，但面临数多多同样的问题——大部分属于长尾数据
5.综合组
此组压轴，虽然在最后介绍，但特点明显，同样值得关注
数据堂
数据圈不多的三板挂牌企业，知名度较高
1)定位：数据服务商
2)模式：API、数据包下载、定制/众包
3)数据量：180(API + 数据包)
4)特点：以出售自有数据为主，走精品路线，科研类数据较有特色
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评论：公司出道较早，有数据处理的技术实力，较全面，但并非典型的数据交易平台
优易数据
明星级阵容：周涛(首席科学家)、车品觉(研究院院长)
1)模式：数据包下载、API、定制
2)数据量：1,300(数据包为主)
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评论：“公司由国家信息中心发起”(百度百科)，具备了较理想的资源和阵容
通联数据商城
较全面的金融数据池
1)模式：API
2)数据量：1,300
3)特点：汇集了通联、恒生聚源、华通人等十余个品牌的数据，涵盖金融各领域
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评论：中国版的quandl.com，是通联在金融领域总体布局的一部分
三、后记
The lack of data circulation hinders the development of the big data market, and the immaturity of big data technology also leads to the lack of strong data demand. Every emerging industry will face such problems, and this is no exception. But we're seeing a group of companies in action, and it's them who keep pushing things forward. Good luck to them.
(Note: Since the transaction volume cannot be verified, no guesses are made in this article)
End.
From 36 Big Data (36dsj.com): Looking at the Flowers: The Status Quo of Domestic Big Data Trading Platforms (Autumn 2016)