dataFactorydFakto
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Related Products
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About
Enterprise synthetic test data solutions. In order to generate test data that accurately reflects the structure of your application or database, it must be easy to model and maintain each test data project as changes to the data model occur throughout the lifecycle of the application. Maintain referential integrity of parent/child/sibling relationships across the data domains within an application database or across multiple databases used by multiple applications. Ensure the consistency and integrity of synthetic data attributes across applications, data sources and targets. For example, a customer name must always match the same customer ID across multiple transactions simulated by real-time synthetic data generation. Customers want to quickly and accurately create their data model as a test data project. GenRocket offers 10 methods for data model setup. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce.
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About
Cut out all the manual processes, sources of errors, and wasted time. Don’t re-engineer your data warehouse every time a business change occurs. Apply automatic quality checks inter and intra-sources, and take action quickly when needed. That’s crucial for hundreds of data consumers. Trust really your data now. Build your “gold record” referential so the business teams have always the freshest data possible. One single version of the truth, available anywhere, anytime. Build an intermediate model that structures, stores, and historicizes your data independently of their uses. Answer fast to changing sources and business requests. From raw data to any system, connect all your sources easily as for the first one (datalake, operational systems, excels, relational database, legacy tools, etc. Store, historicize, and improve data quality to facilitate data warehouse automation. Data is structured, enriched, and documented to be available in datasets (information marts).
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Enterprises searching for a synthetic test data solution to model their applications and databases
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Audience
Organizations in need of a tool to turn raw data from multiple sources into qualitative information for effective decision making
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Support
Phone Support
Supported
24/7 Live Support
Supported
Online
Supported
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Support
Phone Support
Supported
24/7 Live Support
Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Supported
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Company InformationGenRocket
Founded: 2012
United States
www.genrocket.com/enterprise-features/
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Company InformationdFakto
Founded: 2000
Belgium
www.dfakto.com/datafaktory-data-warehouse-automation/
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Alternatives |
Alternatives |
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Categories |
Categories |
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Integrations
BlazeMeter
Supported
Delphix
Supported
Docker
Supported
FitNesse
Supported
Gatling
Supported
Git
Supported
HCL Accelerate
Supported
IBM Rational Build Forge
Supported
IBM WebSphere Application Server
Supported
JUnit
Supported
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Integrations
BlazeMeter
Not Supported
Delphix
Not Supported
Docker
Not Supported
FitNesse
Not Supported
Gatling
Not Supported
Git
Not Supported
HCL Accelerate
Not Supported
IBM Rational Build Forge
Not Supported
IBM WebSphere Application Server
Not Supported
JUnit
Not Supported
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