Gartner recently published an analysis of the short and mid-term implications of ChatGPT, a large language model built on GPT. This language model is capable of performing complex language-related tasks and is becoming an increasingly popular tool for data and analytics professionals. While ChatGPT is well-suited for many of these tasks, there are potential risks and limitations to be aware of.
ChatGPT’s evolution has been relatively rapid, and it is expected that this trend will continue in the coming year. New, complementary technologies are emerging that can further enhance the capabilities of the platform. For example, language models can help data engineers generate data ingestion and transformation scripts, configuration templates, and complex SQL queries. Data analysts could also use them to write DAX code for applications like PowerBI, while data scientists could use them to review Python code for machine learning related functions.
Despite these useful features, caution should be taken when using ChatGPT or similar language models in data and analytics tasks. Because these models often ingest confidential or sensitive information, it is important that data and analytics practitioners first ensure that the language model service provider is properly handling the data. In addition, generated code or other output should be monitored for accuracy, and practitioners should take the lead in informing risk and compliance policies with regard to generative AI at the business.
OpenAI and Microsoft Azure OpenAI Services are two of the most prominent providers of ChatGPT and language model services. OpenAI has been at the forefront of the development and commercialization of ChatGPT, and has released an open source API for developers and businesses to build upon the platform. Microsoft Azure OpenAI Services are part of Microsoft’s Cloud AI platform and give businesses the ability to deploy and manage ChatGPT models, with the aim of automating the development of artificial intelligence applications.
When leveraging the powerful capabilities of ChatGPT and similar technologies, data and analytics practitioners have the opportunity to make a real impact. If used responsibly, this technology can make complex tasks much easier for developers, analysts, and data scientists, all while minimizing the associated risks.
