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Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
When considering the time and effort required to build a catalog and utilize it effectively, combined with the prices, it often does not make financial sense.
A lot of time gets saved in data search, data discovery, and data analysis, which translates into a good return on investment.
Implementing Collibra Data Catalog can be cost-effective if its features align well with the business requirements.
On a scale of one to ten, I would rate the technical support as nine.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
There were weekly sessions with them that covered the loads and highlighted when it exceeded a threshold.
They provide quick and high-quality responses.
When using the Collibra Resident Architect program, the customer service was excellent, with issues quickly resolved.
Azure Data Factory is highly scalable.
I did not experience scalability issues.
We were a big bank and had thousands of assets without any issues.
Our organization has more than 10,000 employees without any glitch, without any hang, and without any slowness.
It can handle growth in users, assets, metadata, and integrations, but it requires good governance and administration.
The solution has a high level of stability, roughly a nine out of ten.
I have been using Azure Data Factory for a very long time, and I did not find too many issues.
The performance and reliability of Collibra Platform is excellent since we use the SaaS cloud offering.
It does not lag, and it can handle large volumes of data in less time.
Collibra Platform is stable.
The ability to handle the largest volumes of data is another concern; if I have to manage more than one terabyte of data every day, I am not comfortable dealing with Azure Data Factory and had to switch to Oracle Data Integrators (ODI) because it lacks performance features.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
Users often find it challenging to utilize data governance tools, with ease of use ranked as an important criterion by 2028 standards.
Integration with tools such as Power BI, Tableau, or notebooks would be great for handling large data processing.
Leveraging AI could simplify the process by automatically listing assets for movement, requiring only a couple of clicks, providing a win for administration purposes.
The pricing is cost-effective.
It is considered cost-effective.
Collibra has high initial costs for licensing that can be a barrier to small and medium-sized companies starting with it.
There are plans to increase license rates.
Adding modules like Privacy could become expensive.
It connects to different sources out-of-the-box, making integration much easier.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
Regarding the integration feature in Azure Data Factory, the integration part is excellent; we have major source connectors, so we can integrate the data from different data sources and also perform basic transformation while transforming, which is a great feature in Azure Data Factory.
My experience with Collibra's collaboration tools in improving data literacy has been quite good. I think it is one of the best for helping people understand and discuss certain data sets and manage workflows.
We have saved up to 30% of manual work as a specific process or workflow became faster.
Another important feature is the data lineage, which helps in impact assessment before making any changes, showing where a particular field is being used in a report, data quality report, or normal report.
| Product | Mindshare (%) |
|---|---|
| Azure Data Factory | 2.3% |
| Informatica Intelligent Data Management Cloud (IDMC) | 3.7% |
| SSIS | 3.7% |
| Other | 90.3% |
| Product | Mindshare (%) |
|---|---|
| Collibra Platform | 8.4% |
| Microsoft Purview Data Governance | 9.4% |
| Varonis Platform | 5.0% |
| Other | 77.2% |

| Company Size | Count |
|---|---|
| Small Business | 31 |
| Midsize Enterprise | 21 |
| Large Enterprise | 63 |
| Company Size | Count |
|---|---|
| Small Business | 24 |
| Midsize Enterprise | 14 |
| Large Enterprise | 63 |
Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.
Collibra Platform is preferred for workflows, data lineage, and a user-friendly interface. It enhances metadata management with robust collaboration, flexible customization, and powerful reporting, aiding organizations in effective data management.
Collibra Platform provides dependable solutions for metadata management, data lineage, and governance. It strengthens data governance with cataloging, glossaries, automation, and integration, supporting compliance and data quality management. Despite challenges with integration and metadata ingestion, the platform is vital for data governance programs, offering comprehensive AI capabilities and streamlined processes for enterprise data management.
What are Collibra Platform's key features?
What benefits should be sought in reviews?
In industries, Collibra Platform supports IT teams through metadata management and data quality assurance. It is widely used for compliance initiatives like GDPR, speeding up digital transformation and enforcing policy management. Organizations employ it to consolidate business and technical metadata, ensuring effective enterprise-scale data management in diverse sectors.
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