数据与计算发展前沿 ›› 2019, Vol. 1 ›› Issue (1): 116-126.

doi: 10.11871/jfdc.issn.2096.742X.2019.01.012

所属专题： “数据与计算平台”专刊

• • 上一篇    

数据中台技术相关进展及发展趋势

苏萌,贾喜顺,杜晓梦,高体伟   

  1. 北京百分点信息科技有限公司,北京 100089
  • 收稿日期:2019-08-15 出版日期:2019-01-20 发布日期:2019-12-26
  • 作者简介:苏萌,1973年生,百分点集团董事长兼CEO,北京大学光华管理学院研究教授、博导,北京大学国家发展研究院特聘教授,国家“千人计划”专家。主要研究方向为大数据建模、政府决策大数据、推荐引擎、数据智能分析预测。
    本文承担工作为：框架的整体结构设计、研究指导。
    Su Meng, born in 1973, President/CEO of Beijing Percent Group. Research professor and doctoral advisor of Guanghua School of Management, Peking University. Distinguished Professor of National School of Development at Peking University. Expert of National “Thousand Talents Program”. His main research interests are big data modeling, big data for government decision making, online recommendation engine and intelligent data analysis and prediction.
    Undertaking the following tasks in this paper: overall research framework design and research supervisor.
    E-mail: meng.su@percent.cn.|贾喜顺,1982年生,百分点平台业务部负责人,在读研究生,主要研究方向为大数据平台、数据治理、数据中台。
    本文承担工作为：数据中台技术框架分析与展开讨论。
    Jia Xishun, born in 1982, Head of Platform Business Group of Beijing Percent Group. He is currently a master student study on big data platform, data governance and mid-end technologies.
    Undertaking the following tasks in this paper: taking part in the discussion about mid-end framework analysis.
    E-mail：xishun.jia@percent.cn|杜晓梦,1984年生,百分点企业业务事业部总经理,首席模型科学家,2018年北京市“科技新星”,北京大学营销模型专业博士,主要研究方向为跨学科数据科学建模、消费者行为预测、归因模型、流失预警模型、社会网络分析。
    本文承担工作为：文献调研与回顾,企业实践案例分析。
    Du Xiaomeng(Corresponding Author), born in 1984, General manager of Enterprise Business Group and Chief Data Scientist of Beijing Percent Group. Nominated “Beijing Technical New Star” in 2018. Ph. D in Marketing Models, Peking University. Her main research interests include big data modeling, data science in different domains, consumer behavior prediction, attribution model, customer churn model and social network analysis.
    Undertaking the following tasks in this paper: Literature review and industrial case studies.
    E-mail: xiaomeng.du@percent.cn|高体伟,1973年生,百分点集团高级副总裁,华南理工大学软件工程硕士,主要研究方向为云计算、政府决策大数据。
    本文承担工作为：政府案例实践分析,数据中台未来发展趋势讨论。
    Gao Tiwei, born in 1973, is the Senior Vice President of Beijing Percent Group. He obtained his software engineering master degree from South China University of Technology. His research interests are cloud computing and big data for government decision making.
    Undertaking the following tasks in this paper: taking part in the discussion about mid-end trends of future.
    E-mail：tiwei.gao@percent.cn
  • 基金资助:
    国家自然科学基金重点项目“基于全网数据的消费者行为与偏好研究”(71332006)

Research on the Recent Development and Future Trend of Data Mid-End Technology

Meng Su,Xishun Jia,Xiaomeng Du,Tiwei Gao   

  1. Beijing PERCENT Information Technology Co., Ltd., Beijing 100089, China
  • Received:2019-08-15 Online:2019-01-20 Published:2019-12-26

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摘要：

【目的】本文主要就数据中台相关研究背景、技术架构和关键技术以及在行业中的落地应用展开介绍,并结合技术发展趋势提出未来研究和应用发展方向。【方法】本文综述了数据中台相关领域的国内外研究,并提出数据中台通用技术架构,分别对大数据技术平台、数据资产管理平台、数据分析挖掘平台和统一服务总线的核心技术和功能进行了展开讨论。【结果】基于本文提出的数据中台的相关技术框架,数据中台在相关行业已经得到初步应用和实践,其中互联网、金融和政府等行业走在前沿。【结论】数据中台的相关技术会越来越向自动化、智能化方向发展,其支撑的上层业务应用将会在一系列相关技术突破的推动下在各行业形成爆发式的发展。

关键词: 数据中台, 数据治理, 数据仓库, 人工智能, 数据服务, 数据应用

Abstract:

[Objective] The article mainly introduces the research background, technical framework and key technologies related to data mid-end, as well as its application in the industry, and proposes the future research and application development direction based on the technology development trend in the end. [Methods] In the research background part, the existing researches on data mid-end and related fields in China and other countries are summarized. The chapter on technical architecture synthesizes the research results at home and abroad by sniffing application in various industries, and puts forwards the general architecture of data min-end. The industry application section introduces the application situation and value of data mid-end in the Internet, traditional industries and government departments. The future trend and prospect part discusses the future development of data mid-end based on relevant technologies. [Results] Based on the relevant technical framework in the article, data mid-end has been preliminarily applied and used in relevant industries, with Internet, finance, government affairs and other industries leading the trend. [Conclusion] The relevant technologies of data mid-end will be developed towards much more automatic and intelligent. The upper business applications supported by data mid-end will register explosive growth in various industries, attributed to a series of relevant technological breakthroughs.

Key words: data mid-end, data governance, data warehouse, artificial intelligence, data service, data application