How generative artificial intelligence helps optimize data engineering

For enterprises, data engineering is an important method to provide direction for product development by extracting user feedback. With the emergence of generative artificial intelligence, many companies are trying to use it to optimize data engineering more deeply to enhance the core competitiveness of their products. Next, let’s learn how generative AI can help optimize data engineering

Assist in data processing: Through training, engineers can use generative artificial intelligence to classify and organize complex data, and regularly clean up useless data to reduce storage pressure. In this way, the overall data quality can be improved and more accurate data services can be provided for subsequent decision-making.

Code conversion: There are many common programming languages ​​at present. When migrating projects, it is often necessary to perform code conversion on different programming languages. This process is very time-consuming and labor-intensive, and the accuracy is erratic, which is very likely to affect the normal operation after migration. Generative artificial intelligence can assist in faster code conversion and reduce errors during the translation process.

Code generation: Through training, generative artificial intelligence can generate specified code content according to the requirements of engineers, improve the efficiency of writing code, and reduce the error rate of the underlying code. During this process, engineers can also perform annotation and more training based on the generated content to improve the final quality

Testing: Generative artificial intelligence can more efficiently test the performance of all aspects of the product according to specific requirements. At the same time, it can also help the product make subsequent adjustments and reduce the time spent on retrieval and modification. In addition, engineers can also use it to build richer test scenarios, conduct more visual operations on detailed functions, and improve the final value.

The continuous development of generative artificial intelligence will surely lead data engineering to a more efficient and intelligent path, improving the overall level of the industry and society.

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