The Oracle Analytics platform is a cloud-native service that provides the capabilities required to address the entire analytics process from data ingestion and modeling, through data preparation and enrichment, to visualization and collaboration without compromising security and governance. Embedded machine learning and natural language processing technologies help increase productivity and build an analytics-driven culture in organizations. Start on-premises or in the cloud—Oracle Analytics supports a hybrid deployment strategy, providing flexible paths to the cloud.
Visually explore data to create and share compelling stories using Oracle Analytics. Discover the signals in data that can turn complex relationships into engaging, meaningful, and easy to understand communications.
Accelerate the analytics process and make decisions with actionable information. A code-free drag-and-drop interface enables anyone in the organization to build interactive data visualizations without specialized skills or programming
Unify data across the organization and from multiple data sources for a complete and consistent view. Oracle Analytics offers more than 35 out-of-the-box native data connection choices, including JDBC (Java Database Connectivity). Securely create, manage, and share data connections with individuals, teams, or the entire organization. Access data wherever it is located: public cloud, private cloud, on-premises, data lakes, databases, or personal datasets, such as spreadsheets or text-based extracts.
Provide a scalable, single view of all data for analysis. Ensure trusted and consistent information across the enterprise with a business representation of data using a shared semantic model without compromising governance. Users access data through non-technical, business terms, predefined hierarchies, consistent calculations, and metrics. Create seamless views across data sources and explore them using native queries that deliver high performance. Easily configure the balance of live and cached connections to ensure high-performance data access.
Use self-service data preparation to ingest, profile, repair, and extend datasets, local or remote, greatly saving time and reducing errors. Data quality insights provide a quick view of data to identify anomalies and help with corrections. The custom reference knowledge feature enables Oracle Analytics to identify more business-specific information and make relevant data enrichment recommendations. Build visual dataflows to transform, merge, and enrich data and save results in Oracle Analytics storage, a connected relational database, or Oracle Essbase.
With the volume, variety, and sources of data constantly growing, machine learning (ML) helps users discover unseen patterns or insights from data. ML built into Oracle Analytics removes human bias and enables users to easily interpret possible outcomes and opportunities. Everyone—from clickers to coders—can use embedded ML to build custom, business-specific models for better decision-making. Business users do not need special technical or programming skills to use ML. In addition, data scientists, engineers, and developers can accelerate model building, training, and publishing by using the Oracle Autonomous Database Python environment as a high-performance computing platform.
Evolving methods of working are demanding more secure data analytics systems. With Oracle Analytics, the semantic layer and data model ensure that everyone uses a common set of curated data and definitions, thereby eliminating inconsistencies. Application and role-based security specify who is authorized to access what. Data-level security enables fine-grained access controls while ensuring that all stakeholders use the same data irrespective of their personalized view and level of access. Plus, native integration with federated identity management systems enables single sign-on (SSO) across applications.
Stay connected with automated delivery of analytics and ongoing monitoring of business performance from anywhere at any time. The Oracle Mobile app learns from each person’s own patterns and data interests to deliver intelligent recommendations for further analyses or data exploration. Use natural language to query data verbally or use search-like patterns in 28 languages. Receive alerts in real time based on different triggers such as when new data or reports become available, a threshold in a metric is reached, or arriving at a specific GPS location.
To ensure predictable costs, Oracle charges only for consumption regardless of the services, features, or roles used.
Oracle Analytics offers several deployment options:
“The capabilities of Oracle Analytics Cloud are wonderful.”
—Risk Management Officer, Finance Industry
“Strong and intuitive data visualization options and solid metadata components.”
—BI Developer in the Healthcare Industry
“Oracle Analytics Cloud provides best of both worlds in governed and ungoverned data.”
—Director, Enterprise Data Services in the Government Industry
Oracle Analytics empowers business users, data engineers, and data scientists to access and process data, evaluate predictions, and make quick, accurate decisions. Oracle Analytics addresses the entire analytics process, including data ingestion, preparation and enrichment, and visualization and collaboration. Machine learning (ML) is embedded throughout the platform to help organizations go beyond being data-driven to become analytics-driven.
Oracle Analytics Cloud is built on Oracle’s next generation cloud infrastructure and is an Oracle-managed native cloud service that can be deployed with a compute size of between 2 and 52 OCPUs depending on the analytic workloads. Analytics Cloud offers the flexibility to scale up and scale down Analytics Cloud environments. When there is no need to access a specific Analytics Cloud instance, it can simply be paused to reduce costs.On-premises
Oracle Analytics Server is customer-managed and deployed at your data center. Analytics Server can also be hosted in Oracle or non-Oracle cloud infrastructure, such as Microsoft Azure.
Accelerates the deployment of customer-managed Oracle Analytics Servers hosted on Oracle Cloud Infrastructure (OCI). Retain full control of your Analytics Server instance. Gain freedom from customer-owned server hardware, maintenance, and administration.
Oracle Analytics has more than 35 built-in native connectors to Oracle and non-Oracle sources, including for other cloud providers, such as Azure and Google. Connect your social feeds, Internet of Things (IoT) sources, and data lakes from popular data sources, including Snowflake, Google Analytics, Amazon Redshift, Google BigQuery, Microsoft SQL Server, and more.Direct query and data caching
Oracle Analytics platform provides both direct query and caching options. Direct query enables data to be ingested into the analytics layer directly from the data source itself at query time. Choose a custom balance between direct query and caching depending on the analytics use case. Analytics queries are automatically optimized for each data source for best performance.
An in-memory engine built into Oracle Analytics boosts the performance of slow or legacy data sources. Boosting slow systems means frequently run query data is cached and optimized for analytics, which then provides high-performance consistently to users. Once data is cached, modern analytics capabilities, such as Auto Insights and machine learning, can easily be run on that cached data. This extends legacy data management systems that are missing modern capabilities.
Develop and deliver trusted and governed semantic models to ensure a consistent view of business-critical data. Map complex data into familiar and consistent business terms. Design an optimized, fine-tuned query for execution.Self-service modeling
Users can directly join two or more tables and control the relationship—for example, inner or outer joins—through self-service. Easily share self-service data models with colleagues.
Datasets can be augmented by business users with additional data, attributes, calculations, or transformations. Oracle Analytics examines the datasets, highlights any data anomalies found, and makes smart recommendations to repair or extend the dataset.
Using the power of the semantic profiler in Oracle Analytics, data quality insights provide a visual representation of your data's quality, helping you to rapidly identify issues. Make inline edits to quickly address any issues, rename columns, and use the scrollable mini map to easily traverse long lists.
Data flows provide business users a code-free capability to transform data sets into the information needed for analytics. Enrich data through a variety of transformation capabilities, including training and executing machine learning models. Save and share results as local datasets or a table in a connected relational database.
Instantly visualize data, jump-starting the analytics process. Get started quickly with more than 45 out-of-the-box visualizations, including waterfall bridge report, spark chart on performance tiles, heat map layers, and custom image maps.Centralized reports and dashboards
Build and centrally manage reports and interactive dashboards to ensure governance and control. Create static reports or interactive parameterized dashboards with functions, such drill down and filtering.Auto-Insights
The Auto Insights capability examines datasets and uses ML to automatically create visual insights with all available metrics and attributes. Discover new connections and patterns in the data that otherwise may not have been uncovered.
Leverage AI-powered natural language processing (NLP) to better understand and interact with your analytics. NLP powers text and speech for conversational search and analysis. Just ask a question and get a visual answer.Natural language generation
Only offered by Oracle Analytics Cloud, AI-driven natural language generation (NLG) creates smart textual narratives of visualizations that, by default, are connected live to the datasource and interact with other data objects on the canvas, such as visualizations and filters.
Oracle Analytics can be launched directly from any browser on any device. Access and transform all necessary datasets in preparation for analysis and share datasets, projects, and presentations with others.Mobile app
Stay connected with automated insights and ongoing monitoring of business activities from anywhere at any time. Receive intelligent recommendations as the platform learns each person’s specific patterns and data interests.
Leverage a documented API for embedding Oracle Analytics visualizations into custom web pages, portals, and applications. Embedded visualizations remain connected with live data access and retain all formatting and interactivity.
One-click, advanced analytics displays quick forecasts, trend lines, clusters, and reference lines. Users can customize the prediction interval and model type of the built-in algorithms to better fit the data and business use case.
The Explain capability examines the dataset to identify meaningful business drivers, contextual insights, and data anomalies—with only a few clicks and no coding. Choose visuals and findings from Explain to start a new dashboard and story.
No-code capabilities enable you to train models using a variety of built-in algorithms, including numeric prediction, multiclassifier, binary classifier, and clustering. These ML algorithms can be customized, trained, tuned, and then published to the wider analytics user community.
Use the depth and sophistication of the data science capabilities in Autonomous Database. Use R and Python to develop, test, and publish ML models that can be registered into Oracle Analytics Cloud allowing anyone to access and execute these new models with their own datasets or analyses.
Customers around the world gain powerful insights from multiple data sources using Oracle Analytics Cloud, driven by machine learning. Discover who uses Oracle Analytics Cloud and how Oracle technology has helped change their businesses.