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To use that familiar saying, I don’t produce data, I’m just a porter of data. This data porter is the first module of the data platform data integration. What are the names of porters In the process of product design, we often encounter various names for the same product. These names seem to refer to the same product. If we look closely, there seem to be some differences. Similar problems will also be encountered when designing data integration products. These same names are mainly data integration, data synchronization, and data acquisition. Sometimes you may also hear about data pipes, data transmission, etc. I searched for the difference through large models. Data integration refers to integrating different data sources, different data types and different formats of data together to form a unified data view or
data warehouse for subsequent analysis and processing. Data Austria WhatsApp Number integration usually involves multiple steps such as data extraction, conversion, cleaning and loading. It also needs to solve issues such as data format conversion, data quality issues and data security. Data synchronization It is to copy or transfer data from one data source to another data source to maintain data consistency in the two data sources. Data synchronization usually involves realtime or quasirealtime data transmission and replication, and can be used in scenarios such as data replication, backup, and disaster recovery in distributed systems. It seems that data integration focuses more on data integration and data processing, while data synchronization focuses more on data transmission and consistency. In the field of big data,

data collection and data integration are two closely related concepts, but their roles and purposes in the data processing process are different. Data collection is mainly the process of obtaining data from outside the system and inputting it into the system through tools or technologies. . During this process, the acquired data may require preprocessing such as cleaning and format conversion to facilitate subsequent data integration and use. Data integration is the process of logically or physically organically gathering data from different sources, different formats, and different properties to form a comprehensive and unified data view or data warehouse.
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