?Recently, Astera COO, Jay Mishra, had a conversation with Tobias Macey from Data Engineering Podcast on the impact of Generative AI on ETL pipelines. During this discussion we were able to cover a lot of ground, but there were some standout takeaways.??
Here are 5 ways generative AI is impacting data management:??
- Data Ingestion: Generative AI has transformed the way unstructured data can get extracted. While structured data extraction with Generative AI still has limitations, it will be fascinating to see what the future holds.?
- Data Transformations: Data engineers have begun using AI to generate code for transformations and to maintain data quality.?
- Schema Mapping: You can harness the power of AI to analyze field context and meaning in extracted data. AI then intelligently establishes connections, enhancing accuracy and efficiency in mapping tasks.?
- Overall Automation: AI has made the biggest impact here as it allows you to look at repetitive tasks in the entire framework and development and use AI to automate it.?
- Usability and User Experience: User experience has improved significantly allowing for non-technical users to explore data in ways they couldn’t before. Many solutions now feature a chatbot that can be used with ease to get remedies to data problems being faced. For example, in Astera’s Data Prep, you can converse with the Chatbot in English and give instructions on what you need done with your data. The feature’s AI then provides the user with the right script to perform the function.?
