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. 

Positive

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.

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.

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.

We primarily use it as an enterprise-level firewall. 

I have to incorporate my particular data, schema into Axon. I can do it in two to three ways. Either I have to do a bulk upload feature in Axon, and I have to create an Excel sheet and I have to incorporate all the columns, all the attributes, all the asset columns, and their definitions, and everything into the Excel sheet and then I have to upload it. That is a manual process, and an SME has to be required to accomplish that feature.

The feature of auto-onboarding of the assets, enterprise assets via EDC is good. EDC will scan the data within the technical metadata, and then you can associate that technical metadata, and then Axon can consume that technical metadata and associate the business metadata to that technical metadata. Following some Axon systems, we have to create some systems to associate that technical metadata, as there has to be some logical hierarchy that has to be followed. It allows for some flexibility. You can have related features like policies, business glossaries, or maybe some regulatory compliance feature policies, et cetera, as well as governance.

If you have a DQ rule, data quality rule, on any particular subject area or any particular column, then one cannot create directly a rule in Axon. It has to ingest the technical tool we create in IDQ then into the Axon.

Informatica Axon itself is not a very complete tool. It's highly dependent on Enterprise Data Catalog and IDQ. Blending data catalog and IDQ makes it complete. When I say blending, I mean in the sense they have internal plugins, internal listeners. Axon has internal listeners for reading EDC, as well as IDQ components. EDC is Enterprise Data Catalog, which's a metadata catalog from Informatica.

I would like to have broader connectivity. Axon currently is limited. It cannot connect to any other application. It does not have any connectors for other applications. I want more applications to have connectivity to Axon. Axon should create more plugins for connecting to other applications, which are currently dominating the market.

The solution still is a bit manual in its functionality. We want t to be more automation-driven.

The solution needs to be more resilient.

I've been working with the solution for the last three years.

Currently, what happens in a week or two, the server goes for a toss because Axon still uses PostgreSQL as its database. They have all the services and they, basically, fetch all the backend tables. All the tables are in the PostgreSQL database. That is also a kind of constraint for Axon as PostgreSQL nowadays is a solution that no one uses. That's why the server always goes for a toss and we have to restart the server. They have to make it more resilient. The resilience is missing. 

For example, in EDC they have multiple nodes. When one node goes down, you can still use the backup node. You have to just configure it. In Axon, this does not work like that. They have to make it more vigilant instead of having to restart the cycle and again restart all the services, pre-configured services to get it up and running. That thing is a bit scary sometimes as, over in product staging and dev, it works, however, for production, if it goes down and we need our scanning and some processes running, then it's pretty tough.

Technical support, nowadays, is a bit of a let-down. They will reply once you raise a ticket. They normally categorize their ticket as a P1, P2, or P3. A P1 ticket is for production for the first failure and the P2 and P3 are for normal failures. They reply promptly, however, the response is not very good. Earlier, GCS, Global customer support used to make sense and be helpful. However, nowadays, their quality of service is really going down. The person that comes to attend the ticket is often not very equipped, or not technically not very capable.

Therefore, you need to have a regular follow-up. Normally what they do is not solve the problem. They will ask you, source this, the source that, and then send some kind of justification instead of trying to solve the issue. Sometimes the client is not technically equipped to answer their ticket. They want to see some logs which get embedded. They ask businesses for those logs. Then, the business has to log into Unix, find a particular folder, and access that backlog. These become a challenge for our business as there are not that many Unix-friendly people. In any case, it lengthens the process and draws out the resolution.. 

When I started, I was using version 6.3 and now it's 7.2.

The solution is on-prem in the sense that it's a web browser. It's browser-based so that you can use it on your desktop for unblocking your firewall. It's an enterprise firewall, you can deploy it. Since it's browser-based, it does not matter where the server is. The server can be on-prem and it can be deployed on an iPaaS service or other infrastructure at your service.

Informatica has created the Axon brand in such a way that it's kind of an interesting strategy for them. Once you have Axon you cannot buy it as a standalone product. You will always have to buy IDQ and EDC. That's a sales strategy. However, they really need to improve on their customer support. I really would advise Informatica to work on support. They really need to catch up on this, and they really need to add more qualified engineers to their customer support team to meet the client's expectations.

Overall, I would rate the solution at a seven out of ten.

At our company, we use Informatica MDM for data architecture and numerous other aspects of data warehouse, such as data designing or modeling. We recommend Informatica products to our customers based on their use cases, data volume, budget, and environment suitability.  

The product isn't mature enough to provide suitable connectors to various data engines. The performance of the solution in transporting data between data lakes and Big data infrastructure is not up to the mark. At our company, we use a similar solution called Spark, which is much better than Informatica MDM in terms of performance and speed. The data support capabilities of Informatica MDM can be improved. 

It's a stable product without any bugs or glitches. But overall Kafka is a better product than Informatica MDM. 

The product exhibits satisfying scalability. 

The tech support is satisfying from the vendor. The support team was able to respond and solve the issues in a very short time. I would rate the tech support an eight out of ten. 

Positive

Informatica MDM easily integrates with the Informatica environment as well as with third-party tools. But for some integrations, for instance, when Informatica MDM is integrated with SAP, the functionality slows down drastically; the task that would take five minutes with Spark takes five hours with Informatica MDM.

The same scenario occurs when Kafka is integrated with Informatica MDM. For popular database integrations such as Oracle and SQL, Informatica MDM functions well enough. 

The initial setup of the solution is straightforward. Our company professionals suggest that Informatica MDM should be on a Linux server instead of Windows. 

The product is very expensive compared to other competitor tools. Informatica MDM is not meant for small businesses but rather used by large enterprises like banks or government organizations. Informatica MDM can be purchased as a stand-alone product and doesn't come in an Informatica bundle. The support for Informatica MDM is not included in the standard licensing fees and must be purchased separately.  

I recommend that others test Informatica MDM with different integration tools before making a purchase decision. I also advise others to evaluate the use cases before choosing a product. Other popular competitor tools in the market include Collibra and SAP MDG. 

Informatica MDM fits our organization's use cases perfectly. When a customer of our company has a plethora of business products, VOCs need to be implemented, even if it's a different MDM solution than Informatica MDM.

Some customers depend on a single technology ERP, while others work with Oracle ERP or SAP, and sometimes they are using ERP and Informatica MDM in combination or migrating from one ERP to another. These use cases will impact the setup that already exists on the customer's site, and thus, the solution needs to be configured accordingly. I would rate Informatica MDM as eight out of ten. 

They could improve the product support for the Arabic language. Currently, there are limitations in processing and the interface itself regarding Arabic language support.

We have been using Informatica Enterprise Data Catalog for two years.

I rate the platform's stability a nine out of ten.

Our organization has 12 Informatica Enterprise Data Catalog users. I rate the scalability an eight out of ten.

We encountered a delayed response from the technical support team.

Neutral

We also use the Erwin Data Catalog, depending on the customer's requirements.

The initial setup process is easy. It takes around two days to complete.

We get help from third-party vendors for product implementation.

The ROI from using Informatica EGC (Enterprise Data Catalog) can be substantial, as it helps everyone, from novices to experts and stakeholders, maximize their data's potential. It enables thorough understanding, insightful analysis, and seamless sharing of data assets. Features like adding business terms enhance data quality and governance, benefiting businesses across various sectors. Many customers have truly benefited from these options.

For 12 users, the platform's estimated annual cost is around $160,000.

Our data management processes primarily use Informatica to connect to data sources, scan metadata to obtain physical data and perform data classification. Subsequently, we create business terms to establish a business glossary repository within the platform.

The features that have been most effective in improving our data governance include auto-classification and the ease of exploration and navigation within the tool. It can automatically connect or associate business terms with various options, providing flexibility beyond general capabilities.

The AI-driven discovery capability has significantly enhanced our data cataloging processes. Utilizing AI for auto-classification and discovery has been particularly beneficial. However, there is room for improvement in certain areas for understanding the data.

It has adapted well to changes in our data landscape, seamlessly accommodating new types of data sources. It offers flexibility in adding new data sources and supporting multiple data connectors.

Looking ahead to the future of Informatica Data Catalog, data lineage will be a significant trend influencing the product. These features are currently available, but there is potential for further enhancement and detail. It will enable organizations to comprehensively understand their data and its relationships with business processes and regulatory requirements.

I highly recommend it to others and rate it a nine out of ten.

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.