1 Introduction to the use of Generative AI in Data Analytics

This book aims to show you how to utilize Generative AI to improve multi-faceted business activities such as Data Analytics. We will show you how to extract knowledge stored in the depths of neural networks and not fall victim to risks inherent to this technology. To excel in both tasks, you need to have in the back of your head what drives the responses you get to your prompts. Therefore, this chapter will provide a brief overview of Generative AI models, their underlying technology, and what are their main limitations. The point is not to give the readers encyclopedic knowledge of the technology but a deep enough understanding to demystify it and allow a more critical interpretation of its abilities.

1.1 Key features (or limitations) of Generative AI models

1.2 The role of Generative AI in Data Analytics

1.2.1 The complementarity of language models and other data analytics tools

1.2.2 The limitation of Generative AIs’ ability to automate and streamline data analytics processes

1.3 Getting Started with Generative AIs for Data Analytics

1.3.1 Web interface

1.3.2 Accessing and using the API and SDK

1.3.3 Examples of programmatic access to ChatGPT

1.3.4 Third-party integrations of ChatGPT

1.3.5 Best practices and tips for successful Generative AI implementation

1.4 Summary