Accessing data as a service is essential, especially for validations requiring external data services. This goes beyond basic syntactic checks, like ensuring an email address contains the @ symbol or .com domain. Instead, it's about advanced validation, such as verifying if an email address exists or if a phone number is valid. These services are in high demand, especially for regions like China, Argentina, and other parts of Latin America. While such capabilities were initially more common in the United States, they are now increasingly required globally.
I think Informatica Cloud Data Quality is one of the more mature cloud products, so I can't think of any areas where improvements are required. Informatica Cloud Data Quality is a product that is very similar to what Informatica offers for data quality on-premises, so there aren't too many gaps compared to the others, and I can't really think of any area requiring improvements. I would like Informatica Cloud Data Quality to offer more integration capabilities with different platforms. I need to consider the fact that Informatica Cloud Data Quality supports a lot of the standard protocols for which most platforms use endpoints. In short, integration is not really an issue with the product. The high price of the product is an area of concern where improvements are required.
Informatica Capability Owner at a insurance company with 10,001+ employees
Real User
Top 5
2023-09-06T17:40:00Z
Sep 6, 2023
Informatica Cloud Data Quality provides many of the capabilities found in on-premises solutions. While the cloud edition offers additional features, it has also deprecated certain functionalities, such as connecting to web services. In the on-premises version, features like web service consumer and web service provider are available, but these functionalities are currently unavailable in the cloud edition. Vendors offer options for custom solutions, although they may not offer the same functionality as the on-premises version.
With the on-premises version, we had many abilities to connect with any kind of server. But when it comes to cloud data quality, there are certain limitations to connecting. For example, we may be using an AS400. There are scenarios where some clients are still using old technology, such as the mainframe. However, for data quality, they mainly deal with the latest tools, such as Snowflake, the cloud database, Azure, Google, and AWS. Informatica has not considered the old version of the software for SaaS applications. The integration with older technology and cloud quality needs improvement.
Informatica Cloud Data Quality could improve by adding more algorithms for matching and mastering. We currently only have five or six. Additionally, the parallelism in data is better in other solutions, such as IBM.
Some capabilities from the cloud version are not included in the on-premises version, such as the ability to create dashboards that show the whole of the metrics and the metrics of quality of the information you are analyzing. I would like to see these capabilities included in the next release of the on-premises version.
Principal at a computer software company with 11-50 employees
Real User
2021-08-24T20:48:13Z
Aug 24, 2021
I used to use Informatica Cloud Data Quality more but recently we have been using another tool that we feel is better because it handles spatial data. Informatica Cloud Data Quality could improve by adding the ability to handle spatial data. When I build the workflow and rule configurations, they could improve by making the process easier. You want to automate it and not have to manually do it.
Accessing data as a service is essential, especially for validations requiring external data services. This goes beyond basic syntactic checks, like ensuring an email address contains the @ symbol or .com domain. Instead, it's about advanced validation, such as verifying if an email address exists or if a phone number is valid. These services are in high demand, especially for regions like China, Argentina, and other parts of Latin America. While such capabilities were initially more common in the United States, they are now increasingly required globally.
We have complex datasets. Logical views are a little bit behind in comparison to the on-premise version.
I think Informatica Cloud Data Quality is one of the more mature cloud products, so I can't think of any areas where improvements are required. Informatica Cloud Data Quality is a product that is very similar to what Informatica offers for data quality on-premises, so there aren't too many gaps compared to the others, and I can't really think of any area requiring improvements. I would like Informatica Cloud Data Quality to offer more integration capabilities with different platforms. I need to consider the fact that Informatica Cloud Data Quality supports a lot of the standard protocols for which most platforms use endpoints. In short, integration is not really an issue with the product. The high price of the product is an area of concern where improvements are required.
Informatica Cloud Data Quality provides many of the capabilities found in on-premises solutions. While the cloud edition offers additional features, it has also deprecated certain functionalities, such as connecting to web services. In the on-premises version, features like web service consumer and web service provider are available, but these functionalities are currently unavailable in the cloud edition. Vendors offer options for custom solutions, although they may not offer the same functionality as the on-premises version.
With the on-premises version, we had many abilities to connect with any kind of server. But when it comes to cloud data quality, there are certain limitations to connecting. For example, we may be using an AS400. There are scenarios where some clients are still using old technology, such as the mainframe. However, for data quality, they mainly deal with the latest tools, such as Snowflake, the cloud database, Azure, Google, and AWS. Informatica has not considered the old version of the software for SaaS applications. The integration with older technology and cloud quality needs improvement.
Informatica Cloud Data Quality could improve by adding more algorithms for matching and mastering. We currently only have five or six. Additionally, the parallelism in data is better in other solutions, such as IBM.
Some capabilities from the cloud version are not included in the on-premises version, such as the ability to create dashboards that show the whole of the metrics and the metrics of quality of the information you are analyzing. I would like to see these capabilities included in the next release of the on-premises version.
I used to use Informatica Cloud Data Quality more but recently we have been using another tool that we feel is better because it handles spatial data. Informatica Cloud Data Quality could improve by adding the ability to handle spatial data. When I build the workflow and rule configurations, they could improve by making the process easier. You want to automate it and not have to manually do it.