1. 对于“大数据”（Big data）研究机构Gartner给出了这样的定义：“大数据”是需要新处理模式才能具有更强的决策力、洞察发现力和流程优化能力来适应海量、高增长率和多样化的信息资产。
2. 麦肯锡全球研究所给出的定义是：一种规模大到在获取、存储、管理、分析方面大大超出了传统数据库软件工具能力范围的数据集合，具有海量的数据规模、快速的数据流转、多样的数据类型和价值密度低四大特征。
3. 大数据的 strategic significance lies not in possessing vast amounts of data information, but in professional processing of meaningful data. In other words, if big data is compared to an industry, then the key to profitability in this industry lies in improving the data's "processing capability" to add value to the data.
4. Technically, big data is inseparable from cloud computing, which provides the distributed infrastructure necessary for handling massive amounts of data. The unique feature of big data is its distributed data mining, which relies on cloud computing's distributed processing, distributed databases, cloud storage, and virtualization technology.
5. The resourceification of data refers to the recognition of big data as a crucial strategic resource for enterprises and society, becoming a new focus of competition. Therefore, enterprises must develop big data marketing strategies in advance to seize market opportunities.
6. The deep integration of big data with cloud computing: Big data cannot do without cloud computing, which provides the flexible and scalable infrastructure necessary for big data. Since 2013, big data technology has begun to integrate closely with cloud computing, and it is expected that their relationship will become even closer in the future.
7. Breakthroughs in scientific theories: With the rapid development of big data, similar to computers and the internet, big data may well trigger a new technological revolution. Emerging technologies such as data mining, machine learning, and artificial intelligence may change many algorithms and foundational theories in the data world, leading to scientific and technological breakthroughs.
8. The establishment of data science and data alliances: In the future, data science will become a separate discipline recognized by an increasing number of people. Universities will establish specialized data science majors, and this will also give rise to a new breed of job positions. Concurrently, based on the data platform, cross-disciplinary data sharing platforms will be established.
9. The rampant data breaches: In the coming years, the growth rate of data breaches may reach 100% unless data security is guaranteed at the source. It is imperative that every Fortune 500 company be prepared for data breaches and reassess their current security definitions.
10. Data management as a core competitive advantage: Data management will directly impact financial performance and become a core competency. As the concept of "data assets as core assets" takes root, enterprises will have a clearer definition of data management and treat it as a competitive advantage for sustainable development.
11. Data quality is key to the success of Business Intelligence (BI): Enterprises that adopt self-service BI tools for big data processing will stand out. One challenge they face is the vast amount of low-quality data from various data sources. To succeed, businesses need to understand the discrepancy between raw data and data analysis to eliminate poor-quality data and make better decisions through BI.
12. The data ecosystem becomes more complex: The world of big data is not just a single, massive computer network but an ecosystem constructed by numerous interconnected components and participants, including device providers, infrastructure providers, network service providers, network access service providers, data service enablers, data service providers, contact service providers, and data service retailers.
