Informatica Cloud Data Quality Reviews

I use Informatica Cloud Data Quality in my company, as most of our customers have data from different systems and just want to standardize and enrich that data. If you have data like cell phone numbers, it is important to ensure that there is a consistent format to adhere to, like the area code, IDs, or social security numbers. The tool also helps users check email addresses because sometimes a user may find that their data has an incorrect email address. A lot of the use cases related to the tool involve understanding the data from all of the systems and starting the journey to unify some of those data fields, having some consistency in how the data is being captured, and helping look at the completeness of the data. In short, the use cases are to understand the data from different systems and different sources generally. Data could come from the CSV, a web service, or out of the database, but Informatica Cloud Data Quality allows you to extract from all those sources to give you a unified interface to decide how you want to customize and standardize the data.

The most valuable features of the solution stem from the fact that the product's integration capabilities are easy to work with, along with another feature, the name of which I forgot, but I know that it helps users to compare the quality of results from two different points in time just to see if there have been any improvements.

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.

I have been using Informatica Cloud Data Quality for a year and a half to two years.

Stability-wise, I rate the solution a ten out of ten.

It is a cloud-native microservices-based product that can manage a lot of data. Scalability-wise, I rate the solution a ten out of ten.

Though at the moment we are not currently using the product in our company, a while ago, around 15 employees used to use the product.

The solution's technical support was good. There were no issues with the solution's technical support.

I have experience with Informatica Intelligent Cloud Integration Services.

The product's initial setup phase was easy.

To get the product running, you just need to switch it on, so I don't think it takes more than a day. After deciding the sources from where your data would come from, you can decide if the cloud needs Informatica Cloud Data Quality while ensuring that nothing gets installed on the server, but the only thing you might need is a secure agent on your machine and that is really quick to set up on a virtual machine, which I feel won't take more than a day.

The solution is deployed on the cloud.

I can't remember the deployment process of the product since I am currently working in a different space.

The product's deployment was carried out with the help of a consultant, an integrator, and our company's in-house team. A consultant would be useful to guide a customer, but typically, customers tend to want some hand-holding and someone who can look towards them. Once someone shows the customers of the product how to do the deployment process, then they can do it themselves.

I have seen some benefits from the use of the solution in my organization.

It is a tool that is easy to trust with your data. The tool's service provider also ensures customer experience satisfaction from the use of the product. In one of the use cases, the tool helped the user identify which systems would be decommissioned because of the outdated data that the user had, and now that the user has updated everything, it should be much easier to cut down on those systems that they don't need to use.

The licensing costs attached to the solution are pretty high, but then, with the cloud model, the prices depend on what it provides for the value of money, which I feel was very high.

Those who plan to use the solution should conduct a pilot or proof of concept before choosing the product to understand the tool and also present the facts of the business because it will be much easier for a normal user to understand the purpose and the value that the product provides in an actual or real case scenario.

I rate the overall tool a nine out of ten.

We utilize it for two tasks. The first involves collaborating with our business team to identify specific data quality issues, and this part of the process runs smoothly. However, the second task is focused on using Informatica to investigate data issues that aren't entirely clear. This aspect doesn't yield satisfactory results, and we struggle to effectively pinpoint the problems using the tool.

When discussing data quality within IDMC (Informatica Data Management Cloud), it involves several modules, including CDI (Cloud Data Integration), CDP (Cloud Data Profiling), and Cloud Data Governance. Initially, we focused on Cloud Data Integration, which was the aspect we were already familiar with. We encountered challenges when trying to explore data quality issues using Informatica. We primarily used Cloud Data Profiling to connect with Cloud Data Governance, a tool also used by Teva. This integration allowed users to access data quality results within the data governance catalog.

We are currently working on improving the user interface for our end users. At the moment, our end users do not frequently connect to Informatica for data quality because they have trouble locating the results within the platform. The remediation processes are not adequately supported within it, and we cannot easily assign data quality issues to specific individuals, nor can we send the entire results to anyone via email. While we can send reports via email, we lack the capability to attach the actual results or provide links to them. We have been suggesting these improvements to Informatica, but as of now, we have not seen any significant progress. If given the opportunity, I would like to address these concerns, particularly with regard to enhancing the end-user experience. Also, there were initial architectural misalignments with the product. We believed that Informatica could directly connect to the source systems, but while it is technically possible, doing so would significantly impact the performance of the source systems. As a result, we did not receive approval to connect directly to them, and we did not plan to maintain copies of these systems.

I have been working with it for one year.

I would rate the stability of the platform seven out of ten. We have faced a recurring issue after each quarterly upgrade or new release in their cloud platform. This problem involves the functionality that used to work correctly no longer operating as expected.

I would rate its scalability capabilities six out of ten.

Overall, I would rate it six out of ten.

The solution is used for data quality implementation. We handle the whole life cycle of data quality from end to end, including rule specification and exception handling.

We're seeing more productivity. The tool provides accelerated libraries that we can use instead of building things from scratch. It's looking very promising from a productivity perspective.

The profiling features are much better than the on-premise version.

We have complex datasets. Logical views are a little bit behind in comparison to the on-premise version.

I have been using the solution for less than three months. I am using the latest version of the solution.

The product is very solid.

I rate the product’s scalability a nine out of ten.

The technical support is very good.

Positive

We have used the on-premise and SaaS versions of the solution. All our on-premise infrastructure is in Informatica. It was a natural move to Informatica Cloud Data Quality. It was easy.

The initial setup is quite straightforward.

The pilot is not in production. It's in a lower environment. We are not at the stage of doing performance testing until the new year. We are not fully utilizing our on-premise infrastructure. Moving to the cloud could save us some money.

People wanting to implement the solution must consider it like launching a new data management program from scratch. Rather than just thinking about migration from on-premise to the cloud, try to adjust your mindset to use the solution as a completely new tool. If you just migrate from the on-premises to the cloud, if you have any technical debt in the on-premise version, you'll just replicate that into the cloud.

Overall, I rate the product a nine out of ten.

We use the solution to validate emails, telephone numbers, and postal codes. It can also create some data quality rules using the Cloud app's data quality function.

It offers enhanced usability with the ability to create rules quickly using its AI engine. This feature simplifies rule creation by allowing users to specify their needs, and the system generates the necessary scripts, acting as a significant accelerator. 

Another advantage is its seamless integration with other Informatica capabilities, making data quality a deeply embedded part of the solution. Informatica has a strong history in data quality with its on-premise product. All those powerful capabilities are now available in the cloud, making this product even more robust.

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.

Five to six people are using this solution.

Informatica Support is one of the best services available in the market now.

Positive

Many clients acquired this product because of the ROI.

Informatica is one of the most expensive solutions available in the market.

Overall, I rate the solution a nine out of ten.

We've 300-400 data quality rules and different kinds of rules for completeness, conformity, and timeliness. We're using Informatica to implement those rules in Cloud Data Quality.

Informatica has CDI. So, if you find some issues, you can always integrate your CDI and then fix your data.

The reusability factors are nice. The Cloud Data Quality is much better. A major flaw in the previous version was integration with the catalog, which is now seamless.

I have been using Informatica Cloud Data Quality as a partner for three months.

I rate the solution's stability a nine out of ten.

We want to keep costs down, so we are not getting enough resources.

It is suitable for enterprise level.

I rate the solution's scalability as nine out of ten.

Support response time could be better.

Positive

I use Collibra Data Quality. I switched to Informatica because Collibra cannot integrate. Colibra Cloud Data Quality is a very basic tool. There is no integration capability. If you have problem records, there is no fix to remediate them using the same tool. With Informatica, you can integrate with CDI and then create a remediation plan.

The initial setup was straightforward, and we were able to start configuring the rules quickly, etc.

It took about half a day to deploy since we are also learning.

There are different tiers based on consumption, but there is no flexible option. The catalog grows slowly over time. It would have been nice to use a flexible feature at the beginning and then transition to a model where you have a fixed set of units that you consume and pay for. If you exceed those units, you move to the next tier. We were expecting a flexible pricing structure, which we did not get.

We would have preferred a pay-as-you-go model. Although pay-as-you-go is slightly more expensive, we know our consumption will not be high initially. 

It is easy to integrate cloud data quality with IT workflow. We haven't faced many challenges. It is fairly straightforward.

I recommend the solution. 

Overall, I rate the solution a ten out of ten.

We have a lot of data from multiple vendors spanning multiple years. We want to have one unified final data standard, rather than searching around to do the quality check. We have a data governance process to make sure we have the proper data. In order to do that, we use some tools, such as Informatica Cloud Data Quality to bring the data together and to do the quality checks.

One of the most valuable features of Informatica Cloud Data Quality is Master Data Management. You can write code to build your logic rules to check the quality. 

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.

I have been using this solution for several years.

The solution is stable, it has been around for a long time.

The solution has been scalable for the amount of data we have been processing.

We are a large company and a long-term customer, the support we have received has been good.

I have evaluated other tools.

This is a good and very valuable tool, but it has some drawbacks and there are other alternatives.

I rate Informatica Cloud Data Quality a nine out of ten.

We are using Informatica Cloud Data Quality for data quality operations.

The most beneficial feature of Informatica Cloud Data Quality is it's cloud-based. 

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.

I have been using Informatica Cloud Data Quality for approximately six months.

Informatica Cloud Data Quality is stable.

We have approximately 200 people in my company using this solution.

I have used IBM solutions similar to Informatica Cloud Data Quality.

This is a good data quality tool. I can't comment more because I have not used the solution extensively.

I would recommend this solution to others.

I rate Informatica Cloud Data Quality an eight out of ten.

We are working with our clients to help them build a data governance product for their enterprise data warehouse. By using Informatic EDC, Informatica Axon, and Informatica Data Quality, they can ensure the quality of their data governance.
Here, we are sharing the data with the consumers. We are using automated tools via Axon to ensure that the quality of data is good and that it is trustworthy. The average threshold for good-quality data is above 85 percent, so we have set a conformance threshold. Data quality is important when scanning data in Axon. We can determine the quality of the data and, if necessary, reach out to the data storage to correct it. Cloud data quality is important in this process because it can correct or reference data.

The most valuable feature is the rule specification. This is where we can define the rules and have our clients verify our transformation. The rule specification is a major transformation used in cloud data quality and especially in rule specification, we can create the business logic. If our business case or our use case deals with any kind of address verification, then we can go with address verification transformation as well.

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.

I have been using the solution for one year.

The solution is stable.

The solution is scalable. We just need to add more licenses.

The technical support is good.

Informatica Cloud Data Quality is a cloud service. All we need is to have a secured agent installed in our local machine or in the VM. Once that is done we get a license and when we have a run time, everything is easy. Since this is a cloud service, we don't need to worry about maintenance. But there are some hurdles in data quality, such as if any one of the services goes down due to reports of our database being full, and there are multiple conditions. So there are pros and cons when compared to on-premises and cloud, And for maintenance, the cloud data quality is the best fit when compared to on-premises. The initial setup is simple.

We pay for a yearly subscription.

I give the solution a nine out of ten. I've been working with Informatica solutions for the last decade. I have worked on other ETL tools as well. But always, Informatica stays close to my heart.

I've been closely working with Informatica's salespeople across the Asia Pacific. Right now, Informatica is pushing all the cloud products to the customers, not the on-premises. Informatica has everything in the cloud except data privacy management. They have canceled or they have stopped the data privacy management of on-premises itself. Right now, Informatica has end-to-end solutions in the cloud. They have all the services starting from data integration, and they have application integration. If it is a web-based application integration, We have CAI cloud application integration. Informatica has a data catalog, data quality, and master data management. They have everything in the cloud. Right now, all the clients are pushing only cloud products to their customers.

Depending on an organization's business requirements and budget, I can recommend Informatica Cloud Data Quality.