Oracle Analytics AI Assistant webinar

Introduction

Welcome to the Oracle Analytics AI Assistant webinar. In today’s session, we will discuss the features and benefits of the Oracle Analytics AI Assistant, including its rollout, usage, and the best practices for making your data AI Assistant-ready. This informative session will feature insights from the product strategy team, including myself, Benjamin Arnold, and Ja Fon, the Vice President of Product Management for Oracle Analytics.

Safe Harbor Statement

Before we dive deeper, we would like to remind everyone of the importance of the Safe Harbor statement regarding any forward-looking statements made during the webinar.

Overview of the Webinar

Benjamin started by addressing some questions from the audience, clarifying that the webinar is being recorded and will be available on YouTube later. He emphasized that a growing community of Oracle Analytics users is actively participating in discussions, events, and training is organized through the Oracle Analytic Community website.

The discussion then moved to the Oracle Data and AI Forum, providing attendees the opportunity to register their interest in attending.

Oracle Analytics AI Assistant Deep Dive

Now, let’s take a deep dive into the Oracle Analytics AI Assistant.

Ja Fon began by explaining that the AI Assistant was announced at Oracle Cloud World, and it functions with two modes: the out-of-the-box assistant managed 100% by Oracle and a future option allowing integration with external large language models (LLMs) such as OpenAI.

Key Features of the Oracle Analytics AI Assistant

Data Privacy: The out-of-the-box version keeps data private, ensuring it never leaves the customer's domain, providing a secure usage model.
Current Capabilities: The AI Assistant can interact with multiple datasets and supports querying questions in natural language, focusing on the data available in the workbook.
Future Integrations: Plans to extend the capabilities of the Assistant by offering support for external LLMs, focusing on how they can provide richer analytic capabilities.
User Experience: The Assistant is designed to enhance user interaction with data. Users can run complex queries simply by asking questions, making it an important tool for data analysis.

Best Practices to Enable the AI Assistant

To set the AI Assistant up successfully, consider the following:

Descriptive Metadata: Ensure your data's column names are descriptive to help the assistant understand queries effectively.
Using Synonyms: Utilize the synonym feature to enable the AI to respond accurately to various terminologies used within your organization.
Indexing: Carefully choose what data to index, focusing on the most frequently queried fields while avoiding low-value data points.

With these practices, users can create a robust interaction experience with the Assistant, enabling better data insights and decision-making.

Questions and Answers Session

The webinar concluded with an interactive Q&A session, where various questions about the AI Assistant's capabilities, such as multi-language support, mobile app integration, and specific industry use cases, were addressed.

Conclusion

In summary, the Oracle Analytics AI Assistant represents a significant advancement in analytics, offering enhanced user engagement and data interaction capabilities. Continuous community support and feedback will help shape its future development.

Keyword

Oracle Analytics
AI Assistant
Webinar
Data Privacy
User Experience
Best Practices
Synonyms
Multi-language Support
Large Language Models

FAQ

Q1: Is the AI Assistant available for users in languages other than English?
A: Currently, the Assistant officially supports only English, but it works in several other languages due to the capabilities of the language models to translate.

Q2: Can the AI Assistant create calculations using natural language?
A: Not yet, but the team is working toward enabling this feature in the future.

Q3: Will the Assistant be available for Oracle Analytics Server customers?
A: Yes, the Assistant will be supported under the "bring your own LLM" model.

Q4: How does the AI Assistant ensure data privacy?
A: Data processed through the out-of-the-box Assistant remains entirely within the customer’s domain and is not used for training external models.

Q5: What are the best practices for preparing data for the AI Assistant?
A: Descriptive naming conventions for columns, the use of synonyms, and indexing the most useful datasets help optimize the Assistant's functionality.