Informatica Data Quality Reviews

We don't use profiling as much, however, we do use it, in certain cases, for profiling. We use the Analyst tool to do out-of-box, high-level profiling of data to see high-level quality of completeness, and uniqueness, et cetera. Mainly, we use the Developer tool to connect to the sources and to write data quality rules.

It has improved our organization. 

We started from just pretty much having flat files, and then doing some basic transformations, then writing back to Excel or QFD files. 

We gradually moved to more analytical tasks. You don't just do statistical data quality you also do analytical. You do lots of joins with other sources and do the consistency checks, and to do more complex logic, and build metrics. 

We use Tableau on the back of it to present the data and data quality, and then monitor it. We use it more like a batch process to build pipelines, and then, using Tableau, monitor the results of it and those metrics. Now, we work more with live updates and do that more than the batch.

It's probably one of the leading lights in ETL. They have really good built-in functionalities, or algorithms, that you can use to transform or process data and validate and standardize.

The solution is stable.

It's not too had to set up the cloud version. 

Support is helpful and responsive. 

We are in this transition mode, where we haven't yet got IDMC, the cloud version, so we don't actually have hands-on experience and have not actually seen the features. All we rely on, at the moment, is just the available documentation. What I don't like on the IDQ side is just the fact that in the on-premises version, you have all these applications, with separate configurations. In the cloud solution, it is fixed so that you have everything on one platform.

The performance isn't as good on-premises. For example, when you install clients, it's slow compared to the cloud. Still, we need to see. We haven't experienced it ourselves. 

The upgrades are a downside. On-premises you manage all the changes in the software. You have to do that yourself, and if there's some problem with compatibility, it makes things that much harder. With the cloud, everything is managed by Informatica on the servers.

Managing the licenses with the on-premises version was difficult. However, with the cloud, it will be much simpler. 

I've been using the solution for the last six or seven years. 

Once you set everything up, it is pretty stable. It's reliable. There are no bugs or glitches and it doesn't crash or freeze. It is way more stable than Hadoop and other applications. 

In terms of scaling, we used the clusters, and the processing was on Hadoop side. If we needed any extra space or any service, it was just managed there, so it was outside of Informatica.

Originally, we had 20 people using the solution, and then it was reduced to less than ten.

We do use it as much as we can for its purposes. In the past, we used that for the whole ETL process with data loads, and then we moved to Hadoop storage. At the moment, we are only going to be using Cloud Data Quality and others for cleansing, standardization, and deduplication, and then using some other Azure capabilities.

I've dealt with support in the past. There were issues, and we had to deal directly with Informatica for some hotfixes. They were good. They just got straight to the point and were helpful overall.

Positive

It is way more complex to install on-premises than in the cloud.

With the cloud, the installation will be way easier since you only install these secure agents. They have many different connectors, so it is definitely less hustle to install all these machines, and all these applications. On-premises, it was more user-based. Now, it's service-based, and you just pay for what you use and the licenses as well. 

We had myself, an architect, and a developer as well as help from Informatica while handling the setup.

We have about two or three people that can deploy and maintain the solution. They also cover other applications, not just Informatica.

We had Informatica support, and we had an internal group of people with Informatica knowledge who handled the solution. For some parts, we were involved as well, and we handled them ourselves. 

We're still in the early stages of moving toward the cloud. We have not seen an ROI yet.

When you are using the on-premises version, managing the licenses is quite difficult. However, on the cloud, you just pay for what you use, and it's a lot easier. With the cloud, if you want MDM, you pay for it, and if you want PowerCenter, you pay for it; however, if you don't want it or don't use it, you don't pay. We'll just pay for Data Quality, as it has all of the features we need inside it. 

I'm not involved in the conversations around licensing and agreements. That said, my understanding is that Informatica is pretty expensive. I'd likely rate it two to two and a half out of five in terms of affordability.

We definitely considered others and had StreamSets used for some other purposes. The company that I moved out of was going to be switching off Informatica at some point due to licensing, et cetera, and they just chose to go to StreamSets with Snowflake for storage. 

I haven't researched enough about other products in relation to Informatica.

We are moving to the cloud version. On-premises, we were on version 10.4.2, and that moved to 10.5. Soon, we will be on the cloud.

We're using IDMC, which is not just Data Quality. It has governance, Axon, and other applications in it.

We're just a customer.

I'd advise people to research use cases before beginning. Companies need to understand what they are trying to achieve, figure out their requirements, and then appraise the solution. 

While Informatica is good in terms of Data Quality and is probably the leading option, you need to be clear about budget, et cetera.

I would rate the solution seven out of ten.

On-premises

We use it for various use cases, including data provisioning, data validation, continuous monitoring of data quality, and data standardization.

We have implemented both data profiling and data quality transformations for data validation. These are the two major components we rely on, with data profiling helping us understand the data's characteristics, and data quality transformations ensuring data validation.

Exploring the possibility of incorporating AI capabilities that can suggest additional rules would significantly streamline our data analysis process following data profiling. Many other tools offer this feature, enabling them to suggest rules, which can be generated with just one or two clicks.

I have been working with it for almost seven years.

Once it was implemented, we din not encounter any stability issues. I would rate it nine out of ten.

The scalability of the solution depends heavily on the design approach. Regardless of the tool used, the effectiveness of the data quality framework hinges on proper design. If the framework is not well-designed, it may not deliver the desired results. I would rate it eight out of ten.

We receive excellent support on a priority basis. I would rate it nine out of ten.

Positive

I would rate the installation and configuration process as moderately complex.

If it has been implemented effectively, I would say it is the best solution. When considering the use of the data governance package, combining Axon ADC and Informatica Data Quality together provides a comprehensive approach. I would rate it eight out of ten.

On-premises

Our primary use case for this solution is purely for data quality analysis.

It took us a while to teach our users how Informatica works and to help them understand. We are still learning together with them because it also took us a while to master the tool. The contractors that come with Informatica are good on the ETL side but not that good on data quality.

The features I find most valuable are the mappings and rules. I am also impressed by the solution's interface. I really like this solution, as it works very well.

The visualization is very limited. It's not modern age, it's not self-service BI. It only has three levels of granularity on which you can present data and that's not enough. What's more, we had a few problems with the configuration. At times we found it difficult to integrate with other systems, but it turned out that the problem wasn't with the solution but with our firewalls. We had a couple of bugs but they are all fixed now. 

Another feature I would also like to see is tagging. At this stage, we can't tag data in the database of the data source with particular data flows. This is a nice feature that other solutions have and that Informatica lacks. We have to analyze and store data in a database and then we have to analyze it again and go through the servers. This takes up double storage. So if the data could be tagged at the database instead, anybody who has access to this data will know if there is a problem with the accuracy or anything else.

I've been using this solution for three years now.

I don't think the solution is very stable because we have to refresh and restart the server at least once a month, or even more often. We couldn't understand what was causing this, perhaps we have a few bugs. But at times one team will be working and everything will be running, and then the other team will have some access issues. All we could do to fix this was to restart the server and then everything was up and running again. 

The scalability is very good. We have about 30 users and this may increase because our organization constantly needs more people, so people see the benefit because it's stable and it gives consistency. We will probably move to big data analytics and purchase their big data applications.

To be honest, we didn't really have any major issues yet but the technical support is good and they have a dedicated tech person assigned to us by Informatica to supports us. It works well because if we have a problem that our own IT team can't fix, they use Informatica to help them. 

I used IBM InfoSphere before but Informatica is much, much better; gold standard. There is no comparison. The interface and everything else is better.

The initial setup was very complex. It is mainly our own fault because we didn't go for the solution that was recommended by Informatica. We used shortcuts that backfired on us and we've been struggling for a year. In the end, we did exactly what Informatica recommended at the beginning and now everything works fine.

We have an integration team that is responsible for maintenance and deployment.

Informatica is very expensive. But luckily we got enough free licenses, so we are still within limit. 

Informatica has been the best solution for the past 10 years, but now there are new tools emerging. So maybe we will switch in the future. 

I would advise others to go for it because I love it. Maybe there are better tools, but I don't know about them. I would use it in conjunction with Tableau and Google Analytics for visualization. I would also suggest others to follow instructions during the initial setup and not to cut corners. Do the configuration exactly as Informatica suggests.
I love Informatica but I am not sure if it is value for money. Organizations that plan to increase their users may find it worth the money, but smaller organizations may want to use something simpler.

I will rate this solution an eight out of ten. My rating would have been nine if the solution offered tagging and if it was cheaper. 

We use this solution for data quality management.

We have matured as an organization with regards to better quality management, and we have evolved over time. This solution has had a positive impact on our efficiency, especially with regard to finance officers. They rely on the quality of data for customers and vendors so that they can invoice properly.

From a sales point of view, there are also improvements.

The most valuable feature of this solution is data profiling. We are able to set rules, establish a data quality management platform, and monitor the quality. These features are excellent.

I would like to see better visuals for business users, such as a dashboard where they can precisely track where problems are. You should be able to better visualize data quality.

We have been using this solution for about nine years.

This solution is stable.

The technical support for this solution is good. They have a good mechanism for support and I haven't experienced any problem with it.

Prior to using this solution, we did not use a dedicated product for data quality. Rather, we used a combination of other products. One of these was CranSoft, by BackOffice Associates.

We switched because this product was quite immature, not covering the governance part of it. It was more for data quality, only. 

The initial setup of this solution is pretty much straightforward.

The deployment should not be complex, although there are other factors that influence the time it takes to complete.

The suitability of this solution depends on your environment. If you need large scale data quality and rely heavily on different connections to ge the data, then you really need a good powerhouse and this is the best. But, for example, if you already have SAP in your organization then you may not need IDQ on top of it. There are different factors to consider.

This is a good solution, but I can't say that you can solve all of the problems using it. Informatica is focusing only on master data quality. In this regard, there is room for improvement, but it depends upon the use case.

I would rate this solution an eight out of ten.

We use Data Quality for healthcare projects, and although it's not its prime purpose, we also use it to extract data. Compared to PowerCenter, it's a little easier to use — we designed the mapping ourselves. In short, we use Data Quality primarily for extraction purposes.

Within our organization, there are 10 employees using this solution.

Seeing the data in the mapping itself is really nice. We don't want to extract the data and just see the flat file. With Data Quality, we can see the data very easily.

When running a workload, we can only use the command mode. We were expecting Data Quality to offer the same type of workflow as PowerCenter.  

Although we are very satisfied with the design of the UI, executing tasks with it can be difficult.

We have been using Informatica Data Quality for three years. 

Overall, stability-wise, it's quite good; however, we think PowerCenter is more stable.

Compared to PowerCenter, Data Quality needs some improvement. When we are dealing with large amounts of data for extraction purposes, it doesn't always work out — often we experience some memory issues here and there. Scalability-wise it needs some improvement.

Although the technical support is responsive, they often take a very long time to solve our issues. They are quick to solve second and third-level requests, but when it comes to first-level requests, their solutions become very vague and general and often don't bear any fruit — otherwise, they're good.

Deployment was quite straightforward. 

We have a long-term license. I can't really speak about the licensing as I don't know much about it.

I would absolutely recommend this solution to others. If you can afford it, then go for it. If it's out of your price range, then I would recommend considering an open-source solution.

overall, on a scale from one to ten, I would give this solution a rating of eight.

On-premises

We are using it for extraction purposes for some of our projects. We extract and test the data. 

It is very useful for testing purposes and designing mappings for small projects. If you go for IDQ in the mapping itself, you can see the data. You can then correct it, and test it so easily. 

It is working fine. It is also stable, scalable, and easy to deploy.

It can be improved in terms of performance and execution. I'm expecting better performance. It currently has some restrictions in terms of execution. For example, if we want to run it in the command mode and execute it, there are some restrictions, and we are facing some issues with a huge volume of data. These restrictions are not there in Informatica PowerCenter because we are able to execute a huge volume of data, and there are more ways to execute it. 

We have been using this solution for the past three or four years.

It is stable.

It is scalable. We have ten engineers who use it. 

We are getting better support with PowerCenter. Informatica Data Quality was developed later, and its support is not up to that level, but it is fine.

We didn't use any other solution.

Its initial setup is straightforward. We just need to create data integration services. The deployment generally takes up to three hours, but it can take longer depending on the nodes.

I did it myself.

I would recommend this solution. We have a long term license, and we plan to keep using it.

I would rate Informatica Data Quality a seven out of ten.

On-premises

Data cleansing and address validation are the most valuable features. Also the web services which can be called on the fly. Data Duplication plays a very important role.

It has improved the customer data management where we had the incorrect addresses and data cleansing. Also in finding the duplicates so as to ensure the customer data is not duplicated.

Asia pacific region address validation needs to be improved.

3 years

None

None

None

Customer Service: 4 out of 5Technical Support: 4 out of 5

We previously used Firstlogic as a data quality tool. We found that Informatica is more feasible and user friendly than Firstlogic.

In-house.

Yes. Trillium.

Our primary use case of this solution is to improve issues of security, quality and accuracy. 
We are partners of Informatica and I'm an architect. 

In terms of Data Quality, the feature most valuable to me is that the solution is applicable for both technical and business users. I like that instead of using on-premises processing power, you can now use your on-cloud platform processing power to process the data and get a faster turnaround time. From a product perspective, everything is well done. 

I think improvements can be made regarding the ability of the product to leverage the power of big data. It would also help if we could get the software as a services product so that we feed in the requirements and it's a more customized solution. I think that would increase the adoption by customers. 

I've been using this solution for three years. 

Informatica is a very stable product, I haven't had any issues with it. 

It's a very scalable solution and it has all the other big data components. 

We have a business partnership with Informatica and they are very responsive. 

I've had a lot of experience with this solution so I don't have any issues with implementation. Perhaps someone from a different background or different circumstance, may face challenges but it is user friendly so it shouldn't be a problem. Implementation generally takes about six months depending on the dimensions required. This solution cannot be implemented in a day or a week.

The pricing of this solution is definitely at the higher end and they don't provide the option of a trial version. If you look at Talend, for example, they provide a free version, so the cost of IBM and Informatica is a little high. 

The cost of the product is high, but feature wise, it provides a whole lot of features that can easily solve your problems. I would recommend this product. 

I would rate this solution an eight out of 10.

Hybrid Cloud