Learn About AI-powered Insights With Oracle Analytics Cloud AI Assistant
Oracle Analytics Cloud AI Assistant provides a conversational analytics workflow that enables business users to instantly generate insights from their data with full data security and governance, and without coding.
Data is the most valuable commodity of the 21st century, and business success relies on making data-driven decisions. However, traditional analytics workflows are often a limiting factor in enabling these data-driven decisions. Business analysts often struggle to develop analytical dashboards at the pace and scale required by business users. Business users typically lack the necessary understanding of data models and dashboarding tools to build reports on their own. Executives struggle to get answers to their mission-critical questions in an accurate and timely manner. Oracle Analytics Cloud addresses these challenges with the AI Assistant.
Oracle Analytics Cloud AI Assistant leverages a large language model to transform your analytics ecosystem into one centered around asking the questions that drive businesses forward. All users, from data analysts to business users to executives, can have a conversation with their data and instantly generate business insight. Analytics is now accessible to everyone, with AI-driven insights delivered within the Oracle Analytics Cloud platform with full data security and with no coding required.
- Connect to a data source
- Create a dataset
- Enable the Oracle Analytics Cloud AI Assistant
- Create visualizations conversationally by using the Oracle Analytics Cloud AI Assistant
- Understand AI Assistant best practices
By leveraging a large language model, the AI Assistant transforms the analytics ecosystem into one centered around asking questions that drive businesses forward, ultimately empowering business analysts to deliver more meaningful insights more efficiently.
Before You Begin
Before you begin, make sure you have access to an Oracle Analytics Cloud instance.
For information about deploying Oracle Analytics Cloud, refer to Getting Started with Oracle Analytics Cloud.
This playbook also leverages Oracle Autonomous AI Database. Production deployments include additional data platform tools such as data integration. For more information on the other data platform components:
Architecture
The following high-level architecture shows the stages of the data lifecycle.
The specific tools used in each stage of the data lifecycle will vary depending on the data types and other requirements:
- Data is ingested from different data sources using integration tools
- Data is stored in the data persistence layer
- Additional machine learning (ML), artificial intelligence (AI), and other data science tools are applied to the data
- Oracle Analytics Cloud is then ready to provide business insight and value via the generative AI Assistant
The following diagram illustrates the architecture:
oac-ai-assist-arch-basic-oracle.zip
Within the context of the above data platform, the analytics workflow for the AI Assistant is shown below. A connection is made to a data source, which in this example is the Oracle Autonomous AI Lakehouse. After this connection is created, a dataset or semantic model is defined in Oracle Analytics Cloud. A workbook is created using this dataset or semantic model, and finally the AI Assistant is available within the workbook.
