The Oracle Analytics Cloud service is a public cloud service that provides a full set of capabilities to explore and perform collaborative analytics.
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| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
Data Integration Flexibility: Users have praised the platform's ability to collect data from various external sources regardless of their size, facilitating reusing data models and reducing overall costs. This flexibility has allowed users to streamline their data management processes efficiently.
Insightful Data Extraction: Reviewers highly appreciate the platform's capability to merge data from different sources, extract valuable insights, and incorporate machine learning functionalities. By leveraging these features, users have been able to derive meaningful conclusions and make informed business decisions.
Useful Analytical Tools: Customers find features like live dashboards, scheduled reports, and seamless integration with multiple data sources very beneficial for their analytical requirements. These tools have enhanced users' ability to monitor key metrics in real-time and generate actionable insights for strategic planning.
Mobile App Unavailability: Users have expressed concerns about the lack of a mobile application, impacting accessibility and convenience. This limitation restricts users from accessing the platform on-the-go and hinders their ability to work seamlessly across devices.
On-Premise Solution Reliance: Reviewers have noted an over-reliance on mainly on-premise solutions, potentially limiting flexibility and scalability for users. This dependence may pose challenges in adapting to evolving business needs and integrating with cloud-based services for enhanced functionality.
Insufficient Documentation for Data Collection: Some users mentioned a lack of sufficient documentation for collecting data from on-premise services, leading to challenges in utilizing the platform effectively. The absence of comprehensive guidance can result in delays and errors in data extraction processes, impacting overall productivity.
