Microsoft Azure Data Factory
What is Microsoft Azure Data Factory?
Azure Data Factory is Azure's cloud ETL service for scale-out serverless data integration and data transformation. It offers a code-free UI for intuitive authoring and single-pane-of-glass monitoring and management. Data Factory provides a data integration and transformation layer that works across your digital transformation initiatives.
Company Details
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Real user data aggregated to summarize the product performance and customer experience.
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Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
87 Likeliness to Recommend
100 Plan to Renew
77 Satisfaction of Cost Relative to Value
Emotional Footprint Overview
Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
+91 Net Emotional Footprint
The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.
How much do users love Microsoft Azure Data Factory?
Pros
- Performance Enhancing
- Enables Productivity
- Reliable
- Efficient Service
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
Negative
Neutral
Positive
Feature Ratings
Data Security
Real Time Integration
iPaaS
Administrative Features
Batch Integration
Synchronization and Replication
Exception Handling and Notifications
Data Virtualization
API Management and Orchestration
Multi Channel Support
Metadata Management
Vendor Capability Ratings
Quality of Features
Ease of Data Integration
Business Value Created
Breadth of Features
Usability and Intuitiveness
Ease of Implementation
Availability and Quality of Training
Ease of IT Administration
Vendor Support
Ease of Customization
Product Strategy and Rate of Improvement
Microsoft Azure Data Factory Reviews
Firoz S.
- Role: Information Technology
- Industry: Retail
- Involvement: IT Development, Integration, and Administration
Submitted May 2023
ini. implementation was hard but then easy to use
Likeliness to Recommend
What differentiates Microsoft Azure Data Factory from other similar products?
Data extraction seems very effective on Microsoft ADF. Once you start working on it, it becomes easy to use.
What is your favorite aspect of this product?
Data pipelines Runtime integration
What do you dislike most about this product?
Managing resources is bit tricky for the beginners. And sometime it is hard to figure out a issue as community is not strong.
What recommendations would you give to someone considering this product?
As it can be integrate with other services, so it become easy to use and get better of the product. Also we can have self hosted runtime and integrate with ADF.
Pros
- Reliable
- Performance Enhancing
- Enables Productivity
- Trustworthy
Please tell us why you think this review should be flagged.
Martha K.
- Role: Information Technology
- Industry: Other
- Involvement: IT Development, Integration, and Administration
Submitted May 2023
A powerful and efficient data integration tool
Likeliness to Recommend
What differentiates Microsoft Azure Data Factory from other similar products?
Due of its integration with other Microsoft services including Azure SQL Database, Azure Blob Storage, and Azure Data Lake Storage, Azure Data Factory is a component of Microsoft's Azure cloud platform. You can quickly move and transform data between various Azure services thanks to this connectivity.
What is your favorite aspect of this product?
The capacity of ADF to enable batch and real-time data processing is a major feature. ADF can handle streaming data in real-time and deliver nearly instantaneous insights by using Azure Stream Analytics. In situations where real-time data processing is essential, such fraud detection, IoT applications, and real-time analytics, this is very helpful.
What do you dislike most about this product?
Because ADF lacks powerful debugging features, it may be difficult to locate and fix issues in your data pipelines. Even though ADF does include some fundamental logging and error reporting functionalities, these might not be enough for intricate data operations.
What recommendations would you give to someone considering this product?
You should be fully aware of your data integration and transformation requirements before implementing ADF. The types of data transformations needed, your data sources and destinations, and any real-time data processing requirements are all included in this.
Pros
- Continually Improving Product
- Reliable
- Trustworthy
- Caring
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Sanay L.
- Role: Operations
- Industry: Technology
- Involvement: Vendor Management and Renewal
Submitted May 2023
Fantastic tool, but should be more polished
Likeliness to Recommend
What differentiates Microsoft Azure Data Factory from other similar products?
It has more features and criterias as compare to any other product
What is your favorite aspect of this product?
Managing my customer data, and the protection provided to my data is the most favorite and important part.
What do you dislike most about this product?
in the settings tab sometimes it feels that there are alot of features. Those should be well organised so that people don't get confused
What recommendations would you give to someone considering this product?
Just close your eyes and go for it! It's way productive than any other tool in the market.
Pros
- Helps Innovate
- Continually Improving Product
- Performance Enhancing
- Enables Productivity
Please tell us why you think this review should be flagged.
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