What are the different components of OAC?

Oracle Analytics Cloud (OAC) consists of the following components:


Data Visualization: This component allows users to create interactive and visually appealing data visualizations, including charts, graphs, maps, and dashboards. It provides a user-friendly interface for exploring and analyzing data visually.


Data Preparation: Data preparation tools in OAC assist users in cleaning, transforming, and enriching their data before analysis. These tools help ensure that the data is accurate and ready for use in visualizations and analyses.


Data Flows: Data flows enable users to create ETL (Extract, Transform, Load) processes to integrate and transform data from multiple sources. Users can design data flows visually, allowing for complex data integration tasks without writing code.


Data Exploration: This component provides capabilities for ad-hoc data exploration, allowing users to delve into the data, identify patterns, and generate insights. It supports features like filtering, aggregations, and drill-downs for detailed analysis.


Advanced Analytics: OAC includes advanced analytics capabilities such as predictive analytics and machine learning. Users can build and deploy machine learning models, perform statistical analyses, and gain deeper insights into their data using these tools.


Narrative Reporting: Narrative reporting allows users to create reports that combine data visualizations with textual explanations. Users can annotate visualizations and dashboards with narratives to provide context and insights, enhancing the understanding of the data.


Mobile: OAC provides mobile capabilities, allowing users to access their analytics content on mobile devices. This ensures that stakeholders can stay informed and make data-driven decisions on the go.


Collaboration: Collaboration features enable users to share reports, dashboards, and insights with colleagues. Users can collaborate in real-time, discuss findings, and work together to analyze data effectively.


Administration and Security: OAC includes administrative tools for managing users, security settings, and system configurations. It allows administrators to control access, ensure data security, and monitor usage within the platform.


Integration: OAC integrates with various data sources, including cloud databases, on-premises databases, and other Oracle Cloud services. Integration capabilities enable users to consolidate data from diverse sources for comprehensive analysis.



OAC also offers a number of additional components, such as:



Data modeling: The data modeling component allows users to create and manage semantic models. This helps to ensure that users have a consistent view of their data, regardless of the source system.

Machine learning: The machine learning component integrates with Oracle Cloud Infrastructure (OCI) Machine Learning to provide users with the ability to build and deploy machine learning models. This allows users to automate their analytics processes and gain deeper insights from their data.

Natural language processing: The natural language processing (NLP) component allows users to interact with OAC using natural language. This includes features such as natural language querying, natural language generation, and natural language search.

Mobile access: OAC provides mobile apps for iOS and Android devices, which allows users to access their analytics data and dashboards on the go.

Overall, OAC offers a comprehensive set of components that can be used to meet the analytics needs of organizations of all sizes