1.1.2 Challenges of
data flow Data flow is a technical term used to abstract and summarize data exchange and transfer behavior between various data systems. If you design a good data platform, you will mainly face the following challenges:
Reliability
Enterprises often have many data systems, and data flow is responsible for connecting these complex data systems to each other, so the stability of the data system will directly affect the connection between these systems. reliability of the data flow.
The network instability of the data stream itself, the problem of disk damage, software bugs, and human operation errors also directly affect the reliability of the data stream.
Data buffering: In the process of
data transmission, complex and time-consuming operations and conversions are often required, and factors such as the processing capacity of the system that ultimately consumes or stores these data will lead to an imbalance in the production and consumption capabilities of data streams, which requires data Streams have the ability to buffer data to address the imbalance between production and consumption capabilities.
Fault Tolerance
Data production systems are diverse, and the quality of the data produced is also uneven. In order to ensure the normal and stable operation of the data stream connecting those data systems with poor data quality, the data stream must be designed with strong fault tolerance.
Fast access
With the development of services and the evolution of requirements, there are constantly new data access requirements. How to quickly access new data in a data stream is a huge challenge.
Compatibility
Data systems have their own architecture evolution plans. For example, the data production system has changed and adjusted the format or protocol of the produced data, but at this time, the data consumption or storage system has not been able to adjust the new changes in time due to various reasons. Make a corresponding response. At this time, in order to ensure that the systems at both ends of the data stream can work normally, the data stream itself needs to be capable of being compatible with this change.
Security The data in the
data stream sometimes involves privacy and business secrets of the enterprise. The data stream needs to ensure the security of the data during transmission.
For regional computer rooms with strict legal requirements for data security, system security is particularly important.
Quick response
With the development of the business, there are constantly new data flow requirements and the need to optimize and adjust the existing data flow. How to quickly create and optimize an existing data stream is also a huge challenge.
data flow Data flow is a technical term used to abstract and summarize data exchange and transfer behavior between various data systems. If you design a good data platform, you will mainly face the following challenges:
Reliability
Enterprises often have many data systems, and data flow is responsible for connecting these complex data systems to each other, so the stability of the data system will directly affect the connection between these systems. reliability of the data flow.
The network instability of the data stream itself, the problem of disk damage, software bugs, and human operation errors also directly affect the reliability of the data stream.
Data buffering: In the process of
data transmission, complex and time-consuming operations and conversions are often required, and factors such as the processing capacity of the system that ultimately consumes or stores these data will lead to an imbalance in the production and consumption capabilities of data streams, which requires data Streams have the ability to buffer data to address the imbalance between production and consumption capabilities.
Fault Tolerance
Data production systems are diverse, and the quality of the data produced is also uneven. In order to ensure the normal and stable operation of the data stream connecting those data systems with poor data quality, the data stream must be designed with strong fault tolerance.
Fast access
With the development of services and the evolution of requirements, there are constantly new data access requirements. How to quickly access new data in a data stream is a huge challenge.
Compatibility
Data systems have their own architecture evolution plans. For example, the data production system has changed and adjusted the format or protocol of the produced data, but at this time, the data consumption or storage system has not been able to adjust the new changes in time due to various reasons. Make a corresponding response. At this time, in order to ensure that the systems at both ends of the data stream can work normally, the data stream itself needs to be capable of being compatible with this change.
Security The data in the
data stream sometimes involves privacy and business secrets of the enterprise. The data stream needs to ensure the security of the data during transmission.
For regional computer rooms with strict legal requirements for data security, system security is particularly important.
Quick response
With the development of the business, there are constantly new data flow requirements and the need to optimize and adjust the existing data flow. How to quickly create and optimize an existing data stream is also a huge challenge.