Informatica Intelligent Data Management Cloud (IDMC) Reviews

Informatica Enterprise Data Catalog is being used for recording enterprise assets, such as customers' products and vehicles. 

We a consulting service that provides information on how to enter the catalog or forms to collect the data catalog and enter them into Informatica Enterprise Data Catalog.

The most valuable feature of Informatica Enterprise Data Catalog is it provides clients with a full view of the enterprise data assets. For example, how many data assets they have and who owns them.

Informatica Enterprise Data Catalog could improve by having a much better user interface. It is not user-friendly.

In a new release of Informatica Enterprise Data Catalog, it would be beneficial to have some new features including data sharing.

I have been using Informatica Enterprise Data Catalog for approximately three months.

The solution is stable. There are some issues that can arise with Informatica Enterprise Data Catalog, but the vendor can resolve them.

We have 10 people that use the solution.

Informatica Enterprise Data Catalog sends support to our clients if they are having problems.

The initial setup of the Informatica Enterprise Data Catalog can be difficult. It can take approximately one week to install all the components, such as metadata.

There are vendors to do the installation and it can cost a lot of money over the week that it takes.

I recommend this solution to others. There is a large market in China for Informatica Enterprise Data Catalog.

I rate Informatica Enterprise Data Catalog a seven 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.

It is generally used for the data integration between multiple ERPs. We have ERPs, and then we have third-party exchanges that sell products. The third parties are partnered up with some of the customers, so they create deeds, and we pull in orders and quote requests.

We're trying to get to the latest version. We're two revisions behind right now. It is a local install. 

It is on-prem, and we're trying to get to all-cloud. We do use the cloud for configuration, but we deploy it to the agents locally. We're using the cloud instance of Informatica to deploy to, and we're currently on Azure.

In the latest version, I like the outlay of the business roles creation. I like seeing that visualization as you're building it, as opposed to going through metatables or XML mappings. We liked that piece, and it makes it more intuitive for the business. 

Its GUI interface definitely helps visualize what we're trying to accomplish. There is always a disconnect between IT and the business, and it helps in creating the feeds that follow the business process flows with some of the types involved with the business.

It is so broad in what it can do. Their services have expanded beyond what they originally built it out to be. The best thing I like about it is that each time they add a new service to the platform, it easily integrates with the core, which is really nice.

The biggest pain point for us is the documentation. Typically, you have to go through knowledge forums and knowledge groups to find out about the syntax issues for interfacing with new products. Typically, you've got to deal with someone who has been through the pain before. Their documents are not really up to date with current innovations happening in the industry. As big as they are, you can't really expect it, but that's our pain point.

We've been using this solution for about four years.

We love it. It is very stable. It is probably the best thing we've seen in a while.

It can out scale our ERP. So, scalability is not an issue for us. However, it can overload our system, but that is not related to the scalability of MDM. It is related to the scalability of the system it feeds.

We have five business roles that are using it, and there are two admins who are supporting it. Basically, it is supporting an environment of about 5 billion in revenue. That's a lot for that amount of revenue. It is a lot of people.

We're trying to extend or expand more modules. We have MDM, and we're going into Supplier 360 and Product 360. We found that it is the most robust platform to integrate with our e-commerce platform. Basically, we have four different e-commerce realms, and we're going to consolidate them. So, Informatica helps with the supplier stuff coming in, harmonizing the data, propagating it out to the sites. In the future, the four sites are going to be combined and consolidated into one site, and then we'll be dealing with four different ERPs, and Informatica will be very key in that as well.

Their technical support is excellent. Whenever we had issues, they were pretty quick to respond. There was never an issue in finding them. The longest we had to wait for getting a resolution was a couple of hours.

I walked into this, so I don't know what they had before.

I wasn't involved with its setup.

It is expensive. That's probably the biggest drawback. The business has heartache paying the license, but that's mainly because they don't realize what value it brings. The key thing about the MDM solution is that it is in the backend, and no one sees what it is actually doing. You don't know it is a problem until it is not there.

I would advise making sure that you have a very well-defined design before you decide you need an MDM. In our case, after MDM was in place and we turned it on, we realized that there are other processes that we needed to refactor for the purpose of MDM, which extended the rollout. This was not an MDM issue. It was a process issue in the business. That's why you need to make sure that the design is well defined. It helps to have their partners involved as well. We're dealing with Informatica consulting today to help design a Supplier 360 portal. 

It is hard to find people who are well versed in Informatica. It is hard to pluck one out of the place. You've got to go and poach for them. They're not out there open and looking for jobs.

I would rate Informatica MDM an eight out of 10.

The MDM solution is capable of integrating multiple systems, so it helped us to solve the purpose of centralizing the depository as well as the standardization of mass data. It takes away all the ambiguity around data integrity issues or all the process challenges which happen when every stage of a process uses a different source as master data. 

The solution's ability to integrate with different solutions is a big selling point for us. It's also quite powerful and customizable. I really enjoy its match and merge capabilities.

When it comes to UI look and feel and user experience, Informatica is not as good as other solutions.

There are some MDM solutions that come with an integrated view, which includes your transactional and master and all other data together and helps you get a 360 view of the object. That's where I think Informatica is not as powerful or as agile in the way other solutions are out of the box. 

It's quite simple to scale the solution. We have about 30,000 users, but I don't see a limitation on the solution that would stop you from having more.

Technical support is pretty good. It does take time. Some solutions are not fixed, but they have releases and updates that deal with the issues, so, I don't see a lag in support in that sense.

In 2010, there were only maybe three solutions: SAP, IBM, and Informatica. Before that, we didn't really have a centralized mass data contract, so it was more of an application grievance. With Informatica, we gained centralization of mass data, and also had governance and quality as part of a data management practice, and I think, at the time, the full package was available with Informatica as compared to other options.

I was not the installer, so I'm unsure of how complex the initial setup was.

We use the on-premises version of the solution.

I would recommend the product, but it depends on your business and other solutions you might already be using. If you're only using SAP, I don't think you'll need Informatica. If you're using Oracle products, you don't even need SAP.

However, if you're looking for an essential repository with very good integration capabilities, want to have a longterm sustainable solution, and you have multiple ESPs, as well as a wider organization setup, then I think Informatica is the best.

I would rate the solution at eight or nine out of ten.

We use Informatica Cloud Data Integration to migrate to the cloud, upgrade our data warehouse, and implement master data management. It helps us with in-depth analysis, leveraging shared history, and addressing data governance questions.

The most valuable features of Informatica Cloud Data Integration for our clients are the AI capabilities within Informatica Intelligent Cloud Services. It excels in mapping development, searching for contracts in data governance, creating data quality rules, and designing merging processes. The ability to identify duplicates and automate analysis coverage is particularly beneficial. Additionally, the cost-effective option of using Informatica Cloud Data Integration for smaller projects or departments has made it more accessible and attractive for experimentation.

One area where Informatica Cloud Data Integration could improve is in providing more accelerators for certain functionalities. For example, for master data management, having additional accelerators could streamline implementation. Additionally, enhancing compatibility with metadata sharing across different applications, similar to what is achievable with PowerCenter, would further enhance the product's capabilities.

I would like to see more connectors for on-premise databases in the next version of Informatica Cloud Data Integration. Currently, CDI free is a great option for cloud integration, but expanding the connectors to include databases like Oracle or MySQL for on-premise environments would make the tool more versatile and accessible for smaller businesses or those not fully in the cloud.

I have been working with Informatica Cloud Data Integration since 2016.

Informatica Cloud Data Integration has been generally stable, with occasional editor issues. However, SLAs are consistently respected, and we typically experience minimal downtime, averaging around two to three hours per month.

The scalability of Informatica Cloud Data Integration is high. With advanced pushdown optimization, it performs well in various environments like Snowflake and AWS. It is suitable for companies of all sizes; for small to medium enterprises, starting with fewer IPUs is cost-effective, and scalability allows for growth as needed.

I would rate Informatica's vendor support as a seven out of ten. It is generally good, but there is room for improvement, especially as they shift focus from on-premise to the cloud. We often find answers in the community for software issues, but sometimes we encounter challenges that require official support tickets.

Neutral

The initial setup for Informatica Data Integration is straightforward. Deployment is simple, involving exporting and importing development processes. The ability to pilot the Informatica Data Integration platform from various APIs makes continuous integration and deployment easy to manage through API calls.

I would rate Informatica's pricing as an eight out of ten in terms of affordability. Starting with a small IPU volume is cost-effective, and as we grow, the pricing adjusts favorably based on consumption, which makes it reasonable for our needs.

I would rate Informatica Cloud Data Integration overall as an eight out of ten. It is a comprehensive platform covering data integration, API integration, data quality, data governance, master data, and privacy tools—all within one platform. The accessibility to all functionalities with the purchase of IPUs is a significant advantage compared to the past where certain features required additional payments and permissions.

We have used it to elaborate on a project for Golden Record, for IDQ data quality, and create business cases for the control parties.

The product could be improved in the area of architecture and technology. All the parts are old.

I would like to migrate it to a new technology. It's better to have a new method for every IT system. Integrate with API, Kafka, and JMS, as API has in Jira code or Jira.

I have used Informatica MDM for ten years. I have used Version 8.6 and 9.1 of this solution.

I think that it's a good solution, but it's an old solution. It is stable because we have the experience to deploy this solution.

I think it's based on ODBC drivers, and they are not good for scalability.

We have not contacted customer service.

The initial setup was complex. It must have taken around eight or nine months to deploy all Informatica systems. The deployment processes for on-premise and cloud are different. For on-premise, we must deploy the data models, and then we must deploy the rules. We must also deploy a .Go file extension and an exposition of the vendor code, among other things.

It's different if we have an on-premise solution. The stability is for the on-premise infrastructure. It builds the IT of enterprises of clients because Informatica is at 'Legacy' level.

So, there are plans for licensing. There are subscription-based and usage-based licenses. Also, there are licenses for exceptional analytics, etc. In short, there are different models of licensing for every enterprise.

I think there is a new Jira-driven event, Jira-driven data, for the flows and extensions. So in this power center technology, I think that it's complex to navigate through the solution without new technology. Overall, I rate the solution a seven out of ten.

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.