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Description
Oversee and protect the entire data lifecycle from the Edge to AI across any cloud platform or data center. Functions seamlessly within all leading public cloud services as well as private clouds, providing a uniform public cloud experience universally. Unifies data management and analytical processes throughout the data lifecycle, enabling access to data from any location. Ensures the implementation of security measures, regulatory compliance, migration strategies, and metadata management in every environment. With a focus on open source, adaptable integrations, and compatibility with various data storage and computing systems, it enhances the accessibility of self-service analytics. This enables users to engage in integrated, multifunctional analytics on well-managed and protected business data, while ensuring a consistent experience across on-premises, hybrid, and multi-cloud settings. Benefit from standardized data security, governance, lineage tracking, and control, all while delivering the robust and user-friendly cloud analytics solutions that business users need, effectively reducing the reliance on unauthorized IT solutions. Additionally, these capabilities foster a collaborative environment where data-driven decision-making is streamlined and more efficient.
Description
A data lakehouse represents a contemporary, open architecture designed for storing, comprehending, and analyzing comprehensive data sets. It merges the robust capabilities of traditional data warehouses with the extensive flexibility offered by widely used open-source data technologies available today. Constructing a data lakehouse can be accomplished on Oracle Cloud Infrastructure (OCI), allowing seamless integration with cutting-edge AI frameworks and pre-configured AI services such as Oracle’s language processing capabilities. With Data Flow, a serverless Spark service, users can concentrate on their Spark workloads without needing to manage underlying infrastructure. Many Oracle clients aim to develop sophisticated analytics powered by machine learning, applied to their Oracle SaaS data or other SaaS data sources. Furthermore, our user-friendly data integration connectors streamline the process of establishing a lakehouse, facilitating thorough analysis of all data in conjunction with your SaaS data and significantly accelerating the time to achieve solutions. This innovative approach not only optimizes data management but also enhances analytical capabilities for businesses looking to leverage their data effectively.
API Access
Has API
API Access
Has API
Integrations
AWS IoT SiteWise
Agent3
Alteryx
App Orchid
AtScale
Azquo
Cleo Integration Cloud
Cloudera Data Platform
Dell AI-Ready Data Platform
IBM Cognos Analytics
Integrations
AWS IoT SiteWise
Agent3
Alteryx
App Orchid
AtScale
Azquo
Cleo Integration Cloud
Cloudera Data Platform
Dell AI-Ready Data Platform
IBM Cognos Analytics
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Cloudera
Founded
2008
Country
United States
Website
www.cloudera.com
Vendor Details
Company Name
Oracle
Founded
1977
Country
United States
Website
www.oracle.com/data-lakehouse/
Product Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Business Intelligence
Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Product Features
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
