Generative AI is the new wave of the AI revolution in 2024. Moving ahead of Chat GPT and numerous AI chatbot technology; Artificial intelligence has been explored to the zenith. Cognizant unfolded a recent statistic stating about 96% accepted that GenAI will democratize technology access.
Data engineering acts as a massive pivot to the process of data collection, making it convenient for data analysts, executives, and scientists to reliably analyze the current pool of data. Understanding generative artificial intelligence and its congruence with data engineering regime is a big gameplay to master.
Of late, data engineering task automation has been hugely powered by Generative AI in diverse forms. Data augmentation, natural language processing, data modeling, schema, and much more have been facilitated by Gen AI in data engineering. This is a freeway that allows data engineers in data management, data pipeline development, data extraction, data transformation, data architecture modernization, and much more.
This in no sense means that humans are deemed useless. It is indispensable to have a coherent balance between human and data engineering task automation. It helps in building trust, creating an emotional connection, understanding context, and leading to a more ethical platform.
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