Informatica Intelligent Data Management Cloud (IDMC) Reviews

I am not quite sure that the product will be part of our use cases anymore. We started off with it because of the data lineage. In other words, we used it because we also used the older Informatica program and it had been serving a purpose for us as a data management tool. But now we are in the process of developing our own solution for at least part of that functionality.  

We currently plan to keep Informatica MDM, but not for the complete handling of the data analytics. We use MDM for data gathering in big data environments. We start with Informatica and do further analysis outside the product.  

I think the most valuable part of Informatica is the flexibility in extending the data model. I think that is the biggest benefit. The data quality component is also an important part of it.  

I have begun to lose track of what needs to be improved because we only use the product now for what it is best at and in those areas it does not need improvement.  

There are two main things and that make up the complete Informatica suite solution. One is the insight into the data lineage which was a huge promise made by the product, but one that it never delivered in practice. That was the big problem that we are trying to solve in another way. The second part of the solution, especially for MDM is its ability to use the data by integrating with other process engines.  

So the insight into the data or the data analysis part needs to be improved.  

I have been using Informatica MDM (Master Data Management) for about two years now.  

Informatica has been stable. It does not have downtime during processing.  

I would say that Informatica is scalable. Right now we have about 20 people using the product directly. The scalability would be in the volume and types of data it can scan and collect and it is good at performing these services.  

With technical support, there is a big gap between sales, presales, and support for the end-users. Like with the data analysis the process starts good but in the end, there is no delivery. There are too many promises and too little delivery. So the support could be also improved after the sales, or I would say that the post-sale support should be improved to be in alignment with the pre-sale support.  

Informatica is definitely not easy to install. In order to do the installation and to set up the whole program, I would say it is complex.  

On a scale from one to ten (where one is the worst and ten is the best), if I were to rate Informatica MDM and I had a review site, I would mark it as a seven-and-a-half out of ten possible points. It has not delivered on all it has promised.  

We use the solution for cloud-to-cloud migration so our clients have all applications and data on their Oracle solutions, and we move it from there to AWS cloud and then to Salesforce. We're an implementation partner with Informatica and I'm the senior technical architect in the company. 

The connectivity and their whole suite are valuable features. Whether we need data cleansing or data mastering, we get it all in one platform. There's no need to test different cloud vendors and then integrate with one solution. Informatica is a one-stop shop.

The one thing that I think could be improved is connectivity with the Salesforce because if you're loading a huge amount of data, whatever optimization is carried out, takes some time and it could be a little faster. 

I've been using this solution for a year. 

We had some very minor issues initially, but the product is stable. We haven't experienced any down time. 

We've just completed the first part of the implementation. In the upcoming months we plan to carry out multiple implementations and then we might see some challenges in the scalability. I think it will be fine. I have about 35 users in my team - around 40% are developers, 30% are testers and QAs and then a few are designers, data modelers, and architects.

The way we carried out our transformation was throwing some junk value as an output and that meant we had to reach out to Informatica to see what kind of configuration changes might be required. They were pretty quick to respond and knowledgeable about the issue, and dealt with it very well. 

The initial setup was very simple and took a couple of days. AWS provided everything for us. 

We initially wanted to build the programming language in Python but the client's needs made us realize that Informatica was the way to go. Our initial design was something different and it was the cost that put us off going with Informatica as a first choice. If we had worked with something like Python, it could possibly have been more scalable and the cost reduced.

If cost is not a issue then I would recommend Informatica as the tool of choice. 

I would rate this product an eight out of 10. 

Our primary use case is connecting to the AWS S3 buckets and AWS instances in the cloud, extracting data from on-premises, and pushing it to the cloud. I think that's a perfect use case for Informatica Cloud.

I do a quite a lot of data transformations, and the fact that I can do them without changing any of my SQL queries from the code, using the inbuilt tools, is very helpful. Very few tools outside of Informatica have the ability to do that.

I would like to see support for more data sources. At this point in time, I'm not sure if they are supporting Microsoft Azure or Google Cloud, but continually adding new data sources is one area that they can improve on.

The deployment could be somewhat simplified. One drawback is that you need a separate server for it. However, from an enterprise point of view, it is worth it because the product is good.

I have been using Information Cloud Data Integration for about one year.

I have had no trouble in terms of stability.

The scalability is quite good.

Informatica has a strong support team and they are very good.

The initial setup is complex. It isn't easy because it needs a separate server of its own.

My understanding is that Informatica is quite expensive compare to other tools that are available in the market.

I am a fan of Informatica and it is definitely a product that I recommend because of its inbuilt capabilities. At the same time, I would like to see more data sources added. Inclusion of support for Azure and Google Cloud would be a game-changer, wherein companies can move their analytics capabilities to the cloud instead of being on-premises.

If you have the money then you should implement it. Otherwise, there are many open-source tools in the market, although you will still have to invest quite a lot in terms of resources because the individual transformations still need to be built.

I would rate this solution an eight out of ten.

The primary use case of this solution is centralizing and mastering the data. It is also used for centralizing the data between your administrator and customer.

The most important features are the mastering of the data and the UI intuitiveness.

I find this solution to be the most efficient, immersive, and robust.

Also, they have a feature map that is flexible and robust.

They need more feature flexibility, as it is not fully developed.

I have been using this solution for approximately 11 to 13 months.

I have not contacted technical support. We have a team in our company for support and maintenance.

My advice for anybody who is implementing this solution is to see the business needs and the requirements.

I would rate this solution a seven out of ten.

Our primary use case for the solution has been in some of our smaller pilot projects.

One of the main valuable features is the user interface which is very easy to use if we have any problems to solve. We don't need to install any client machines to do this, we can access from any machine. 

For the past six and a half years I also worked with PowerCenter, so I used to see the big icons and it's very easy for me to do. But with moving to Cloud there have been some challenges but it's getting better. We are able to connect to a lot of structured data, there are a lot of provisions. 

The user interface could be more user friendly with a simplified mapping task. In general, improvements could be made in mapping. When we create mapping from uploaded data, I'd like to see integrational mapping. I possibly need some extra time to grasp it all but a general improvement in icons and the virtual interface would be good for us. We are working as developers and we're working with the solution on a daily basis so any improvement would be good in this area. 

As far as my knowledge base goes, I feel pretty good with the stability of the product. 

I think technical support is awesome. Initially it feels challenging connecting with IACS, but I am able to get assistance and then apply it immediately. I feel like we're always getting good support from Informatica, even when there are technical challenges, it's one of the best things about the solution. 

I would rate this product a six out of 10. 

We have a lot of applications with different functionality. We use Informatica mainly for sensitivity tests. 

The most valuable features are the structure masking and platform masking. 

I also like that for Salesforce integration we can use Informatica Cloud. For on-premise, normally we do the SQL server database.

I don't see where it has much room for improvement. 

I have been working with this solution for the last two years. 

We have a team of 10 users on-premise. Their roles are doing the initial analysis for identification.

We don't currently have plans to increase usage. 

I would rate it a seven out of ten. 

It's not a perfect ten because the data discovery isn't that good yet for Salesforce. We have another tool that we use for this. It may be a problem because Salesforce on the cloud. 

We provide services mostly to banks. 

I am currently working at a bank where they are using Data Masking and Data Transformation at the same time. They are an old core banking system, which is COBOL, and it's unstructured data. We are using Data Transformation to transform and structure the data into a relational format.

We use the test data management to create test data from the relational data. To create the test data, we mask using different techniques for the discovery. After that, we re-transform the relational data into unstructured data to be fed into the core banking system.

The most valuable feature is data discovery. This is the most exciting feature for all of the banks.

I have encountered some issues using the substitution, which is one of the techniques of data masking. I used the substitution and software. I had issues in both when using the field, and specifying the field. Each one will have the same data for the same person, and they will have realistic data each time. This issue was raised with technical support and it was flagged as an issue that had no solution. They have indicated that it is a bug that would be resolved in the next release.

In the next release, I would l like to see the bug with the substitution resolved.

I have two years of experience with Informatica Data Masking.

This solution is stable and we have not had any issues.

Informatica Data Masking is scalable.

The technical support is good, although sometimes they don't respond quickly. Overall, they are good.

I raised the case where I was having some issues with the substitution, and it took two months. Finally, the answer was that they have no solution for this, but said they will flag it as a bug to be resolved for the next release.

As I was not able to stop the project because of the bug, I created a workaround using PowerCenter to make it work. The data was not unique. I used PowerCenter and added an ID to all of the columns, then I concatenated the ID with the columns. As an example of why this was complete is if my name is Donna, it will show as Donna123. That way, any other person named Dana in the same database or table would show as Donna246 and they would no longer be the same. With this, I would then offer a substitute.

Previously, we did not use another solution.

The initial setup is straightforward.

The length of deployment depends on the solution. For example, I find security was very easy, but the data integration was more complex. This is because it has many features and you can do many things. Setting up the data quality was also very easy.

We have deployed both on-premises and on the cloud. Mostly, I work in Lebanon and some  Arab countries also. There have been some issues with the Cloud, so they prefer on-premises software. We implemented some iPaas on the Cloud for Data integration.

It's good as a solution.

I would rate this solution a nine out of ten.

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.

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.