Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Combine data silos effortlessly using Azure Data Factory, a versatile service designed to meet diverse data integration requirements for users of all expertise levels. You can easily create both ETL and ELT workflows without any coding through its user-friendly visual interface, or opt to write custom code if you prefer. The platform supports the seamless integration of data sources with over 90 pre-built, hassle-free connectors, all at no extra cost. With a focus on your data, this serverless integration service manages everything else for you. Azure Data Factory serves as a robust layer for data integration and transformation, facilitating your digital transformation goals. Furthermore, it empowers independent software vendors (ISVs) to enhance their SaaS applications by incorporating integrated hybrid data, enabling them to provide more impactful, data-driven user experiences. By utilizing pre-built connectors and scalable integration capabilities, you can concentrate on enhancing user satisfaction while Azure Data Factory efficiently handles the backend processes, ultimately streamlining your data management efforts.
Description
Easy Data Transform is a user-friendly tool designed to simplify the process of transforming and cleaning data. It offers a wide range of transformation features, such as splitting columns, merging datasets, handling missing values, and performing statistical analysis—all without the need for coding. Supporting formats like CSV, Excel, and JSON, this software helps professionals quickly clean and organize large datasets, saving time and reducing errors. Ideal for data analysts, researchers, and business professionals, Easy Data Transform provides a fast and efficient way to prepare data for further analysis.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon Redshift
Yes
Amazon S3
Yes
AnalyticsCreator
Yes
Apache Spark
Yes
Ascend
Yes
Azure Data Lake
Yes
Azure Marketplace
Yes
Evvox
Yes
FairCom DB
Yes
Klera
Yes
Integrations
Amazon Redshift
No
Amazon S3
No
AnalyticsCreator
No
Apache Spark
No
Ascend
No
Azure Data Lake
No
Azure Marketplace
No
Evvox
No
FairCom DB
No
Klera
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$99/user one-time fee
$99+tax per user
Minor version upgrades are free
Deploy on up to 3 computers (PC or Mac)
Minor version upgrades are free
Deploy on up to 3 computers (PC or Mac)
Free Trial
Yes
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
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
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)
No
In Person
No
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/products/data-factory/
Vendor Details
Company Name
Oryx Digital Ltd
Founded
2005
Website
www.easydatatransform.com
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
Data Preparation
Collaboration Tools
No
Data Access
No
Data Blending
No
Data Cleansing
No
Data Governance
No
Data Mashup
No
Data Modeling
No
Data Transformation
No
Machine Learning
No
Visual User Interface
No
ETL
Data Analysis
No
Data Filtering
No
Data Quality Control
No
Job Scheduling
No
Match & Merge
No
Metadata Management
No
Non-Relational Transformations
No
Version Control
No
Integration
Dashboard
Yes
ETL - Extract / Transform / Load
Yes
Metadata Management
Yes
Multiple Data Sources
Yes
Web Services
No
Product Features
ETL
Data Analysis
Yes
Data Filtering
Yes
Data Quality Control
Yes
Job Scheduling
No
Match & Merge
Yes
Metadata Management
No
Non-Relational Transformations
Yes
Version Control
No