Level: Beginner
【Presenter】
Naohiro Masukawa, JMP Japan Division, SAS Institute Japan Co., Ltd.
[Presentation summary]
Since the end of last year, generative AI such as ChatGPT has been on the rise, and it is still a hot topic of conversation as an event that will greatly change our lives and work. Similarly, in data analysis, there is a strong possibility that this will result in a paradigm shift that will significantly change the approach itself.
What made me feel this particularly strongly was the release of ChatGPT's official plug-in ``Advanced Data Analysis.'' With "Advanced Data Analysis," you can easily perform data summarization, visualization, and statistical analysis by commanding what you want to analyze in natural sentences, which lowers the barrier to analysis and greatly improves the efficiency of analysis work. You can expect it.
JMP has a feature that allows analysts to proceed with exploratory analysis while interacting with data, but is this feature really the point of using it for generative AI? Are there any other points that give it an advantage over generative AI? Regarding these points, obtain the latest information on generation AI at the time of publication and state your own thoughts without relying on JMP.
*Note: This presentation expresses the presenter's personal opinion and does not express our company's official opinion.
[Presenter profile]
Mainly responsible for technical work at JMP Japan Division. In recent years, he has been introducing the various functions and features of JMP through webinar lecturers, video creation, and blog writing.
*No distributed materials
