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What is Oracle Big Data Preparation?

Oracle Big Data Preparation Cloud Service is an all-encompassing managed Platform as a Service (PaaS) that streamlines the processes of data ingestion, correction, enhancement, and publication for large data sets, all within an intuitive interface that offers complete transparency. This service integrates effortlessly with other Oracle Cloud offerings, such as the Oracle Business Intelligence Cloud Service, which enhances the potential for in-depth analysis downstream. Among its core features are profile metrics and visual representations that become accessible after data ingestion, allowing users to see a visual summary of each profiled column alongside the results of duplicate entity evaluations conducted on the entire data set. The Home page of the service makes it easy for users to visualize governance tasks and access essential runtime metrics, data health reports, and alerts that keep them updated on their data’s status. Furthermore, users can oversee their transformation processes to ensure files are processed correctly, while also gaining comprehensive insights into the entire data journey, from initial ingestion through various enrichment stages to final publication. This platform is designed to equip users with the necessary tools for effective data management, empowering them to take charge of their data preparations confidently. Ultimately, Oracle Big Data Preparation Cloud Service not only enhances data handling efficiency but also fosters a robust environment for data governance.

What is Dremio?

Dremio offers rapid query capabilities along with a self-service semantic layer that interacts directly with your data lake storage, eliminating the need to transfer data into exclusive data warehouses, and avoiding the use of cubes, aggregation tables, or extracts. This empowers data architects with both flexibility and control while providing data consumers with a self-service experience. By leveraging technologies such as Apache Arrow, Data Reflections, Columnar Cloud Cache (C3), and Predictive Pipelining, Dremio simplifies the process of querying data stored in your lake. An abstraction layer facilitates the application of security and business context by IT, enabling analysts and data scientists to access and explore data freely, thus allowing for the creation of new virtual datasets. Additionally, Dremio's semantic layer acts as an integrated, searchable catalog that indexes all metadata, making it easier for business users to interpret their data effectively. This semantic layer comprises virtual datasets and spaces that are both indexed and searchable, ensuring a seamless experience for users looking to derive insights from their data. Overall, Dremio not only streamlines data access but also enhances collaboration among various stakeholders within an organization.

Media

Media

Integrations Supported

Azure DevOps
Eloqua
Jira Work Management
Kinetica
MySQL
Omnis Studio
Oracle APEX
Oracle Cloud CX
Oracle Database
Oracle Fusion Cloud Procurement
TurningPoint

Integrations Supported

Apache Superset
Azure Marketplace
Codd AI
DashboardFox
HPE Ezmeral
Okera
SQL
Yurbi
witboost

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Linux

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Not specified

Company Facts

Organization Name

Oracle

Date Founded

1977

Company Location

United States

Company Website

docs.oracle.com/en/cloud/paas/big-data-prep-cloud/index.html

Company Facts

Organization Name

Dremio

Date Founded

2015

Company Location

United States

Company Website

www.dremio.com

Categories and Features

Big Data

Not specified

Data Preparation

Not specified

Data Virtualization

Not specified

Categories and Features

Big Data

Not specified

Data Engineering

Not specified

Data Lake

Not specified

Data Lineage

Not specified

Data Virtualization

Not specified

Data Warehouse

Not specified

Query Engines

Not specified

Semantic Layer

Not specified

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