Oracle Analytics Cloud Features

Based on 162 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Reports interface for standard and self-service reports is intuitive and easy to use.

Based on 159 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Requires a minimal number of steps/clicks to answer business question.

Based on 152 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Offers a variety of attractive graph and chart formats.

Based on 123 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Score cards visually track KPI's.

Based on 153 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Provides business users an interface to easily design, refine and collaborate on their dashboards

Based on 150 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Using formulas based on existing data elements, users can create and calculate new field values.

Based on 150 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Business users have the ability to filter data in a report based on predefined or automodeled parameters.

Based on 138 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Users can drill down and explore data to discover new insights.

Based on 122 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Ability to search global data set to find and discover data.

Based on 133 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Ability for users to share data and reports they have built within the BI tool and outside the tool through other collaboration platforms.

Based on 122 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Tool automatically suggests data types, schemas and hierarchies.

Based on 119 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Analyze current and historical trends to make predictions about future events.

Based on 137 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Communicate complex information clearly and effectively through advanced graphical techniques.

Based on 104 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Ability to handle large, complex, and/or siloed data sets.

Based on 82 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Converts data formats of source data into the format required for the reporting system without mistakes.

Based on 85 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Ability to (re)structure data in a manner that allows extracting insights fast and accurate.

Based on 74 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Provides business users an interface to easily design and refine their dashboards and reports. (What You See Is What You Get)

Based on 64 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Application Programming Interface - Specification for how the application communicates with other software. API's typically enable integration of data, logic, objects, etc with other software applications.

Based on 58 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Ability to connect the analytics platform with a wide range of connector options for common data sources, including popular enterprise applications.

Based on 57 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Connects to enterprise data governance software, or provides integrated data governance features to avoid misuse of data

Based on 59 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Using formulas based on existing data elements, users can create and calculate new field values

Based on 59 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Business users have the ability to filter data in a report based on predefined or automodeled parameters.

Based on 59 Oracle Analytics Cloud reviews and verified by the G2 Product R&D team. Allows the user to combine data from multiple sources into a functioning dataset.

Allows users to generate text based on a text prompt. 50 reviewers of Oracle Analytics Cloud have provided feedback on this feature.

Condenses long documents or text into a brief summary. 51 reviewers of Oracle Analytics Cloud have provided feedback on this feature.

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Enables non-technical users to build dashboards through intuitive, drag-and-drop interfaces

Enables automated report generation and scheduled delivery to stakeholders

Allows dashboards and analytics to be embedded into external apps with branding flexibility

Supports integration with major data sources like cloud data warehouses, SQL/NoSQL databases, and SaaS applications

Efficiently processes large datasets with minimal lag and ensures high performance under load

Maintains performance and uptime during high traffic from multiple users or teams

Supports semantic data layers, role-based access controls, and metadata governance

Integrates with Jupyter, Python, or R for custom analytics and modeling

Provides native tools for statistical analysis, forecasting, and trend prediction

Uses AI to generate textual summaries, key takeaways, and data stories from dashboards

Allows users to query data and build reports using conversational or plain language

Detects and notifies users about KPI anomalies or significant metric changes in real time

Recommends next questions, analyses, or exploration paths using autonomous AI agents

Learns from historical user interactions to improve and personalize query results over time

Tailors dashboard views and suggestions based on user roles, access levels, and past behavior

Supports AI-driven exploration via prompts or multi-turn conversations for iterative querying

Supports deployment across multiple environments or cloud platforms with consistent configuration management

Provides APIs and SDKs for seamless integration with orchestration, governance, and custom data tools

Allows querying and joining data across multiple warehouses and lakes without requiring data replication

Automatically adapts to schema or metadata changes in connected data sources while maintaining consistency

Enables users to create derived or calculated metrics based on governed data definitions

Provides built-in support for time-based calculations such as YoY, MoM, and rolling averages

Enhances performance by using intelligent caching, precomputation, and acceleration techniques

Automatically tunes and optimizes queries based on data size, frequency, and usage patterns

Provides visibility and control over how AI systems or automated agents interact with the semantic layer

Tracks how governed metrics and datasets are used in AI/ML training to ensure transparency, compliance, and clear data traceability

Provides version control for semantic models and metrics, with change tracking, rollback, and impact analysis to see how updates affect downstream data or reports

Allows users or AI assistants to explore and query metrics through natural language prompts

Enables AI and machine learning systems to directly consume standardized, governed metrics and logic

Suggests relevant metrics, joins, or insights based on context and historical usage patterns

Enables autonomous AI agents to compose, execute, and refine analytical queries via the semantic layer

Provides semantic context graphs that help AI agents understand data relationships and business logic

Allows semantic agents to trigger automated actions such as data refreshes, alerts, or report generation