【Published by】 CHINA ACADEMY OF INFORMATION AND COMMUNICATIONS TECHNOLOGY
【Compiled by】 CHINA ACADEMY OF INFORMATION AND COMMUNICATIONS TECHNOLOGY
【Published in】 2019.12
Abstract
This white paper is the fourth edition of Big Data White Paper released by China Academy of Information and Communications Technology (CAICT) following Big Data White Paper (2014), Big Data White Paper (2016), and Big Data White Paper (2018). Based on the first three editions, this white paper focuses on the progress and trends in various fields of big data over the past year, analyzes and summarizes the main challenges, and looks into the future of big data. In terms of technology, this white paper focuses on the latest big data technologies and the convergence trend in the past two years; in terms of industry, it places an emphasis on the development of big data products in China; in terms of data asset management (DAM), it introduces the latest development of the industry and the assets management tools, with a focus on the key issues of data assetization; in terms of security, it analyzes the security issues and technical tools from multiple perspectives.
Contents
I. Overview of Big Data Development Around the World. 1
1. Big Data Strategies Continue to Expand. 1
2. Underlying Technologies of Big Data Are Maturing. 2
3. Big Data Industry Is Growing Steadily. 3
4. Consolidation of Big Data Companies Is Accelerating. 5
5. Data Compliance Requirements Are Getting More Stringent. 6
II. Convergence Has Become an Important Feature of the Development of Big Data Technologies. 8
1. Convergence of Computational Power: Diversified Computational Power Improves Overall Efficiency. 8
2. Convergence of Stream Processing and Batch Processing: Most Cost-Effective Solution. 9
3. TA Convergence: Hybrid Transaction/Analysis Supports Instant Decision-Making. 10
4. Module Convergence: One-Stop Data Capability Reuse Platform.. 11
5. Cloud-Data Convergence: Cloudification Trend Lowers the Threshold of Technology Use. 12
6. Convergence of Big Data and AI: Deep and Multi-Dimensional Integration of Big Data and AI. 13
III. Big Data Industry Is Booming. 14
1. Policy Environment Is Getting Increasingly Favorable for the Development of Big Data Industry. 14
2. Local Big Data Authorities Were Successively Established. 18
3. The Level of Big Data Technology Products Continues to Improve. 23
4. Big Data Industry Applications Move Deeper. 25
IV. Data Assetization Is Advancing Steadily. 28
1. Data: From Resources to Assets. 28
2. The Theoretical Systems of DAM Are Still Developing. 29
3. Various Industries Have Actively Applied DAM. 31
4. DAM Tools Are Flourishing. 33
5. Data Assetization Faces Many Challenges. 35
V. Data Security Compliance Requirements Become More Stringent. 39
1. Data-Related Laws and Regulations Are Getting More Stringent and Standardized. 39
2. Data Security Technologies Facilitate the Landing of Big Data Compliance Requirements. 41
3. The Framework of Data Security Standards and Specifications Continues to Improve. 44
VI. Big Data Development Outlook 46
