Oracle Autonomous Data Warehouse is the world’s first and only autonomous database optimized for analytic workloads, including data marts, data warehouses, data lakes, and data lakehouses. With Autonomous Data Warehouse, data scientists, business analysts, and nonexperts can rapidly, easily, and cost-effectively discover business insights using data of any size and type. Built for the cloud and optimized using Oracle Exadata, Autonomous Data Warehouse benefits from faster performance and, according to an IDC report (PDF), lowers operational costs by an average of 63%.
Nézze meg Juan Loaiza EVP Oracle CloudWorld vitaindító előadásának ismétlését, és ismerje meg ezt az úttörő, AI-központú AppDev infrastruktúrát.
Reduction in financial closing time
Lower data administration costs
Faster query performance
Five-year ROI with five-month payback period
Reduction in DBA workloads for reporting
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Autonomous Database provides the foundation for a data lakehouse—a modern, open architecture that enables you to store, analyze, and understand all your data. The data lakehouse combines the power and richness of data warehouses with the breadth, flexibility, and low cost of popular open source data lake technologies. Access your data lakehouse through Autonomous Database using the world's most powerful and open SQL processing engine.
Autonomous Database's advanced data processing engine lets you gain insights across multicloud data sources. It doesn't matter if your data is in AWS, Azure, Google Cloud Platform, or Oracle Cloud Infrastructure object stores and databases. Or, if your data is in big data file formats such as Apache Parquet, JSON, Apache ORC, Apache Avro, CSV, or XML, Autonomous Database delivers a simple, consistent view of your data estate using your preferred SQL-based tools and applications.
Increase the productivity of business users by reducing their dependency on IT, using self-service data tools, and creating low-code analytic applications. Enhance collaboration across teams with Autonomous Database’s analytic views that provide common business definitions and metrics integrated with Oracle Analytics Cloud, Tableau, and other business intelligence applications. Enhance business storytelling based on all data, using the power of built-in machine learning, spatial and graph analytics, and data visualization.
Autonomous Database provides the most advanced data security that helps reduce the risk of a data breach and simplifies regulatory compliance. Its automated self-patching, automatic, always-on encryption and key management, granular access controls, and flexible data masking provide comprehensive user behavior monitoring with sophisticated auditing capabilities.
Oracle Autonomous Database plays a central role in the data lakehouse as both an analytic engine and optimized data store. Users can access the lakehouse through Autonomous Database’s powerful and open SQL processing engine. Analyze Autonomous Database data from big data frameworks using highly efficient Apache Spark and Python connectivity.
Autonomous management capabilities, such as provisioning, configuring, securing, tuning, and scaling, eliminate nearly all the manual and complex tasks that can introduce human error. Autonomous management enables customers to run a high-performance, highly available, and secure data warehouse while running thousands of databases with no administration.
FeaturesAutonomous Data Warehouse continuously monitors all aspects of system performance. It adjusts autonomously to ensure consistent high performance even as workloads, query types, and the number of users vary over time.
FeaturesSecure Autonomous Data Warehouse with a unified database security control center that identifies sensitive data and masks it, issues alerts on risky users and configurations, audits critical database activities, and discovers suspicious attempts to access data.
FeaturesData Studio comes built into Autonomous Database, offering users simple, self-service data management tools for loading, transforming, analyzing, and sharing data among teams for better collaboration. Business and data analysts can easily integrate data from more than 100 application, cloud service, and database sources with drag-and-drop workflow capabilities. Data Studio lets you generate business models; quickly discover anomalies, outliers, and hidden patterns; share data with stakeholders; and understand data dependencies based on the impact of changes.
FeaturesBuild and deploy machine learning models in Oracle Autonomous Data Warehouse using scalable and optimized in-database algorithms. Oracle Machine Learning accelerates the creation of machine learning models for data scientists by eliminating the need to move data to dedicated machine learning systems. Let your users ask any questions in their natural language and have Autonomous Database Select AI answer them.
FeaturesAutonomous Database includes graph database features to represent and manage complex data relationships. The graph analytics enable data scientists and developers to apply pattern recognition, classification, and statistical analysis for deeper context.
The spatial features in Autonomous Data Warehouse address all forms of applications, spatial workloads, and datasets, including the most demanding, large-scale location intelligence and geospatial applications.
FeaturesAutonomous Database provides more than 99.995% availability1 with built-in Oracle Real Application Clusters, parallel infrastructure, automated disaster recovery, and backups.
FeaturesOracle application accelerators for Oracle’s E-Business Suite, Fusion Applications, and NetSuite provide enhanced analytical capabilities with self-service data discovery, built-in ETL, and KPI metrics. Users can do more with comprehensive data integration and ready-to-use data models.
Oracle Autonomous Database@Azure lets organizations run workloads where they choose, modernize and innovate with Oracle and Azure services, and simplify cloud purchasing and management. Customers combine Azure services of their choosing with Oracle Autonomous Data Warehouse, an OCI service that’s deeply integrated with and colocated in Azure data centers, to run analytics workloads with high performance, scale, and availability.
Watch how to maximize collaboration with Oracle Autonomous Database data sharing.
IDC finds Autonomous Database customers obtain a 417% ROI in five years.
Read the IDC report (PDF)Learn how Oracle customers are using Oracle Autonomous Data Warehouse to modernize their businesses through data lakes, machine learning, and automation.
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Select AI’s new support for retrieval-augmented generation (RAG) makes it easy to use large language models (LLMs) to gain insight or generate innovative content based on your private data using natural language prompts. Use Select AI with RAG to get more relevant responses to your natural language questions while helping reduce the risk of hallucination.
Read the complete postExplore Oracle Help Center for product documentation and other resources to deploy Autonomous Data Warehouse.
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1. The service level agreement (SLA) for 99.995% availability assumes the use of Oracle Autonomous Data Guard. The SLA is 99.95% availability when Autonomous Data Guard isn’t enabled.
2. The Gartner Peer Insights logo is a trademark and service mark of Gartner Inc. and/or its affiliates and is used herein with permission. All rights reserved. Gartner Peer Insights reviews constitute the subjective opinions of individual end-user reviews, ratings, and data applied against a documented methodology; they neither represent the views of, nor constitute an endorsement by, Gartner or its affiliates.