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ease
features
design
support

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Description

Connect and centralize data. Transform your data landscape into a flexible powerhouse. Data Virtuality is a data integration platform that allows for instant data access, data centralization, and data governance. Logical Data Warehouse combines materialization and virtualization to provide the best performance. For high data quality, governance, and speed-to-market, create your single source data truth by adding a virtual layer to your existing data environment. Hosted on-premises or in the cloud. Data Virtuality offers three modules: Pipes Professional, Pipes Professional, or Logical Data Warehouse. You can cut down on development time up to 80% Access any data in seconds and automate data workflows with SQL. Rapid BI Prototyping allows for a significantly faster time to market. Data quality is essential for consistent, accurate, and complete data. Metadata repositories can be used to improve master data management.

Description

Eliminate all manual procedures, potential error sources, and inefficiencies. Avoid the need to constantly re-engineer your data warehouse with every shift in business requirements. Implement automatic quality checks both between and within data sources and respond swiftly when issues arise, which is essential for numerous data users. It’s important to genuinely trust your data now. Create a “gold record” reference point to ensure that business teams always have access to the most up-to-date information available. Establish one unified version of the truth that can be accessed anytime, anywhere. Develop an intermediate model that organizes, stores, and preserves your data independently of how it will be used. Be agile in responding to evolving data sources and business inquiries. Seamlessly connect all your data sources—from data lakes and operational systems to spreadsheets and legacy tools—just like you would with the initial one. Ensure data is stored, preserved, and enhanced in quality to streamline data warehouse automation processes. Data should be organized, enriched, and thoroughly documented so that it is accessible in well-structured datasets (information marts). In doing so, you pave the way for more efficient decision-making across the organization.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Google Sheets
Microsoft Excel
Microsoft Power BI
Tableau
Adobe Marketo Engage
Brandwatch
Emarsys
Fountain
Google Ads
IBM Db2
JW Player
Looker
PostgreSQL
Qlik Cloud Analytics
Redis
SAP Analytics Cloud
Snowflake
Spotfire
Xero

Integrations

Google Sheets
Microsoft Excel
Microsoft Power BI
Tableau
Adobe Marketo Engage
Brandwatch
Emarsys
Fountain
Google Ads
IBM Db2
JW Player
Looker
PostgreSQL
Qlik Cloud Analytics
Redis
SAP Analytics Cloud
Snowflake
Spotfire
Xero

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Data Virtuality

Founded

2012

Country

Germany

Website

datavirtuality.com

Vendor Details

Company Name

dFakto

Founded

2000

Country

Belgium

Website

www.dfakto.com/datafaktory-data-warehouse-automation/

Product 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

Product Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

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