Analytics Platform Capabilities Explorer

Introduction

Oracle Analytics is a complete platform with ready-to-use services for a wide variety of workloads and data. Offering valuable, actionable insights from all types of data—in the cloud, on-premises, or in a hybrid deployment—Oracle Analytics empowers business users, data engineers, and data scientists to access and process relevant data, evaluate predictions, and make quick, accurate decisions. The Oracle Analytics platform addresses the needs of the entire analytics process, including data ingestion, preparation and enrichment, visualization, and collaboration. Machine learning (ML) is embedded throughout the platform to help organizations go beyond being data-driven to become analytics-driven. Unlike other products, Oracle Analytics provides a customizable balance between centralized, governed analytics and self-service analytics.

A platform that addresses the entire analytics workflow

This image shows a high level diagram depicting the analytics workflow. It defines the analytics workflow in 6 steps. It then classifies Oracle Analytics built-in capabilities into that 6-step workflow from connecting to data sources, data modeling, data preparation, data exploration, self-service analytics, and collaboration for everyone, anytime, anywhere.

1. 1. Connect – Shows the many built-in native connectors that Oracle Analytics provides including Snowflake, Salesforce, BigQuery, Dropbox, MongoDB, MySQL, Teradata, Excel, and many others.
2. 2. Model – Shows the built-in ability to do both centralized governed modeling as well as self-service data modeling.
3. 3. Prepare – Shows the built-in capabilities to prepare and enrich datasets directly within the Oracle Analytics platform, negating the need to export data for manipulation with insecure spreadsheets.
4. 4. Explore – Shows capabilities like natural language processing that allow users to directly explore and interact with their data using natural language.
5. 5. Experience – Shows the capabilities that most users would interact with including web browser or mobile app. Experience also includes capabilities like data visualization, natural language narratives and embedding analytics into 3rd party apps.
6. 6. Collaborate – Shows the capabilities for sharing information. This includes social networking, the analytics catalog and multi-user development.

Oracle Analytics provides a rich workbench of capabilities that power the entire analytics workflow, including connecting to data, modeling, data preparation and enrichment, data exploration, visualization, storytelling, and collaboration. Reduce the need to rely on unsecured Excel exports to fill gaps in data preparation and enrichment. Oracle delivers a unified analytics process, ensuring that all data, from source to visualization, is managed through a tracked and shareable process.

Oracle Analytics Cloud (OAC)

If your data is gravitating to the cloud, so should your analytics. OAC is a cloud native service delivered on next-generation Oracle Cloud Infrastructure (OCI). OAC brings the collaboration and visualization advantages of an Oracle-native cloud service without the need for an on-premises data center.

Oracle Analytics Server (OAS)

If keeping infrastructure and data on-premises is preferred, then OAS provides what is required for an on-premises, private cloud analytics platform offering. Start new or move existing Oracle Business Intelligence Enterprise Edition (OBIEE) deployments to OAS. At no additional cost to existing OBIEE customers, OAS delivers modern, AI-powered analytics while keeping all data on-premises.

Why Oracle Analytics?

The Oracle Analytics platform provides:

• Analytics capabilities to all roles within the organization, including IT, data engineers, citizen data scientists, data scientists, executives, and business users.
• Embedded machine learning for every level of user, with capabilities that include no-code, one-click analytics to customizable algorithms trained for specific use cases.
• Both centralized, governed reporting and analytics together with business-led self-service, while always ensuring consistent and trusted numbers.
• A data model that abstracts physical data sources and query languages from business users.
• Built-in, trackable, and repeatable data preparation and enrichment that removes the need for unsecure data exports and Excel.