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What is Oracle Analytics Cloud Service ?

What is OACS ?

Oracle Analytics Cloud Service (OACS) , a scalable and secure public cloud service from Oracle , provides organizations with the ability to explore and perform collaborative analytics from any data source. It allows you to interact with your personal data, harmonize data sources, collate and manage disparate inputs, and handle data with coherence and consistency during organizational sharing. You can review and visualize both personal and corporate data, and gain insights at key stages of the iterative information cycle.

In addition to adding Essbase as a cloud option, OAC also delivers a new Business Intelligence Cloud Service (BICS) version - Enterprise Edition . Using BICS within OAC also means having access to the BI Admin Tool, which is used to create, modify, and maintain the BI logical models that drive its subject areas.

Oracle Analytics Cloud offers everything you need for analytic agility, from fast self-service discovery to simple yet sophisticated data loading and blending, powerful inline data prep, automatic visualizations, data storytelling, instant mobile with full authoring, easy and extensible advanced analytics, and more. These capabilities are part of Oracle's best in class solutions - Oracle Data Visualization, which is delivered via Oracle Data Visualization Cloud Service (DVCS), Oracle Data Visualization Desktop (DVD), and integrated into Oracle Business Intelligence Cloud Service (BICS).

Features of Oracle Analytics Cloud include:

  • Built on a high-performance platform with flexible data storage, Oracle Analytics Cloud provides a complete set of tools for deriving and sharing data insights.
  • Data preparation: Analysts can ingest, profile, and cleanse data using a variety of algorithms.
  • Data flow: Analysts can prepare, transform and aggregate data, and then run machine-learning models at scale.
  • Data discovery: Subject matter experts can easily collaborate with other business users, blending intelligent analysis at scale, machine learning, and statistical modeling.
  • Data collaboration: Large organizations and small teams can share data more simply, without the need to manage or consolidate multiple versions of spreadsheets, and quickly perform ad hoc analysis of the spreadsheet data.
  • Data-driven: Application developers can utilize interfaces that enable them to extend, customize, and embed rich analytic experiences in the application flow.


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