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features
design
support

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Description

Today’s data warehouses are more advanced than they have ever been, yet the methods for integrating data have not kept pace with these advancements. The outdated middleware systems present significant obstacles for businesses aiming for agility. By utilizing SQL functions in Snowflake, organizations can effectively push data to their applications. It's also important to manage integration alongside other tasks in the data pipeline. Minimizing the need for extensive data infrastructure can help alleviate security concerns and reduce vendor assurance burdens. Complicated middleware and ETL processes contribute to deployment delays. Maintaining agility while minimizing code complexity is essential. Addressing the issues of consolidating customer data is key to establishing a reliable single source of truth. Recent advancements offer unprecedented connectivity and flexibility. Integrations can now operate without any intermediary infrastructure between the data source and its destination. Instead of transferring data, Connect utilizes live queries to present information directly within the destination application, ensuring that users always have access to the most current data.

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 No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Google Cloud BigQuery Yes 
Google Sheets No 
Microsoft Excel No 
Microsoft Power BI No 
Qlik Data Integration No 
Salesforce Yes 
Snowflake Yes 
Tableau No 
Toucan No 
Zendesk Yes 

Integrations

Google Cloud BigQuery No 
Google Sheets Yes 
Microsoft Excel Yes 
Microsoft Power BI Yes 
Qlik Data Integration Yes 
Salesforce No 
Snowflake No 
Tableau Yes 
Toucan Yes 
Zendesk No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Omnata

Country

Australia

Website

omnata.com

Vendor Details

Company Name

dFakto

Founded

2000

Country

Belgium

Website

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

Product Features

Integration

Dashboard No 
ETL - Extract / Transform / Load No 
Metadata Management No 
Multiple Data Sources No 
Web Services No 

Product Features

Data Management

Customer Data No 
Data Analysis No 
Data Capture No 
Data Integration No 
Data Migration No 
Data Quality Control No 
Data Security No 
Information Governance No 
Master Data Management No 
Match & Merge No 

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