Informatica Intelligent Data Management Cloud (IDMC) Reviews

It can be used for different kinds of use cases. You can use it for data deduplication purposes for any industry. For example, in the pharma, healthcare, or life science sector, often a lot of medical data gets duplicated across different business functions of the enterprise. As a result, the sales and marketing channels may face a lot of challenges in marketing their medicines to the right physicians. In such a scenario, Informatica MDM could be really helpful in standardizing the data and creating a golden copy of it, which can then be published to the sales and marketing channel so that the sales representatives have accurate data to market their medicine or product. This is one of the use cases.

Its deployment depends on the project and client requirements. I don't have Informatica MDM deployed for my organization. We build solutions for our clients by using Informatica MDM. So, it entirely depends on what a client wants. For some of the projects, it is deployed on-prem, and for some of the projects, it is deployed on the cloud. In the most recent scenarios, it is mainly on the cloud. Informatica, just like other MDM solutions, is also moving toward the SaaS platform. So, I'm sure that going forward, for any kind of project opportunity, we'll be using the SaaS model when it comes to the deployment of Informatica MDM.

The Provisioning tool is something that is really handy for everyone. It is my pick as the best feature.

It is a very mature tool. It has been in the market for more than a decade.

If I compare it with other MDM solutions in the market, one thing that can definitely be improved is automation to help with the configuration. Currently, when we are creating any staging of base object tables, all the columns have to be configured manually in the Informatica Hub Console. A lot of tables and different kinds of business columns have to be configured manually. There should be an automated process for this, especially in the Dev environment. When people are creating tables and columns from scratch, if there is a backend automated process for that, it would be really helpful. In Stibo, a similar feature is there wherein you can tag attributes to certain objects. It would be helpful if Informatica also provides a similar option. It would reduce the manual effort. It could be that such a feature is already there, but I am not aware of it.

Their support can also be improved. They sometimes take long when an incident is not a priority incident.

I have been using Informatica MDM for the past five or six years.

It has been in the market for more than a decade. Over the last decade, Informatica has proved to be the best MDM solution that is available in the market. Informatica is one of the leaders as per Gartner and Forrester. There are no second thoughts about the stability of the tool. It's definitely the best one in the market right now.

I would rate them a four out of five. There is definitely room for improvement when it comes to technical support. Sometimes, when an incident is not a priority incident, they take their own sweet time to meet the SLA. For a priority one incident, they jump in and resolve the issue really fast. 

For someone trying it for the first time, it would definitely be a little bit complex, but once you get used to it, over a period of time, the complexity reduces. With experience, it becomes easier.

The deployment duration depends on the complexity of the configuration and the complexity of the import configuration on Informatica MDM. There is a feature called import where you get the chance to import it from the lower environment to a higher environment. The import process is pretty straightforward, but sometimes, when very complex configurations are done in the lower environment, it can get a little bit complicated to import the delta changes. It can take a while. 

Its maintenance isn't a big headache. For on-prem deployments, the maintenance is pretty easy and straightforward. It is not a very big overhead. With the SaaS solution, there is no overhead at all.

It was done in-house. There was no third party.

There is no doubt that it is very expensive, but the brand value comes at a cost. Other MDM solutions in the market that haven't proven themselves like Informatica are also pretty expensive. We need to understand that MDM itself is very expensive to implement. So, Informatica is also pretty expensive. I would rate it a two out of five for being pretty expensive.

One piece of advice that I would like to give to anyone implementing Informatica MDM or any other MDM solution is to be in regular touch with business users during the implementation. Because it's an MDM solution, it's business-driven rather than IT-driven. So, always stay in constant touch with business users or data stewards to best understand the data. Never try to make decisions related to the data on your own. It is always good to be in regular touch with business users and let them make the decisions. Based on their decisions, you do the implementation. Do not make any decisions yourself because the businesses understand their own data best, and they are the best decision-makers when it comes to their own data. 

I would rate Informatica MDM a nine out of ten.

Our clients need to perform data masking to comply with GDPR rules or the company's internal data security policies. Data masking restricts who can look at the private customer data. Informatica provides a comprehensive solution for on-the-fly or real-time data masking. 

One use case is masking the data for a test environment, so developers and testers can't see production data. This is something you have to do regularly with large amounts of data.

The second use case is in a production environment. Sometimes you need to mask the data on the fly when the data consumers are retrieving reports from the data platform. You are masking the data for certain groups who don't have permission to see that data. 

Informatica should simplify the rules for setting classifications and user access management permissions. It's too complex to define, configure, and make work.

One feature I would like to see is the ability to do data sampling when anonymizing a test environment. It would save you the trouble of having to replicate or perform complex configurations when moving to another environment for testing or development. You should be able to easily configure the data sampling when you are preparing an environment with anonymized data.

We are a system integrator, and we've been one of Informatica's biggest partners for around two years. My team integrates Persistent Data Masking for our clients, but I don't use it personally. I understand the product and its capabilities, and the clients give me feedback on it.

Persistent Data Masking is stable and ready to scale. It has to be. You are working with large amounts of data.

I rate Informatica support eight out of 10. Informatica provides standard support during deployment. A vendor that doesn't offer support isn't a good company. Informatica is willing to make a straightforward deployment because they care about feedback from the client. 

They don't mind investing some money at the beginning to make it run. They care about retaining clients for a long time. Client satisfaction is essential.

Positive

I rate Persistent Data Masking eight out of 10 for ease of setup. It's straightforward. You can deploy a proof of concept in three weeks. It takes two or three people to deploy, but one guy is fine for maintenance. Then again, it depends on the scope and how many anonymizations you have to do, but it doesn't require a big team.

It's usually a yearly subscription, but customers can go with a different pricing model. Typically, it's a yearly subscription for the cloud solution. If you're buying an on-premise solution, it's a one-time payment and annual license for support.

I rate Informatica Persistent Data Masking seven out of 10. 

I use MDM to collect customer information and ensure that there is no duplicate information on our system.

The most valuable features are that MDM has a very strong master merchant, and it's possible to model all kinds of domains in one solution.

An area for improvement would be that the pricing model is not very visible, which makes it hard to understand how much things will cost. In addition, the on-prem solution is harder to learn than the cloud-based versions. I also understand that Informatica is not porting their on-prem system to cloud, so I would like the new cloud solution to include all the features from the on-prem solution and make it the proper multi-domain MDM.

I've been using Informatica for around twenty-five years.

MDM is very stable - it can handle millions of hits daily and still run 24/7.

MDM is scalable with no problems.

As a customer, you can raise tickets, but you also have a Customer Success Manager in Informatica who is responsible for customers and helps them get the best value out of their investment. So you can raise your ticket with them, and they will help you with it.

The initial setup is straightforward on cloud, but the on-prem version is not so easy.

Don't underestimate how much work you will have with integration (though this is an issue with every MDM solution, not just Informatica). I would give this solution a score of eight out of ten. 

I use Informatica Enterprise Data Catalog for searching for PII data, tagging different kinds of data, and for data lineage.

These are the features I found useful in Informatica Enterprise Data Catalog: one is its data profiling is good. The data lineage is also okay, though it had a few issues to be solved. The data domain discovery for the solution is good, though it was hard to implement.

Informatica Enterprise Data Catalog is hard to set up, so this is an area for improvement, e.g. it would be good if they make it easier to set up, because the project was made 80% of the time of the setup. Another area for improvement is its ease of use, because the interface is not as user-friendly.

I've been using Informatica Enterprise Data Catalog for the last three years, and the last time I used it was three days ago.

Informatica Enterprise Data Catalog is not as stable.

Informatica Enterprise Data Catalog is an easily scalable solution.

The technical support for Informatica Enterprise Data Catalog is not so good, because it took a lot of time for them to solve simple problems.

The set up for this solution was not easy.

My advice to other people who want to implement Informatica Enterprise Data Catalog is that they need to be sure that it can deliver the expectations they have about the data catalog, because after our implementation, we weren't able to use it a lot.

I'm rating Informatica Enterprise Data Catalog seven out of ten.

The organizations I work with often have trouble getting buy-in from business users and understanding how data governance relates to them or where the data lineage is. We use Axon in two key areas. 

The first is automating data governance processes, policies, and roles in terms of data stewards, data owners, etc. Those process flow charts are typically stored in a PowerPoint, Excel, or board document. Everyone involved in data governance would have to send emails manually and such. Axon allows them to automate all that. So if there's a data owner that needs to update a definition, a request that needs to be flagged, or a data quality error, all that is embedded into the Axon system. That's one reason our clients go with it. 

The use case is embedding the data or the business glossary into the day-to-day workflow. For example, we could integrate it with Tableau. When people are looking at a Tableau report, they understand exactly what the data lineage is and where this data is coming from. They'll also know exactly what those business glossary terms mean, so they can more accurately interpret and analyze the report.

Axon does one interesting thing that I don't think other tools do as well. It lets you rate data and incorporates Informatica's data quality feature into it. There are little indications and graphics that show you how good the data quality is, and you can drill into it to see where potential issues lie. 

Users can comment on the data, tag people, and ask questions or rate the data one to five based on their experience, which helps eliminate data silos. You have all your information right there, and it's easier for future users to know which data to draw from.

The cloud version of Axon is far behind the on-prem, and many of my clients want to go fully to the cloud. However, Axon has to be an on-prem installation. I would like to see their cloud products catch up with their on-prem capabilities. 

I would like to see Informatica add more automation and AI. Some of that is already there, but it would be helpful to have some automation to speed up the process of manually tagging and moving components of your IT setup into your business glossary and the front end.

We started our first Axon implementation at one of our clients in the fall of 2021. Two of my other clients are about to purchase the technology and start using it.

Axon is stable. 

Axon is scalable.

Informatica support has been good. These data governance and metadata products are some of the newer products on the market technology-wise, so I've been impressed with their responsiveness and the tool's maturity.

Installing Axon is straightforward. If the cloud version were more robust it would be easier, but it's just fine for the on-prem solution. Two people should be enough to deploy and support it. 

I rate Informatica Axon nine out of 10. If you're planning to implement Axon, I recommend having an identified data governance lead. I think the most difficult part of implementing this is getting your people and processes aligned, so you know what you're putting into the system. Having a clear data governance manager is the most helpful data governance practice for an organization.

We use Informatica to extract data from production. It's mainly the configuration of the systems. We extract data from one site in the same system and mass customer data to the test system. It's a list of customers that is a subset of the data. 

In our CRM, we have data on our customers, and the data in that system is a copy of the production environment. We have all the configurations manually modified to work as a test, but we can extract only new clients, which is a problem. We need to have a CRM with only the configuration but not the customers. 

My plan is to make Informatica work with the CRM. If it works, I am sure that I can get the budget to make it work with other systems, but the first system that I need to work with is CRM. The other ones are less important and don't have the same impact of making it work with the CRM. We're at about 80 percent completion with this project. 

Informatica is user-friendly, stable, and scalable. These three aspects are the most valuable for us. If we can make it work well with the CRM, we can continue or try again this year to complete that part of the project. I am confident that this kind of solution is what we need because we have a third-party resource that works in the development. 

We need to have a lot of hardware infrastructure to make our test system work. We use a complete copy of the production environment for testing, which is a real problem for us. The problem is not with Informatica as a provider per se. It's more of an issue with our system providers, but we need support to complete the projects. That's our real situation. With the pandemic, we have undergone many changes that have slowed down these projects in the last few years.

We have the license to deploy Informatica on any system we want. Right now, we aren't using it as much as we thought we would. We understand the solution, but it isn't easy in some areas. One problem is we have systems in which we don't know all the relationships among the data, and we need support from our providers to get that information. That is one of our most complicated problems implementing it.

Informatica's support understands the solution, but they lack the experience we need for our use case. That was one thing that we prioritized when we started searching for this kind of solution. 

Informatica is working well, but we need access to the production databases to extract the data. The real problem is understanding the data in the system that we don't own or provide. Those are the most problematic to implement with this solution. We make it work with what our team has developed. Deployment took four to six months. Right now, we have one developer and two or three system administrators using Informatica, so it takes about three or four people to deploy and manage the solution. 

We worked with the team we used for all the installations. They made it work. I can say that wasn't as good as I expected when we purchased the solution. When we started the implementation, we understood that they didn't have the research that works in this project because we did a lot of work to understand the data from the implementation team. That wasn't what we wanted because we knew that Informatica would be the most complicated of all the systems we would implement in the extraction. After all, they are our clients, and almost all other systems depend on that system. 

We have a perpetual license for Informatica, and we only need to pay for support. However, because we're not actively using it at the moment, we don't have the budget to continue with the support.

We evaluated several solutions, including IBM InfoSphere Optim and Delphix. We purchased 15 licenses at the same time that totaled around $230,000.

I rate Informatica Persistent Data Masking eight out of 10. It's important to have a robust understanding of the knowledge you need in the system. That is one of the main problems that we have. You need firm control over the systems to do data masking. All of the data is a subset because we want to make the subset and the data masking, but you have to have good control over the systems. I think that is the key.

The solution is used for real-time validation of the addresses entered by end-users in the MDM solution and validation of the addresses which are received via the inbound interfaces. 

Apart from validation, this service is used to enrich the address data, for example, entered addresses include country, city, and street name. The service returns additional characteristics, for example, postal code (if it can be derived from the other attributes), which are then written back in the requesting system. It's used for Master Data Management in our case.

The overall quality of the addresses associated with other master data entities (Customer, Supplier, physical locations, etc.) has improved significantly. Addresses have now standardized format per country of origin - this means that addresses located in one country have a bit different template than in others. This is a consequence of the fact that Informatica uses various country postal authorities to provide the content used by the Address Verification service. As explained earlier, we use the results of AV service to enrich the address information in some cases. 

Due to improved quality of addresses, the user satisfaction of our MDM solution has increased. Also, the connected systems receive more complete data from MDM. Address Verification service helps in ensuring proper data governance of the master data which is used in many critical processes across the whole enterprise.

The product is easy to set up thanks to pretty good documentation. 

It supports several ways of using it (real-time, batch mode) and has testing capabilities. 

The pricing model is clear. 

The service returns good results which vary depending on the country of the address origin. In case there are multiple matching addresses, this service returns all of them which allows our end of the process or the end-user to select the best matching record. The speed of returning the validated addresses is really great.

The product is really good in its current form; it's hard to imagine what can be improved. It's easy to integrate via the exposed APIs, hence, also in this aspect, I don't see much that can be changed.

The only thing that I can imagine that might be improved is how the available transactions verify addresses used. These transactions have a valid end date and must be used within the agreed timeframe. Sometimes it's difficult to predict how many transactions will be required. In the worst case, some of them might be lost if not used on time.

I've used the solution for more than one year.

There is no single issue with the stability since we started using it (more than 1 year ago).

The scalability is very high.

We previously used Google APIs, however, that was for another client. Hence, there was no real switch as such.

The product is very easy to set up and offers good documentation.

We handled the implementation in-house.

I'd advise users to try to predict the expected usage of the service. The unused transactions may be lost if not used on time.

We looked at both Google and Experian.

We have it deployed on the cloud, but I don't think Informatica has been involved much with cloud-based solutions. They have multiple issues, especially related to LDAP and other configurations. Plus, their certified and supported versions are also not what every client has, so they're still evolving in terms of AWS. I don't think they have any support on Azure. They say that for the time being in the Azure setup, you can install MDM the way you would install it on-premise, but we don't have a built-in solution as they have for the on-prem database. That is my understanding for now.

With a Java user configuration, I will probably see 70 to 75 percent of the use cases met. I'm not talking about workflow integration. Instead of going to an active worksite, I'm managing everything from Informatica PowerCenter. I used to do those things, but now I'm just keeping my viewpoint specifically within MDM. I think with the configuration, you can achieve 75 percent of use cases. New tools are coming out that will enable you to achieve 90 percent of use cases with the out-of-the-box configuration, but I would like to keep Informatica tight here. Otherwise, you need a Java user edit course and other things to do multiple things that you cannot configure out of the box. They have to go through those use cases to do something if those can also be configured rather than coded.

We promote our code changes from a lower to a higher environment, which is highly complex when working with a multi-domain MDM like Informatica. This is the biggest obstacle for Informatica MDM, and I think they should change it because that's very time-consuming. You have to be very, very focused. Also, Informatica should develop a process where all the application servers are synced for people using multiple application servers. That's another significant drawback I've seen with Informatica MDM.

Informatica MDM's pricetag should come down. They have to cut some costs.

I rate Informatica MDM nine out of 10. It's one of the best tools in its class. It gets a high rating because of the improvements in the latest version. I was working on a very outdated edition that was seven to 10 years old. There were multiple issues, but they have made a lot of progress, especially in the newer version. For example, they moved away from DB to a different DB-sorted feature. 

We are customers of Informatica PIM and I'm a senior architect. 

Informatica comes with a predefined data model which is the way in which you enrich your products. It acts not only as master data but also as a product enrichment tool. The product provides flexibility; you can go for an undefined number of attributes that define a product. You can plug it in with any e-commerce website. That's its value to us and why we need it. 

Database access is highly restricted with PIM. If you're using the cloud version, you probably won't have database access or a view of it. If you're wanting a customized application, you can develop the out-of-the-box PIM solution with a little bit of customization here and there without even needing a database. That's a very big drawback. As a developer or as an architect, you need to have a data model. I know some people use it without database access and the issue is that they don't know what that data model is built on other than just seeing it through UI tabs. The one thing I'd really like to see is for the solution to be made scalable. 

The solution is stable, in terms of bugs they're very good. They keep evolving their toolset. I have encountered many bugs in Multidomain MDM, but to date not in P360.

Scalability depends on your use case. If you're using it as an integrator, then it is definitely scalable. That said, it would require an altogether separate MDM solution. If you don't have MDM, then there are likely to be some limitations. We're in the process of installing now but in my previous company, we created the core set of attributes through MDM. From there it went worldwide through an e-commerce website. We have 50 to 60 people internally using it as a tool. If you're exposing your data through an e-commerce website, then it's accessible to all, although just for reading and not for updates.

If you're working with Informatica, you need to interact with them on the out-of-the-box features. They are very efficient and quick in their response times. 

I've trained in Stibo which is a little bit better than PIM and I've used Oracle PDH and CDH. Those were basically a package MDM solution. If you're using SAP, I would suggest Oracle products. But there's been a very big evolution over the past decade when it comes to enterprise MDM tools. Most people working in companies are disbursed in different locations and using multiple toolsets, they can't be restricted to one technology. That's the reason that Informatica, Stibo, Riversand, and other technologies are very useful and very powerful. When comparing PDH to PIM or CDS to Multidomain, managing the Informatica toolset is easier in terms of effort required in comparison to managing Oracle MDM or Oracle CDH or PDH because they have their own set of limitations. The good thing is that they can be very easily coupled with an ERP solution. Here, you have to build real-time or multiple interfaces. 

The setup is relatively easy I would say. But if you need additional attributes, it gives you a repository manager feature where you can use XML, add your own attributes and then configure it. To my mind, the setup is simple to moderately complex.

Licensing costs are a little pricey. For my previous client, as a support contract partner, we were making less money than Informatica was charging them. 

Informatica 360 PIM was bought from Heiler and is a very good tool if you already have MDM in place and you simply want to use it as an enrichment tool. With Informatica, you perhaps need to go somewhere into the roots of Multidomain. P360, Multidomain, and C360 are all different things. Managing a thousand plus attributes into that data model is going to be very complex. If they could come up with a standard data model that Oracle offered customers like PCH or PDH, similar to what P360 has, that would be my preference. Also, my recommendation is to always utilize your team as an integrator rather than being a master data manager.

I rate the solution eight out of 10. 

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.