Informatica Intelligent Data Management Cloud (IDMC) Reviews

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.

It's about mastering various domains. For example, an organization might want to master customer data residing within their IT landscape. This includes all master attributes related to customers, like name, email ID, phone number, address, and potential information like stores they visit. Ideally, if the organization also stores data related to those stores, all that information, files, and everything would be included. So, these master attributes would lie within the MDM system.

Here's where things get interesting. I'd bring this data from disparate sources. For example, accounting systems hold phone numbers, email addresses, and maybe even bank information (just an example). 

But another system, like the ER system, might have different information, like the customer's spouse. So, I'd likely get streams from both these systems, but there might be an additional attribute in the ERP system, like the spouse's name.

Now, looking at all these different attributes lying in different systems, one system might have my name as "Raja S.," while another might have it as "Raja Soni." So, the question becomes: are Raja S. and Raja Soni the same person? How do you identify them from these records?

They try to match these records based on phone numbers or any other common attribute between the two systems. Then, I would have a complete record in MDM, which is called the "Golden Record" - the single version of truth within the system.

Furthermore, MDM can also contain additional attributes that the ERP or accounting systems didn't have. So, imagine ten different applications or data sources feeding customer information. I can gather all of that information and create a single version of the truth for a particular customer within the MDM system.

Additionally, if I want my customers to update any information, I can provide a form where they can enrich their data. For example, they could potentially enter their Social Security number (although this wouldn't be common practice). This is just an example of how someone might want to collect this information. So, I can create a form and say, "Okay, can you directly feed this into the MDM system?" This becomes an enrichment opportunity as well.

With Informatica MDM, before you consume the data, you need to check what kind of data it is. There could be some systems where the first name is missing, or the last name is listed as "missing." 

This is where, before consuming or ingesting data into any MDM system, I can filter it out or rather do profiling using Informatica's data quality tool, which is a different tool called IDQ. I can profile the data, okay, and see the current state of the data from our system, any other database, or any source system. 

This is where I'll identify issues like missing phone numbers, incorrect cities, and other things.

So, when I see that the data is incorrect or incomplete (not just incorrect, but also incomplete), I can go back to the source system based on these profiling reports. I would say, "Source XYZ, you have missing data. Can you please ensure that you send it?" So, when I ingest data into the MDM system, I will only ingest it with certain rules. 

These rules define that only records with a first name, last name, city, phone number, and email address should get into MDM. If any of this is missing, I'm not going to let it get into the system.

I would ask the business to review those and then probably ask the system to correct them and then feed them again until the defined criteria are achieved. That's how I improve data quality using Informatica MDM.

Plus, I can also decide that once the data is in MDM, it can feed back to these source systems from where it was originally consuming the data. So, whatever is corrected gets looped back to these sources if they allow me to publish it to them. 

Then, this automatically becomes a cycle: data comes in, gets a data quality check, then enters MDM, and then can be fed back to the source systems if they accept it.

First and foremost, data profiling is a very important aspect, because it allows me to understand the state of the data from the different source systems and applications I'm going to pull into MDM. This is crucial, as it helps me understand the existing data landscape.

Next, Informatica MDM allows you to perform fuzzy matching. Like the example of Raja S and Raja Soni mentioned above. With fuzzy matching, I can define a threshold, and the system will let me know whether these two records are the same or not. 

This is where I think MDM shines - with its strong fuzzy matching algorithm. This is the essence of Informatica MDM. Based on these results, I can write our match conditions and then perform the corresponding data management activities.

When it comes to how data is governed - how accurate it is, what's missing, and what's not.

There are other Informatica tools involved: Informatica Enterprise Data Catalog (EDC) and Informatica Axon, which is specifically a governance tool. With these tools, users can understand data quality. 

Data quality, Informatica EDC, and Axon work together - they "talk" to each other. The moment Axon identifies that data is bad, incomplete, incorrect, or whatever, the governance tool allows you to monitor all of these things and feed them back into the organization.

For example, if someone within the organization is using the governance tool, which is connected to data quality, they might realize: "This particular source isn't giving me certain information, like city data. But I need city information for my XYZ data usage. So, I should focus on another data source or application where customer cities are available." Based on this, data governance can be implemented, and workflows can be established.

MDM also provides workflows. When records come in or if a customer wants to update a record directly in MDM, different personas can be defined. 

A workflow would then be triggered, and someone could review the data being fed through these forms or sources. They might reject or accept it based on predefined criteria. This is how data entering MDM is governed, ensuring everything is correct and meets organizational standards.

I feel the out-of-the-box APIs or the API management could be improved slightly from their current state. It could be more user-friendly.

In future releases, I would love to have more reports and dashboards available within Informatica MDM specifically for master data reporting. 

Currently, there aren't many reporting functionalities offered. While it's true that reporting isn't a core feature of any MDM system, they do have basic dashboard reports. I'd like to see them made more customizable and offer more options for creating reports.

I have been working with it for more than ten years. 

Stability-wise, it's also pretty decent and stable. So, I would rate the stability an eight out of ten. 

I would rate the scalability an eight out of ten. It's pretty good because mastering data across various domains like suppliers is crucial. Informatica is probably the best when it comes to multi-domain solutions.

There are around 500 end users. 

The quality of resources is good, and the time is acceptable. However, the initial quality of resources assigned to support tickets could be better.

Neutral

I'd rate Informatica higher. The biggest reason is the multi-domain capability. Not all vendors offer that flexibility. 

Additionally, Informatica is actively working on a clear, built-in AI engine for its tools. The SaaS version functions well, and they've introduced CLAIRE AI engine for on-premise versions. This engine learns from usage within your organization, further enhancing the experience.

The complexity of the setup depends. For example, it is different for the on-premise version. Now, Informatica has mostly shifted towards a SaaS model, which is essentially plug-and-play. You just need to log in and start using it, making it very simple. 

However, for the on-premise version, the setup process requires some expertise. It's not something just anyone can do. You need experts in place to handle the setup effectively.

Within the organization, businesses have benefited significantly. Tasks that used to take four to six weeks now only take three to four days.

Pricing can vary because Informatica doesn't have a standard price across the board. It depends more on the sales representatives in different regions. They essentially call the shots and decide the discount percentage for each customer.

So, it's quite flexible, like a bargain, in a way, but it depends on the salesperson.

Overall, I would rate the solution an eight out of ten. 

I absolutely recommend it. If you're looking to implement a Master Data Management (MDM) solution, Informatica MDM is the most flexible tool available in the market. Compared to its competitors, it offers several advantages.

Firstly, it provides the option to move seamlessly between on-premise and SaaS versions. If you start with the on-premise version, you can easily transition to the SaaS model later, if needed. 

My company works with our different customers to implement and install the solution.

The workflow in Informatica Axon is intelligent and good. Informatica Axon provides good data collection and good search criteria. In Informatica Axon, workflow and business glossary are good.

There are some limitations with Informatica Axon when one tries to connect or integrate it with Jira. For example, I can't delete any workflows after the integration process. There are issues with the integration capabilities of the tool with third-party solutions, specifically Jira.

I have experience with Informatica Axon for two to three years.

It is a very stable solution.

It is a scalable solution.

I recommend the solution to big companies because its functions are suitable for high-end companies.

The P1 support offered by the solution's technical support is very fast. If it is not P1 support, the support a user might get will be slow as it takes time. I rate the technical support a seven out of ten.

Neutral

For data governance, I work with Informatica Axon only. I prefer Informatica Axon for enterprise metadata management at an enterprise level, data quality, and integration. I only recommend Informatica Axon, mainly for data governance.

The product's initial setup phase is very easy.

For each of our company's customers, with an installation scope in place, it doesn't take much time. The product's implementation scope differs from the installation scope. I usually help our company's customers implement the tool.

The solution is deployed on an on-premises model.

Informatica Axon is a very good product with an easy implementation phase and a lot of information about the tool available online on the internet.

I rate the overall tool an eight out of ten.

Informatica MDM's most valuable feature is the interconnection between multiple Master Data domains.

Informatica MDM could be improved by adding drag and drop options, business data insights, and visualization reporting.

I've been using Informatica MDM for six months.

Informatica MDM is scalable.

Informatica's technical support is good, except for response delays because of time zone differences.

Neutral

The initial setup is simple.

Informatica MDM's price could be lower.

We evaluated TIBCO, IBM, and Microsoft.

I would rate Informatica MDM eight out of ten.

Some of my clients use it as a front end tool for the data quality governing process.

The solution allows the complete governance process, starting from the data quality, those definitions, and it can get the data quality in the EDC.

I would like to see more API integration to have the capability to build a report using other third party reporting tools allowing things to be streamlined.

I have been using this solution for one year.

It is a stable solution, we do not see any kind of issues. When we do find issues we have to go to Informatica to get help, I would say it is not completely matured.

The technical support is very good, they have resolved any issue we have had.

The installation is simple.

You can purchase licenses for this solution at different intervals. For example, annually or every three years. They recently changed their terms for licensing and now it is more flexible.

When choosing this solution you need to identify a path by asking yourself a few questions. Where are we going to start? What are the sources? What are the business pain points in terms of the data governance process?  Are you looking for metrics in terms of streamlining the whole process? Are we looking mainly in the bigger lineage? Are we looking to build reference data? We need to identify those areas and prioritize what is more important. Start small and then eventually add more sources, do not commit too much at the beginning you will not be able to be successful. Start thinking in terms of what are the business pain points currently. What would be the first result that you feel would make the business happier and then adjust accordingly, you can build on it further later.

I rate Informatica Axon a nine out of ten.

Our primary use case for this solution is purely for data quality analysis.

It took us a while to teach our users how Informatica works and to help them understand. We are still learning together with them because it also took us a while to master the tool. The contractors that come with Informatica are good on the ETL side but not that good on data quality.

The features I find most valuable are the mappings and rules. I am also impressed by the solution's interface. I really like this solution, as it works very well.

The visualization is very limited. It's not modern age, it's not self-service BI. It only has three levels of granularity on which you can present data and that's not enough. What's more, we had a few problems with the configuration. At times we found it difficult to integrate with other systems, but it turned out that the problem wasn't with the solution but with our firewalls. We had a couple of bugs but they are all fixed now. 

Another feature I would also like to see is tagging. At this stage, we can't tag data in the database of the data source with particular data flows. This is a nice feature that other solutions have and that Informatica lacks. We have to analyze and store data in a database and then we have to analyze it again and go through the servers. This takes up double storage. So if the data could be tagged at the database instead, anybody who has access to this data will know if there is a problem with the accuracy or anything else.

I don't think the solution is very stable because we have to refresh and restart the server at least once a month, or even more often. We couldn't understand what was causing this, perhaps we have a few bugs. But at times one team will be working and everything will be running, and then the other team will have some access issues. All we could do to fix this was to restart the server and then everything was up and running again. 

The scalability is very good. We have about 30 users and this may increase because our organization constantly needs more people, so people see the benefit because it's stable and it gives consistency. We will probably move to big data analytics and purchase their big data applications.

To be honest, we didn't really have any major issues yet but the technical support is good and they have a dedicated tech person assigned to us by Informatica to supports us. It works well because if we have a problem that our own IT team can't fix, they use Informatica to help them. 

I used IBM InfoSphere before but Informatica is much, much better; gold standard. There is no comparison. The interface and everything else is better.

The initial setup was very complex. It is mainly our own fault because we didn't go for the solution that was recommended by Informatica. We used shortcuts that backfired on us and we've been struggling for a year. In the end, we did exactly what Informatica recommended at the beginning and now everything works fine.

We have an integration team that is responsible for maintenance and deployment.

Informatica is very expensive. But luckily we got enough free licenses, so we are still within limit. 

Informatica has been the best solution for the past 10 years, but now there are new tools emerging. So maybe we will switch in the future. 

I would advise others to go for it because I love it. Maybe there are better tools, but I don't know about them. I would use it in conjunction with Tableau and Google Analytics for visualization. I would also suggest others to follow instructions during the initial setup and not to cut corners. Do the configuration exactly as Informatica suggests.
I love Informatica but I am not sure if it is value for money. Organizations that plan to increase their users may find it worth the money, but smaller organizations may want to use something simpler.

I will rate this solution an eight out of ten. My rating would have been nine if the solution offered tagging and if it was cheaper. 

We use Informatica Axon for MDM purposes.

The most valuable feature of Informatica Axon is that it is flexible and user-friendly.

Informatica Axon needs more integration connectors so that it can connect to systems and different kinds of datasets.

I have been using Informatica Axon for two years.

I rate Informatica Axon an eight out of ten for stability.

Ten engineers are using Informatica Axon in our organization. I rate Informatica Axon an eight out of ten for scalability.

Informatica Axon's installation, configuration, and user access take two to three days.

Informatica Axon eliminates all MDM-related problems quickly.

Informatica Axon is a costly solution. I rate Informatica Axon a four out of ten for its pricing.

I am using the latest version of Informatica Axon. I recommend Informatica Axon to users as it is a good and flexible tool that gets the work done.

Overall, I rate Informatica Axon a seven 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.