Informatica Intelligent Data Management Cloud (IDMC) Reviews

We used the solution for data storage, and data cleaning to improve data quality. The solution also served as a data lake for reporting purposes.

The solution has made it easier for us to retrieve and maintain the data as well as saves us time.

The ability to clean out data and improve the data quality is the best feature.

The solution is user-friendly and easy to navigate.

The cost of Informatica MDM is expensive and has room for improvement. Although the solution is good, it is not worth the high cost.

I have been using the solution for five months.

I give the stability a ten out of ten.

I give the scalability a ten out of ten.

We had ten people using the solution in our organization.

We previously used EXAScaler and switched because we were moving to the cloud.

I give the initial setup a nine out of ten. The deployment took us one month. We prepared the environment and the deployment was completed by the Informatica engineer.

The implementation was completed by an Informatica engineer.

The solution is very expensive. I give the cost a three out of ten.

I give the solution an eight out of ten.

The solution is good and I recommend it as long as the pricing fits the organization's budget.

We are using Informatica Cloud Data Integration in a large organization, and we have customers all across the world. 

Informatica Cloud Data Integration is for migrating data from a source to a target. The major advantage of working with this solution is that it can handle large amounts of data. The drawback is the performance is a bit slow but it can handle a large amount of data compared to other tools.

The most valuable feature of Informatica Cloud Data Integration is Pushback. You are able to push the data to the solution itself, and it can handle the queries. It helps us a lot. With other tools, the burden is kept on the server.

Informatica Cloud Data Integration can improve by being more user-friendly. When you're working with the solution a lot of technical knowledge is required. It's not a solution that anyone can use properly, you need knowledge of what's happening at the back end, such as SQL. When you get stuck, you need to look into your logic. For other tools, such as Dell Boomi, anyone can use them.

In a future release, the UI should be more developed to allow more features.

I have been using Informatica Cloud Data Integration for approximately four months.

Informatica Cloud Data Integration is stable. 

I rate the stability of Informatica Cloud Data Integration a four out of five.

There are some performance issues sometimes.

We have more than 50 developers using the solution in my company.

I rate the scalability of Informatica Cloud Data Integration a three out of five.

The support from Informatica Cloud Data Integration is great. They respond quickly and if there is an issue it can be resolved fast.

I rate the support from Informatica Cloud Data Integration a four out of five.

Positive

Informatica Cloud Data Integration is famously known for its high price. The vendor targets large enterprises, and not medium or small companies. These large companies, and organizations, handle large amounts of data. If you go into any large bank, such as American or Canadian banks, these banks use this solution because it is more reliable, secure, and has more functionality.

There can be extra changes, such as using the cloud.

I rate the price of Informatica Cloud Data Integration a two out of five.

This is a good tool and others should use it. This solution is known for its ability to handle large amounts of data and in the market, there are not that many tools available. However, there are competitors in the market, such as Oracle and IBM.

If an organization's data is very limited and they are not using large amounts of data, then I would suggest going for a smaller targeting solution, such as Dell Boomi. When it comes to large and secure data, I would recommend others to use this solution or SAP BODS or IBM.

Informatica Cloud Data Integration has a nice GDP rating and a good European market.

I rate Informatica Cloud Data Integration a seven out of ten.

I'm a senior architect and we are partners with Informatica. 

The solution offers good data governance.

I've found that whatever functionalities are available on-prem, can become a bit of a challenge sometimes in the cloud. There are no simple rules for customization so they need to be applied which is a challenge on the cloud side.

I've been using this solution for four years. 

Informatica stability is great. Even now, Purview has evolved a lot, but we haven't used it to the same extent. 

The solution is scalable. 

We are partnered with Informatica, so we don't have an issue with technical support. 

Positive

Our preference is Purview when we're asked for a cloud solution because it's a cloud native and the same applies when taking cost into account. Deployment is easier with Purview. If an organization is going for a hybrid solution and there's a lot of governance and complex rules involved, my first choice is Informatica. If that's not the case then I go for Purview.

Without experience, it may be somewhat difficult but I don't find it particularly complex because there's a lot of training and documentation available. We've already had a lot of experience so it's a piece of cake for us. 

Licensing costs are not fixed and I know that Informatica offers discounted prices to certain customers. Microsoft is cheaper.

The solution is suitable for enterprise or mid-size organizations. But if there are customer-related or different domain issues and it has some kind of regulatory impact and a lot of external agencies come into the picture, then it's always good to go with the Informatica Axon.

I rate this solution eight out of 10. 

A lot of times, we use it for basic profiling. That's its most common use case. Currently, we are also in the process of establishing a set of ongoing processes around Data Quality that would feed into and augment our current metadata. So, from that standpoint, our usage is primarily around some of the basic dimensions of data quality, such as completeness, conformity, consistency, timeliness, accuracy, etc. We measure each of those or at least create quality rules that measure each of those aspects. We're in the process of doing this for all of the data that's currently feeding into our analytics engine. These are some use cases that we're currently doing on a daily basis.

There are a couple of valuable features. One is that it is very quick on the profiling. So, you get a very fast snapshot of the type of data that you're looking at from the profiling perspective. It can highlight anomalies in the data.

The other valuable feature of the Data Quality tool is the flexibility of using their Analyst tool to create a mapping specification, which allows you to join multiple sources of information. You can then create rules within that data set. You can apply aggregations and all other types of functions, and then you can feed that into the profiling tool. From the profiling tool, you can then create your scorecards. It can be two-step where you're using that mapping engine to integrate multiple sources. If you don't have a need for that, you can do a lot more sophisticated mappings inside their Developer tool, and then maybe do an analyst type of mapping engine. So, you can do straightforward data quality within the Analyst tool, or you can do more sophisticated data quality within the Developer tool, at least as far as the rules are concerned.

Their UI needs improvement. Their scorecards and reporting also need improvement. Their data quality reporting, especially their dashboards and scorecards, is lackluster at best. Its reporting capabilities are limited. If you want to do anything beyond its limited reporting capabilities, then you're going to have to use an external reporting tool such as Power BI or something like that.

It has a few glitches that they haven't fixed. For example, while creating a new scorecard, when you get up to a point, you have to stop and save what you've done. You have to exit and then go back into the tool to finish up your work. From the development aspect, using their scorecard tool has a couple of glitches in it. This might be a tool that they're going to eventually phase out. So, they're just not doing a lot of work on it. I've been living with it for a few years now. I've learned that I got to save my work, and then I got to get back into it to finish up what I was doing.

I have been using this solution for at least five years.

It is pretty stable.

As far as I know, it scales pretty well. The part of the problem that we have is with the way it saves the results. When it saves the result, it creates a physical copy of some of the data results and stores it. So, when we're processing, for example, 500 million rows of data, depending on the type of rules that we have and how we're doing it, it can quickly use up a lot of space. We've had some issues with some of the space and storage. It scales, but you still have to be careful how you configure it so that you don't use up all your resources. We've added a lot of disk space, and we still occasionally have problems.

Currently, we have maybe half a dozen heavy users, but we're probably going to scale that up to 20 to 25.

It is straightforward.

I would rate it a six out of ten.

We are using it to understand the assets that we have from their technical metadata perspective, but we're also using it to align our business glossaries with the actual physical data location where the data is stored. Using their Claire or AI engine helps facilitate that. We've been doing that for a while.

The other thing we're trying to do is extend that metadata capability to include extended lineage and provenance attributes. We're trying to incorporate those into the existing EDC environment, and hopefully, when we get Axon, we'll try to figure out how we would expose that to the customer. We will figure out whether we're going to expose that directly or whether we're going to have to augment Axon with an additional UI layer.

From my standpoint, Informatica offers a pretty robust set of scanning tools that can scan a variety of sources of information. It offers a central repository that you can go to for interrogating and finding data. You can find the data that you're looking for based on enhanced metadata.

The other thing that we're working on is extending the existing Informatica data quality capabilities within the EDC so that we have a more robust understanding of not only what the data is and where it is located but also the quality of that data. We are doing this so that when people are looking for data, they see not only where they can find the data, but they also feel confident that the data is going to meet their needs.

The capability of the tool to scan and capture the metadata from a variety of sources is one of the capabilities that I find most useful. The central repository into which it is going to put that captured metadata is the best.

The model is somewhat flexible. There are certain aspects of the model that are not as flexible as we would like. It doesn't do certain things to a great level of depth. So, in situations where we want to drill in to do something specific, we have to essentially copy that data into our own structures in order to add that additional layer of flexibility.

Robust process management or workflow management, like Bonita, should be incorporated into the Informatica tool stack because it offers very simplistic workflow capabilities. If we had more dynamic and robust workflow capabilities, we could make use of that a lot more. Currently, we have to do a lot of pre-work outside of the Informatica tools before we can get the data loaded and start using it because they're UIs. I haven't dealt with Axon. So, I don't know exactly how that's going to change things, but with the EDC tool, I can't say the user interface is useless, but people don't use it because they find it cumbersome.

Its UI, without considering Axon, is probably their least desirable part. It has some interesting capabilities, but it is not what I would call cutting edge or super. It is not as intuitive as I would've expected. Its UI is probably prior to Axon. It is a little dated, and even Axon has been out there for a while now, but it is a little dated. That's probably why they went out and bought the company that originally made Axon.

I have been using this solution for five or six years.

It is very stable.

We're using it for our enterprise. We are not the largest enterprise in the world, but we're a pretty good size. We have 20,000 people working here and petabytes of data flowing through various systems. It is less about the people using it directly as opposed to the systems using it. It is really a matter of the system interfaces that are automating. We're trying to automate the metadata as much as possible so that when people are looking at their data, they can also see the associated metadata. Sometimes, we have to pull the metadata out of EDC and feed it into other systems so that as they're using these other systems, they can see the metadata flows with it.

I haven't dealt much with them directly, but I've had colleagues create tickets all the time. Generally, they're pretty good. 

I'm more from the end-user perspective. From a system standpoint, there is a different team that sets things up on the server and establishes various types of configurations. I do work with them, but I'm not actually doing that work. 

They have three people that are actively managing the system, and they are system administrators. There are also various people who might be testing things at any one point in time, and then there are various analysts who might be creating data to feed into the system, such as definitions of business terms. The same people may review the results once it gets into the engine. When it starts to process that data and makes the associations between the terms and the actual metadata where it is linking the two up, somebody has to go in and validate that, especially the exceptions or the ones that don't have a high enough matching score. So, there are probably three or four system admin folks, and those are more technical folks, and then you have maybe 20 people who might be putting in data, validating the data, and so on. Those are still primarily an IT function. They have subject matter expertise, but they're still reporting up through the IT group, and then, we'll eventually get to the point where we have a more robust set of business users who are reviewing and vetting that information.

I have no idea what the price actually is. It is probably not going to be the cheapest, but it is a pretty stable and robust platform from the backend standpoint. 

I would rate it an eight out of ten.

Informatica MDM is used for customer affiliations and sites and hierarchy management.

Informatica MDM has helped our organization because we now work from a harmonized single record for customers and patients. We're able to have an aggregation or hierarchy view, which drives a whole variety of things, such as data quality and data reliability.

The most valuable feature of Informatica MDM is hierarchy management. It's not something that's typically available and effective within ERPs.

Informatica MDM can improve the data catalog and data marketplace.

Informatica MDM is expanding in AI by making it much more efficient and automated stewardship-related work. I'd like to see that accelerated and made available for on-premise.

I have been using Informatica MDM for approximately four years.

The stability of Informatica MDM is good.

Informatica MDM is scalable.

We have approximately 100 people using this solution in my company and their roles vary. For example, we have stewards, data analysts, platform administrators, architects, developers, and support teams. The active users are primarily stewards and data analysts.

We rate Informatica MDM support on an annual basis and we have quarterly executive business reviews where we discuss support issues.

Positive

We previously used SAP for MDM. We switched because there were new use cases that SAP couldn't meet. 

The initial setup of Informatica MDM is more complex than it should be.

We used a third party for the implementation of Informatica MDM.

We have approximately 20 people that do the maintenance and support of the solution. This includes support admin teams and architect engineers. We have a BA for each of the domains, shared architecture, shared engineers, ETL, and MDM. Additionally, we rely heavily on third-party assistance.

We have seen an ROI in duplicate data management, visibility to market share, and reduction in risk.

I rate the licensing cost of Informatica MDM a five out of ten.

We did go through a solution selection and RFP process before we chose Informatica MDM.

My advice to others is for them to look at SaaS and cloud options first.

I rate Informatica MDM a seven out of ten.

Informatica MDM has a lot coming ahead from a solution standpoint, which is a benefit for them. However, there's a lot of configuration involved to keep the solution going and this is why I would encourage a SaaS solution for anyone coming in.

Informatica MDM is used for all data management practices use cases, such as centralized master data, cataloging, and metadata management.

The most valuable features of Informatica MDM are its reliability, match functions, and integration capabilities. The out-of-box functionality of deduplication and built-in data models ensure faster implementation.

Informatica MDM could improve the interdependency with integration. The solution sometimes becomes a bit difficult to change considering a lot of interdependency with the integration. There can be some improvement in the workflows and they can introduce more artificial intelligence.

In a future release, Informatica MDM could improve the UI and create an easier way to change the existing setup.

I have been using Informatica MDM for approximately 20 years.

Informatica MDM is stable.

Informatica MDM is scalable. However, sometimes it becomes difficult to perform the change. When it comes to volumes, it's fantastic and very fast.

We have an entire organization of approximately 80,000 using the solution.

The technical support from Informatica MDM is good.

I have previously used IBM, SAP MDG, and Parallels.

If an organization has a quite complex setup with different systems then I would recommend Informatica SAP MDM because of the integration capabilities. If the organization only has one ERP, then it's not advisable to use Informatica MDM because SAP MDG is quite integrated with SAP.  The IBM solution I use quite a long time before, but I don't know how they are doing today.

The setup of Informatica MDM is easy.

We have two people that do the development and maintenance of the solution.

Informatica MDM recently changed its pricing model. It's usage-based but I don't have much insight into the current pricing.

Whether to use Informatica MDM or not is highly depends upon what is the use case and the core structure you have in the organization. If you have a small company with limited systems, then you use something lightweight MDM. Where you have more than one ERP, all technology interacting with each other, then I would suggest a solution, such as Informatica MDM, it is a good deal.

I rate Informatica MDM a seven out of ten.

In the past, people used Informatica MDM because it was one of the leading tools at that point in time to work on an on-premises model. It was the leading tool in the market, offering vast customization options and matching and merging options that were better compared to other solutions. The way the data lineage or the customization options it gave, the tool was good. Now, the tool has a changed dynamic, and it is currently available on the cloud. Apart from Informatica MDM, there are other tools, as well as the market, that are completely on the cloud.

The feature of the product that has been most helpful in improving data quality revolves around Informatica DQ or IDQ, which is one of the tools Informatica offers. IDQ helps cater to the scoring of the data, clean up the data, and integrate it.

In terms of the room for improvement required in the product, I would say that the product is still in the maturing phase, specifically on the cloud. The product is not too user-friendly to do the configurations. There are a couple of areas in the product where I feel improvements can be made, but if I consider the algorithms used in the match process, the tool is very robust.

I have been using Informatica MDM for nine to ten years. My company is a partner of Informatica, and we also implement the tool.

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

In terms of scalability, I would say that the product is currently more available in the cloud. Scalability-wise, I rate the solution a five out of ten. The scalability on the cloud is good. On the cloud, by default, the tool becomes quite scalable.

Informatica provides premium products. The product is mainly meant for enterprise-level customers because the tool is available at the premium cost.

I have not used the technical support provided by the product. If you asked me about the support offered for the tool's on-premises model, I would say they were really good. We really liked Informatica's support. With the cloud, I'm not aware of the support.

If one is a difficult setup and ten is easy, I rate the product's initial setup phase as a five.

If you are talking about the product on the cloud, the initial configuration must be done. There is quite a lot of refresh which takes place every time we have to publish something, and then we have to wait for some time. It is not that you make a change, but you can see it immediately in the tool. The wait period is quite long. If you are a first timer, it takes time for that person to figure out the product. Once you get the hang of it, then it becomes easy.

An end-to-end implementation would take nine to ten months, or maybe a little more than that, depending upon the customer's desired features.

The tool does give a good ROI.

The product is not very pocket-friendly for small and medium-sized businesses, and it is understandable because of the kind of features the tool gives.

On a scale of one to ten, if one is a cheap solution and ten is an expensive one, I rate the tool's price as seven.

Informatica MDM is able to handle complex data integration scenarios with the help of IDCM, which offers the power of an ETL tool.

Speaking about the AI part, I feel the product is still in the maturing phase.

My first preference would be for Welkio, and only after that would I prefer Informatica MDM, so I would say that it won't be my first choice.

I rate the tool a seven out of ten.