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What is Oracle Cloud Infrastructure Data Lakehouse?

A data lakehouse embodies a modern, open architecture tailored for the storage, understanding, and analysis of large data sets. It combines the strong features of traditional data warehouses with the considerable adaptability provided by popular open-source data technologies currently in use. Building a data lakehouse is feasible on Oracle Cloud Infrastructure (OCI), which supports effortless integration with advanced AI frameworks and pre-built AI services, including Oracle’s language processing tools. Users can utilize Data Flow, a serverless Spark service, enabling them to focus on their Spark tasks without the hassle of infrastructure management. Many clients of Oracle seek to create advanced analytics driven by machine learning, applicable to their Oracle SaaS data or other SaaS sources. In addition, our intuitive data integration connectors simplify the setup of a lakehouse, promoting comprehensive analysis of all data alongside your SaaS information and considerably speeding up the solution delivery process. This groundbreaking methodology not only streamlines data governance but also significantly boosts analytical prowess for organizations aiming to harness their data more efficiently. Ultimately, the integration of these technologies empowers businesses to make data-driven decisions with greater agility and insight.

What is Lyftrondata?

If you aim to implement a governed delta lake, build a data warehouse, or shift from a traditional database to a modern cloud data infrastructure, Lyftrondata is your ideal solution. The platform allows you to easily create and manage all your data workloads from a single interface, streamlining the automation of both your data pipeline and warehouse. You can quickly analyze your data using ANSI SQL alongside business intelligence and machine learning tools, facilitating the effortless sharing of insights without the necessity for custom coding. This feature not only boosts the productivity of your data teams but also speeds up the process of extracting value from data. By defining, categorizing, and locating all datasets in one centralized hub, you enable smooth sharing with colleagues, eliminating coding complexities and promoting informed, data-driven decision-making. This is especially beneficial for organizations that prefer to store their data once and make it accessible to various stakeholders for ongoing and future utilization. Moreover, you have the ability to define datasets, perform SQL transformations, or transition your existing SQL data processing workflows to any cloud data warehouse that suits your needs, ensuring that your data management approach remains both flexible and scalable. Ultimately, this comprehensive solution empowers organizations to maximize the potential of their data assets while minimizing technical hurdles.

Media

Media

Integrations Supported

ADP Comprehensive Services
Basecamp
Copper
Docusign
Exact Online
Facebook
Gmail
Google Contacts
IBM Db2
Jotform
Microsoft Dynamics 365 Marketing
Microsoft Excel
Microsoft Project
SAP NetWeaver
SAP SuccessFactors
Snowflake
Xero
Zoho CRM
eBay

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Oracle

Date Founded

1977

Company Location

United States

Company Website

www.oracle.com/data-lakehouse/

Company Facts

Organization Name

Lyftrondata

Date Founded

2017

Company Location

United States

Company Website

lyftron.com

Categories and Features

Data Lake

Not specified

Data Management

Not specified

Data Warehouse

Not specified

Categories and Features

Data Lake

Not specified

Data Pipeline

Not specified

Data Preparation

Not specified

Data Replication

Not specified

Data Virtualization

Not specified

Data Warehouse

Not specified

DataOps

Not specified

ETL

Not specified

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