

SAS Data Management and Collibra Platform compete in the enterprise data management category. SAS seems to have the upper hand due to its data quality tools, while Collibra stands out for AI-driven governance capabilities.
Features: SAS Data Management is appreciated for its data integration, quality management, ETL processes, and language flexibility. Its metadata management and user-friendly interface are also highly valued. Collibra Platform is recognized for data governance workflows, data cataloging, and customization avenues. It excels in connectivity, collaboration, and providing enterprise-wide data lineage features.
Room for Improvement: SAS Data Management could benefit from a more flexible licensing model and smoother integration processes for non-ETL use cases. Improvements in database connections and documentation are recommended. Collibra Platform needs enhancements in data ingestion and integrating with older technologies. It could also improve its pricing structure and work on simplifying the user interface for non-technical users.
Ease of Deployment and Customer Service: SAS Data Management is primarily deployed on-premises, offering strong support with various global service levels. While technical support is effective, response time can be slow. Collibra Platform supports hybrid and public cloud deployments, providing flexibility for businesses with different infrastructure needs. Its customer support is competent, but improvements in technical documentation and issue resolution speed would enhance user experience.
Pricing and ROI: SAS Data Management is seen as expensive but offers high ROI, especially in industries like pharmaceuticals due to its alignment with FDA standards. Collibra Platform is also a premium tool with pricing reflecting its extensive features. Though the initial investment is significant, the ROI from improved search efficiency and audit readiness is notable. Smaller companies may find Collibra's pricing challenging despite its valuable governance features.
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.
Implementing Collibra Data Catalog can be cost-effective if its features align well with the business requirements.
While there are no direct cost reductions, there is significant indirect cost reduction.
There were weekly sessions with them that covered the loads and highlighted when it exceeded a threshold.
When using the Collibra Resident Architect program, the customer service was excellent, with issues quickly resolved.
The technical support from Collibra Governance is excellent.
The support for SAS in Brazil is not the best one, but the support in Sweden is really good, as they visit the company and work to solve the issues.
We were a big bank and had thousands of assets without any issues.
Collibra Lineage's performance is reliable, as the lineage harvest runs on the lineage server which operates on Collibra cloud.
I would rate the scalability of Collibra Lineage as a nine; it is a scalable solution for my business.
Collibra Platform is stable.
I rate the stability of Collibra Lineage as seven.
Users often find it challenging to utilize data governance tools, with ease of use ranked as an important criterion by 2028 standards.
Leveraging AI could simplify the process by automatically listing assets for movement, requiring only a couple of clicks, providing a win for administration purposes.
There should be a reduction in cost as compared to other tools.
There is significant room for improvement, especially with regard to using a hybrid approach that involves both CAS and persistent storage.
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.
From my experience, SAS Data Management is an expensive tool.
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.
SAS Data Management stands out because of its data standardization, transformation, and verification capabilities.
The best features I appreciate about SAS Data Management tool are that it's easy to create the flows and schedule data, and the tables are not too big, making it easy to control the ETL process, including user access which is also easy to manage in SAS.
| Product | Mindshare (%) |
|---|---|
| Collibra Platform | 7.6% |
| SAS Data Management | 1.7% |
| Other | 90.7% |
| Company Size | Count |
|---|---|
| Small Business | 23 |
| Midsize Enterprise | 12 |
| Large Enterprise | 57 |
| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 1 |
| Large Enterprise | 8 |
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.
SAS Data Management provides data integration, governance, and robust reporting tools. It connects to diverse data sources, ensuring quality management and enabling data analysis for technical and non-technical users.
SAS Data Management features flexible data flow creation, scheduling, and ETL control. It enhances data integration and metadata management with tools that support data standardization. Users benefit from its importing and exporting capabilities, connecting to multiple sources. It facilitates improved data quality management and offers a flexible language for diverse needs. Data visualization capabilities further support decision-making across industries, automating reports and data warehouses.
What are the key features of SAS Data Management?SAS Data Management helps industries like finance integrate diverse data sources for analytics and reporting. It is used for tasks such as financial reporting, credit risk analysis, and data cleansing. Through user-driven automation, it aids in aligning data warehouses and generating insightful visual outputs, making it ideal for analyzing structured data from sources like Excel and CSV files.
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