1. Big Data, Data Assets, Digital Economy
Big data is the foundation and root of development in the digital economy era. Data assets and the digital economy are derivative foundational concepts based on big data.
Big Data:Refers to a massive, diverse collection of data that is processed quickly and has low value density. — It is the raw state of fundamental resources, which needs to be processed and analyzed through technology and methods to fully realize its value.
Data Assets:Refers to data resources that an enterprise or organization owns or controls, which can bring economic benefits.— It is the value form generated from processing the big data that they own or control, typically transforming data assets into products or services targeted at specific scenarios.
Digital Economy:Refers to a new economic form based on digital technology, with data as the key production factor and digital transformation as the core driving force, encompassing both digital industrialization and industrial digitization.— It is a classification of social economic forms under macro properties, including all upstream and downstream industries related to digital technology.
2. Cloud Computing, Edge Computing, Data Internet
Cloud Computing:Provides powerful computing resources and storage capabilities through distributed computing and storage technologies, serving as the foundational support for processing big data.— It processes large amounts of data in the cloud to achieve efficient processing and services.
Edge Computing:Refers to an open platform that integrates network, computing, storage, and application core capabilities, providing services close to the source of the object or data. — It processes data at the network edge, providing real-time capabilities, reducing data transmission latency and bandwidth consumption, in contrast to cloud computing.
Data Internet:Integrates and relates big data that is dispersed across different systems, platforms, and fields, emphasizing the interconnection between high-dimensional data.— It breaks the data silo effect, achieving cross-service data integration.
3. Artificial Intelligence, Privacy Computing, Blockchain, Federated Learning
Artificial Intelligence:Refers to the technology and science that simulates human intelligence through training, learning, and analyzing vast amounts of data, including capabilities like learning, reasoning, decision-making, language understanding, and visual perception.
Privacy Computing:Refers to a technical system that achieves data computation and analysis while protecting data privacy. — It ensures privacy and security during data usage, (during the transmission and aggregation processes of the same model).
Blockchain:Ensures the immutability and traceability of data through cryptographic techniques. — It ensures the authenticity and security of various actions (such as data flow and technical processing) during the flow of data.
Federated Learning:Refers to collaborative training of a machine learning model among multiple participants without sharing raw data. — It ensures privacy and security during data usage, (among multiple entities using the same model).
[Editor’s Note]
If we consider big data in a single carrier (such as a single platform or system) as a small unit, then:
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The interconnectivity of multiple units forms the Data Internet;
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Combinations formed by unit associations have application value, thus forming data assets;
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The process of forming data assets from units distinguishes between cloud computing and edge computing based on their storage and processing methods;
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Artificial intelligence belongs to big data technology, used to mine data patterns, trends, etc., to generate practical applications;
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Blockchain, privacy computing, and federated learning also belong to big data technology, mainly used to protect data privacy and security during flow and processing.
(This article is from Data Observer)
