Informatica Intelligent Data Management Cloud (IDMC) Reviews

I'm a freelance consultant, so I work for a few different clients on different projects. Sometimes I do system integrations, and sometimes it's more of the deployment of the tool itself. 

Informatica Axon is mainly used for master data management because it's quite a powerful tool. Lots of clients are struggling because Collibra is not an MDM tool. Azure has some possibilities in the data factory for MDM, but in the end, it doesn't have the engine that Informatica has. I see quite a few clients bring Informatica into the architecture for ETL processes. They use it to extract, transfer, and load data, in addition to MDM, since they're a bit restricted with other tools.

I think definitely what my clients find strong about the solution is all of the processes that it can do. You can extract and transfer your data as you wish it to be consumed later. I definitely hear that this adds value to the tool. 

Another thing I hear clients say is that you can use the MDM modeling functionality as a kind of engine to do data cleansing before you consume the data.

Also, for example, Collibra works closely together with Azure, which works closely together with Informatica and Google because the clients have needs that can't be fulfilled all by one platform. Solutions needs to fit into that architecture, and Informatica can fit in there, and that's appreciated in the market.

There is always room for improvement in making the look and feel more user-friendly. There are also some technical issues sometimes with integrations because clients have a lot of different types of data sources.

One thing I miss with Informatica is the sandbox environment. I do freelance consulting, meaning I give trainings, and sometimes clients ask me to give a training in my own environment, my sandbox environment. 

I have an environment that Collibra provides me with for certifications of training, so I can use a kind of sandbox to actually show a few things to clients.  I have the same thing with Microsoft. With Informatica, it's a bit more difficult. They're not that willing to provide the sandbox to an individual consultant, so I'm just on my own. That's a bit of a pity because sometimes if a client has something that is not configured, I can quickly configure it in my own environment and then show it in a demo. I don't have that opportunity with Informatica. I have to work on the client's system, which then sometimes causes security problems.

I don't have complaints about the stability, and I don't see it as a big issue coming up with my clients. The app sometimes had issues for some clients but it was not business critical or actually impacting them.

I think it is scalable, but that is not really the focus of my work. There are a lot of reasons I can give that the scalability might be affected, but they are actually not really related to the tool itself, but just how you build it in.

If I have a problem with the client and I'm a bit stuck, the support is really good. I can fall back on the people from support and they're quite willing to help. 

It can also help the client because I do a project for six or twelve months, and then I'm gone. If the client has a question after that, they can talk to the support and it's really good. 

From what I have experienced, I would give the technical support an eight out of ten. 

I think the setup is quite easy if you are data-minded. If you don't have any clue about data management or don't have that background, you're not going to be able to do it. You need to have a bit of technical understanding to do it in the correct way. If you're completely new and you don't have that background of experience, then it's a bit harder, and you'll need to follow a step-by-step plan.

I see clients starting to set it up from scratch and it takes three years. If a client says they want to deploy it within their whole organization, then, in general, you need to count about three years because it's not only the tool. You also need to set up your governance and your organization on it. All of your processes need to be aligned with the tool, so it's a three-year program in general.

Both for the business end users and for the technical people, the maintenance is more on the technical side. For example, for the API connections, the batch processes, and the real-time processes, it's not always easy. One of the things that I always say to my clients is that they need to document everything, and that helps. I tell them to build into their project a documentation pillar where they document everything that they do, like their MDM and rules. It's easier if they have good documentation, but it's still a challenge. Without documentation, it's hard.

I think definitely starting it up gradually, meaning don't buy the tool and then start trying to put everything in from the beginning. First, think about: What do I want to bring into the tool? Which sources do I want to go integrate with the tool? Which data, which business areas do I want to cover with that? You need to do a modeling exercise. You need to do some preparation work first and take it slow. Start small, take a specific business unit or data domain, and then show the value for your business. Then the budget will come, and you can do more with the tool. 

I rate this solution as an eight out of ten.

The most valuable features are data quality, data integrate transformations, match-merge, and a few MDM solutions we build into data quality transformation. 

One area that could use improvement is the speed of the web interfaces. At present, they are very slow. I think it is essential that we are original and robust on-premises.  

I have worked with Informatica Data Quality for the past four and a half years.

You have excellent stability in the market in comparison to other data solutions.

We find that scalability is not an issue and have installed it on fourteen servers.

I have a lot of issues with their customer support and not getting the required technical information, which we actually need unless you can do a call with their senior technicians. Most of the cases that you raise are assigned to a junior technician. 

Positive

The initial setup is simple for a person who knows the company. If you already have one of their products you will find yourself comfortable doing the deployment. If you do not have experience with the company it is medium in relationship to complexity. 

I would continue to encourage the upgrades that are taking place every other one in order to release the new and relevant features. I would rate Informatica Data Quality an eight 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. 

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.

It comes with lot of features and is a one-stop-shop solution for integration, data modeling, and data governance. Everything can be built under one particular umbrella. If any issues come up, then there won't be any blame game saying that it could be an integration issue or an MDM hub issue because it's wholly owned by Informatica. That's the biggest advantage of Informatica MDM over that of any other tools that are available on the market.

It has given us a lot of flexibility in terms of solutions.

This is a costly solution. We have several customers who evaluate it but then look for other solutions because of the cost.

At present, Informatica MDM comes as an on-premises or cloud-based solution. I would like to see them offer a SaaS-based MDM model. I think they are working on it.

I've worked with Informatica MDM for close to a year.

We have not had any performance issues.

It is a scalable solution.

The technical support is good depending on the SLA. Sometimes, they do have a busy schedule. When I contacted them for issues, someone joined the call if he/she was ready. Otherwise, we have had to wait for a day or two.

Informatica MDM is a costly solution because it comes as a bundle. They are also globally positioning themselves and are definitely working on very upgraded technologies. If someone wanted to do it on the cloud, they have a lot of flexibility because they upgrade themselves according to the current needs. It definitely comes with a lot of features and that's the reason why it's costly.

The licensing cost should be approximately one million dollars. It's about four to five times that of other vendors.

Take a look at your budget first and then proceed with this solution.

On a scale from one to ten, I give Informatica MDM a nine.

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.

We use Informatica MDM for various clients for integration, removing duplicates, and centralizing data in one place.

It has improved our organization because it has made our data more reliable. Data is the most important asset these days, and in order to trust your data, you need these tools to make sure that your data is clean and reliable.

The match and merge function is good.

New machine learning could be added to Informatica MDM because the solution is outdated and is not moving with the current trends. The solution is good, but it definitely needs a lot of improvement and needs to speed up as per the market.

Artificial intelligence is something which they should add to the solution.

They need to do MDM on real-time data as well.

The price is a big factor. We try to convince our clients to go for Informatica, but the cost is too high, and they choose another product.

I've been using this solution for 15 years.

It's a reliable and perfectly stable solution.

It is scalable but to a certain limit.

I'm satisfied with the technical support.

Previously, I used IBM MDM, Orchestra Networks MDM, SAP MDM, and Oracle MDM. I have used a lot of MDM tools, and I've found that Informatica is the best solution out of all of them in terms of the architecture and user-friendliness. Also, the graphical user interface is very simple to use.

The initial setup is not very straightforward but not very complex either. It's somewhere in the middle.

Deployment can take six to seven months to a year or two years. It depends on the number of domains and the number of data sets you need to implement.

A team of eight to nine people can usually handle the deployment.

We mostly deploy on-premises and sometimes on the cloud. Informatica is very weak on cloud-based computing though.

We implement the solution for our clients.

Based on my clients' feedback, they have seen a return on investment in the long-term. After five or six years, they can definitely see that the value of their data is growing.

Informatica MDM is very expensive. Apart from licensing fees, they have broken down their products into multiple products, and they charge for each and every product. If the data is huge, they charge for the data. At times, we have to use third party services for data cleaning, and they charge for that as well.

If you are choosing Informatica, then you need to employ the right kind of service provider. If you don't have good implementers, you'll not be able to leverage the product. So, choose your consultant and service provider wisely; then, you will not have any issues when implementing Informatica.

I would rate Informatic MDM at eight on a scale from one to ten.

Axon is a platform that lets everyone see all the data assets, business glossaries, lineage, catalog, classification, etc., but the real activities are being done on EDC.

We have only been using Axon for a short time in my organization, and we are decommissioning it, but I used the solution at my previous organization for data governance projects. Data owners, software developers, and architects all access the solution. In total, we have around 150 to 200 users on it. 

Axon has a marketplace that allows you to showcase all the assets the data owner has, so they can request access. That's one feature we use extensively.  Axon also offers great visibility and intuitive searchability, allowing you to easily search data assets. You can check the lineage and see the work EDC does. EDC handles all the classification, cataloging, and lineage. It's integrated with Axon, and anyone can see that.

Though EDC has maximum coverage, a few things were not available to scan, but I think EDC is evolving to address this issue.

I have been working on Informatica EDC and Axon for nine months.

Axon is stable.

Scaling isn't a problem. It depends on how the implementation is done. Kafka is scalable If the implementation has an image, and it would definitely be scalable on the cloud. We run Axon on our private cloud instead of a Kubernetes cluster. If we wanted to implement it on Kubernetes, we could scale it easily. 

I rate Informatica support eight out of 10. 

We tried an open-source solution, but we stopped it midway through the project and adopted EDC and Axon. We also started using Atlas and Ranger.

Setting up Axon wasn't too complicated. One to three people were involved. It took about three months to implement the solution and onboard various data assets. It was a continuous process, which means we were onboarding new assets as soon as we got them. After deployment, we only need one person for maintenance. They handle this in addition to some other responsibilities.

I can't give an ROI measured in dollars, but we see qualitative benefits. You gain the confidence of our customers because they know their data is secure and only accessible to those with authorization. Data quality is improving. We are gaining our customers' confidence, and they rely on us for data classification.  

EDC comes with an Enterprise Licensing Agreement, whereas Axon is a yearly subscription. That is an expensive affair. I don't know the exact cost because the asset management team handles that. We only tell them how many licenses to get.  The administrator who manages the platform distributes the licenses, and we provide them to data owners who are making policy changes.

Axon is sold separately, and it's subscription-based. Usually, EDC is included in a big data package as an enterprise license. It would be nice if EDC and Axon could be bundled in one enterprise license.

Every tool is evolving. New technology platforms and applications are coming out all the time, like Databricks, Scala, IBM Db2, z/OS, etc. 

I rate Informatica Axon eight out of 10. It's a leading solution in the data governance segment. If you're looking for a quick and easy implementation, I recommend Informatica EDC and Axon.

I use the solution for enterprise-wide data discovery and traceability, providing business context to data and collaboration between different stakeholders of data.

My organization, being a service provider, uses the product to develop domain PoCs, customer PoCs, develop data management and governance use cases, etc. The major issue with enterprises are the ability to quickly develop an MVP and showcase it to business and other data users for greater buy-in. This is important as these are new technologies - and hence, users might not easily adopt.

Our organization is a service provider as compared to an end-user. We have helped multiple organizations onboard onto data management using these technologies. 

It has improved different areas for different enterprises, including the improvement in overall business outcome and business experience, imbibing a data-driven culture, having easy availability of the right and relevant data, allowing for better compliance to regulations, and providing greater data quality and privacy management.

It has also improved overall time to service data requests such as DSAR requests.

The metadata management of Informatica is great. When an organization uses developer for data integration, IDQ for Data Quality, EDC for Data Catalog, Axon for Business Glossary, DPM for data privacy management etc., Informatica tools integrate metadata from all these tools seamlessly. The advantage is getting a complete view of your enterprise data through business and data lineage - as it not only provides you with pure data lineage but also associates related data quality measures, data protection levels, etc.

Additional metadata harvesters from different major tools can be an added advantage. Informatica provides some smart connectors for harvesting metadata from some of the industry tools. That said, this can be improved a lot more.

Overall, the toolsets are really good.

Installation and configuration can be another area where Informatica can improvise a bit. It is not easy to set up and configure the tool. A proper step by step guide to ensure this process goes smooth can be a huge advantage for end customers.

I've used the solution for more than six years.

The stability is excellent.

The scalability is excellent.

Technical support is good.

Positive

Most of our customers were using excel and email-based communication for data access. These new-age solutions improve efficiency ten times or more.

The initial setup was not very straightforward. This is an area of improvement.

We, being a service provider, have implemented and configured the setup on our own.

ROI depends on the buy-in from businesses and overall adoption rates. There is a huge amount of change management and change strategy that needs to be in place to ensure users are adopting the new tools/technology.

Informatica has good pricing options and a good professional services team who can help with setup/configuration.

There are other competing good products such as Collibra, Azure Purview, Erwin, IBM CP4D, and more. All have their strengths and weaknesses.

If you are an Informatica shop, there is no need to think twice to opt for an Informatica-based Data Management product suit.