

Informatica IDMC and erwin Data Intelligence compete in the data management solutions category. Informatica IDMC appears to have the upper edge due to its extensive cloud-native platform and seamless integration with MDM, providing robust data quality and versatile mapping capabilities.
Features: Informatica IDMC offers seamless integration with MDM, robust data quality, and versatile mapping capabilities in a scalable cloud-native platform. It provides AI-driven data discovery and cloud scalability. erwin Data Intelligence is known for its outstanding reverse-engineering capabilities, comprehensive metadata management, and Smart Data Connectors. It excels in providing a business glossary and effective lineage visualization.
Room for Improvement: Informatica IDMC could improve by integrating more smoothly with non-Informatica applications and offering a more streamlined UI. Enhancements in SAP application integration and preconfigured business services are also needed. erwin Data Intelligence faces challenges with limited customization options, SDK inconsistencies, and complex navigation. Improving data quality assessment capabilities and expanding plugin support would benefit erwin users.
Ease of Deployment and Customer Service: Informatica IDMC supports deployment in both on-premises and cloud environments, offering versatility. However, its integration process can be challenging. erwin Data Intelligence offers similar deployment options but is less flexible in integration. Informatica receives praise for its strong support, though users desire better SLA adherence. erwin’s customer support is positively received, but cross-product integration could enhance user experience.
Pricing and ROI: Informatica IDMC is generally perceived as expensive, with its pricing based on data usage or user count, ideal for large enterprises. Despite its cost, it delivers significant ROI through improved data quality and time savings. erwin Data Intelligence provides a more budget-friendly pricing structure while maintaining robust features, offering ROI through efficient data governance and reduced manual overhead.
Leadership prefers to utilize third-party tools, such as Snowflake, which has both storage and ELT features.
The stability and performance remain issues.
Compared to Collibra Catalog, where the value is noticeable within six months.
Compared to competitor products like Collibra, erwin Data Intelligence is more cost-effective, providing a data catalog and data lineage views without the high costs associated with governance software.
Due to the tool's maturity limitations, solutions are not always simple and often require workarounds.
Even after going out of service support, they still reached back to me whenever I raised tickets.
We expect more responsive assistance because they have the expertise since Informatica is their tool, but I don't see enough expertise on the Informatica support side.
Quest technical support is very good, as they provide not only a technical help desk but also a data automation team that creates and customizes smart connectors, offering a wealth of skilled support.
For technical support, they need to improve response time.
I have used the product over multiple systems and was able to write reports for large data sets without any performance issues.
As a SaaS platform, IDMC is quite scalable and provides complete flexibility.
There are many options available, and the licensing model is quite good, supporting our needs effectively.
Regarding scalability, I would rate erwin Data Intelligence as an eight or nine for its ability to expand.
When we tried to connect erwin Data Intelligence to ERP on Oracle Cloud, specifically Oracle Fusion, we encountered many problems.
Stability is crucial because IDMC holds business-critical data, and it needs to be available all the time for business users.
There are substantial stability issues with Informatica Cloud Data Quality on the cloud.
I find the stability to be good, with occasional restarts required every two to three months due to glitches.
It is good for small and medium enterprises, but larger enterprises with huge amounts of metadata might face some issues.
From my perspective, I would rate the stability of erwin Data Intelligence as an eight or nine out of ten.
I feel whatever the tool does not have now, there is a feedback loop allowing us to request new features, and we continually ask for different ways to do things as we have a pipeline into the product management team.
The tool needs to mature in terms of category-specific attributes or dynamic attributes.
The current solution requires code-writing and tweaking, while other solutions offer material-level matches.
erwin Data Intelligence could improve particularly in the UI, as they are using old technologies that are not modern and do not serve the current requirements of the modern market.
The dashboard in erwin Data Intelligence is customizable, and you can easily create different views.
It ranges from a quarter million to a couple of million a year.
Informatica Intelligent Cloud Services is affordable for my specific use cases, with the pricing being rated three or four on a scale where one is very cheap.
Regarding pricing, compared to other tools I have worked with, Informatica offers competitive pricing, which I find not high in terms of starting strategy.
The platform's ability to pull in data from other platforms without the need for an additional integration tool enhances its appeal.
The connectors serve as the main functionality, making data integration processes more efficient by saving time and effort.
We could run data quality rules as part of Service Bus, which ensured the integrity of customer information before it was entered into our database.
This feature is probably the most valuable because it allows for automated reverse engineering of lineage.
The mind maps clarify for the business the related business terms and the relation between the business terms and other technical terms and technical data products, and they are very effective.
| Product | Mindshare (%) |
|---|---|
| Informatica Intelligent Data Management Cloud (IDMC) | 4.9% |
| erwin Data Intelligence | 2.1% |
| Other | 93.0% |

| Company Size | Count |
|---|---|
| Small Business | 51 |
| Midsize Enterprise | 27 |
| Large Enterprise | 155 |
| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 4 |
| Large Enterprise | 16 |
Informatica Intelligent Data Management Cloud (IDMC) offers seamless integration of master data management, data quality, and data integration with a cloud-native architecture supporting multiple data management styles, optimizing data governance through metadata management.
IDMC enhances data synchronization and mapping tasks, utilizing a broad range of connectors to interact efficiently with data sources. Its precise address validation via AddressDoctor and intuitive navigation bolster user empowerment, delivering agility, scalability, and security in data governance. Despite its strengths, areas like ease of use, SAP integration, and reporting could benefit from enhancements. Connectivity issues and workflow complexities are noted, needing improvements in performance, support, and licensing cost. Users demand expanded ETL capabilities, real-time processing, and broader data source support to address growing data needs.
What are the key features of IDMC?In industries such as banking, healthcare, and telecom, IDMC is implemented for data integration, cloud migration, and enhancing data quality. Its capabilities are crucial for metadata management, lineage tracking, and real-time processing, ensuring high data quality and streamlined operations.
erwin Data Intelligence is a comprehensive platform for metadata management, data cataloging, and governance. It enables organizations to gain insights, improve traceability, and streamline compliance through its advanced features.
Focusing on data lineage, metadata repositories, and seamless integrations, erwin Data Intelligence provides a unified perspective of enterprise data. Its robust capabilities include Smart Data Connectors for automation, efficient data visualization with mind maps, and adaptable metadata properties. While the platform integrates well into existing systems, areas for improvement include automation, SDK inconsistencies, and the need for better data quality assessments. Use cases highlight its importance in enhancing business data models and regulatory compliance.
What are the key features of erwin Data Intelligence?Industries implementing erwin Data Intelligence often focus on mapping data sources and integrating governance with ETL tools. This supports comprehensive data management strategies, enabling business teams to better locate, understand, and utilize data effectively. Its application in metadata management and automated reporting is particularly valuable in sectors requiring stringent regulatory compliance.
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