Google Cloud Next 2024 Review Part 3: Generative AI Using Enterprise Data

To effectively utilize the data enterprises hold with Generative AI, an approach tailored to the nature of the data is necessary. Data is classified into Structured, Semi-structured, and Unstructured data according to its form.

Everyday usage patterns mainly involve copying and pasting small amounts of unstructured data, but enterprises must handle large volumes of all data types. Therefore, rather than a simple input method, a structure capable of efficiently processing schemas and large-scale data is essential.

According to data volatility, data is divided into Static data and Dynamic data. Generative AI is advantageous for processing trained static data, but for dynamic data containing up-to-date information, accuracy must be secured through real-time integration with external storage.

In enterprise environments, AI is used for important decision-making such as marketing strategy, so high accuracy is required for dynamic data. To achieve this, enterprises must effectively integrate their data storage with Generative AI applications to keep them up to date.