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What is SAP Datasphere?

SAP Datasphere acts as a unified data experience platform within the SAP Business Data Cloud, designed to provide seamless and scalable access to vital business information. It effectively merges data from both SAP and non-SAP sources, promoting a cohesive data environment that enhances the speed and accuracy of decision-making. The platform includes features like data federation, cataloging, semantic modeling, and real-time data integration, which help organizations sustain consistent and contextualized data in both hybrid and cloud environments. Additionally, SAP Datasphere simplifies data management by preserving business context and logic, thereby delivering a comprehensive view of data that fosters innovation and improves business workflows. This integration not only enables businesses to utilize their data more efficiently but also positions them to thrive in a competitive market. As a result, organizations can make informed strategic choices that drive growth and success.

What is Data Virtuality?

Unify and streamline your data operations. Transform your data ecosystem into a dynamic force. Data Virtuality serves as an integration platform that ensures immediate access to data, centralizes information, and enforces data governance. The Logical Data Warehouse merges both materialization and virtualization techniques to deliver optimal performance. To achieve high-quality data, effective governance, and swift market readiness, establish a single source of truth by layering virtual components over your current data setup, whether it's hosted on-premises or in the cloud. Data Virtuality provides three distinct modules: Pipes Professional, Pipes Professional, and Logical Data Warehouse, which collectively can reduce development time by as much as 80%. With the ability to access any data in mere seconds and automate workflows through SQL, the platform enhances efficiency. Additionally, Rapid BI Prototyping accelerates your time to market significantly. Consistent, accurate, and complete data relies heavily on maintaining high data quality, while utilizing metadata repositories can enhance your master data management practices. This comprehensive approach ensures your organization remains agile and responsive in a fast-paced data environment.

Media

Media

Integrations Supported

Adform
Amazon EMR
Apache Hive
Criteo
GTmetrix
Google Ads
HubSpot Customer Platform
IBM Cognos Analytics
Jira
Looker
Meltwater
Recurly
SingleStore
Snowflake
SolarWinds Pingdom
Spotfire
Typeform
Verint Predictive Modeling
Vtiger Help Desk
Zendesk Chat

Integrations Supported

Adform
Amazon EMR
Apache Hive
Criteo
GTmetrix
Google Ads
HubSpot Customer Platform
IBM Cognos Analytics
Jira
Looker
Meltwater
Recurly
SingleStore
Snowflake
SolarWinds Pingdom
Spotfire
Typeform
Verint Predictive Modeling
Vtiger Help Desk
Zendesk Chat

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

SAP

Date Founded

1972

Company Location

Germany

Company Website

www.sap.com/products/data-cloud/datasphere.html

Company Facts

Organization Name

Data Virtuality

Date Founded

2012

Company Location

Germany

Company Website

datavirtuality.com

Categories and Features

Data Fabric

Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Categories and Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Integration

Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services

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