Informatica Intelligent Data Management Cloud (IDMC) Reviews

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

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

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

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

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

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

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

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

Neutral

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

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

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

My company does not specifically focus on selling the solution to a particular sector. My company generally sells the solution to various sectors, including manufacturing and finance.

Informatica Enterprise Data Catalog is a compact tool. Many products operate as a data system solution or as a data catalog tool. The product is helpful when it comes to data transformation. If you would like to solve specific data-related problems, Informatica Enterprise Data Catalog can serve as a useful product.

I cannot specifically point out an area in Informatica Enterprise Data Catalog that needs improvement since it properly functions as a data catalog tool. You cannot use something like Atlas to get catalog ranges, making Informatica Enterprise Data Catalog a comparatively powerful tool. The UX and UI of the solution are areas with certain shortcomings where improvements can be made in the future.

If I want to get some extra features in the product, I can contact Informatica's research and development team, who can add some new features to the product and make the tool available in the market.

I have been using Informatica Enterprise Data Catalog for more than ten years. My company has a partnership with Informatica.

Stability-wise, I rate the solution an eight out of ten.

Though there are some bugs in the solution, Informatica's research and development team, along with Informatica's customer service team, supports my company in solving such bug-related issues.

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

Informatica Enterprise Data Catalog can be a good solution that is really easy to use when it comes to enterprise-sized companies, but it may pose some challenges for small and medium-sized companies.

Most companies to whom my company provides the solution are enterprise-sized businesses.

I rate the technical support a ten out of ten. My company has a partnership with Informatica, and we provide Informatica's products to the end users or customers. Informatica has to provide my company with good support in order to hold on to its customers who deal with my company.

Positive

I rate the product's initial setup a nine and a half to ten on a scale of one to ten, where one is difficult and ten is easy.

Most of the companies to whom my company provides the solution deploy it on an on-premises model. My company also sells the cloud version of the solution while also offering our customers the option to move from on-premises to the cloud version of the solution.

My wife runs a pharmacy, and she uses an ERP solution for sales-related activities, the data of which I can move to the cloud in ten minutes if she chooses Informatica Enterprise Data Catalog.

With Informatica Enterprise Data Catalog, measuring the return on investment can be hard. I rate the return on investment a seven on a scale of one to ten, where one is zero return on investment, and ten is a hundred percent return on investment.

The price of the product is something that may vary from customer to customer. I rate the product's pricing a five on a scale of one to ten, where one is cheap and ten is expensive.

If a customer or business wants to easily maintain their data domains, they can opt for Informatica Enterprise Data Catalog.

I rate the overall product an eight to nine out of ten.

Informatica MDM is a multi-domain product for any master data management. We could use it for customer master data management or supplier data. Given the nature of the business, we can apply Informatica MDM to master the core data entities within an organization.

Informatica MDM has a defined data model we can customize with user and developer options. The solution's user interface allows users to work with the master data model. Another feature I like is that the solution can integrate with various data cleansing engines, such as address cleansing or data quality-related packages or functionalities.

From a data or master data management perspective, the solution is pretty evolved. But from a business process automation workflow standpoint, it could be a bit more intuitive, rather than technically complex, such as in workflow alteration using ActiveVOS. The solution also needs adaptive rules elaborating AI/ML technologies.

I have been working with Informatica MDM for ten years now.

The solution is robust and stable enough.

With master data, we don't usually talk about tons of data. There could be a lot of records, but then it's not that huge. Now that Informatica is shifting towards the cloud as part of their software, they would have considered the scalability perspective, which is not too huge. Like transactional databases, we would expect less data there. The solution is mature enough to cater to a wide range of users.

We have a huge dependency on support all the time. If something is required or unclear or doesn't work, we have to raise a ticket and follow a process to resolve it. The turnaround time is long sometimes.

Even for simpler questions, we still have to be put on hold and wait for someone to pick up and respond. Even if the problem is critical, support does not treat it with the same urgency we would anticipate or expect.

Neutral

One would need professional services from Informatica to get MDM installed, and there has to be a contract with professionals all the time after that to manage the data model and any changes to the data. Moreover, there is a huge dependency on their professional services to work with the product in the long-term perspective.

The setup is not complex for professionals, but people without a technical background would not be able to set up the solution by themselves.

Once the installations are complete, there are two aspects to the solution. One is the back-end, which is the model, then setting up integration to load the data and configuring the MDM system to perform its master data capability. The other part is the front end, which is deploying the user interfaces and ensuring the user roles are defined and set up.

When deploying the solution, the whole project team needs to be around because the developers, the users, and everybody on the project team must come together because once it is deployed, it needs to be tested. Maintenance teams would be separate. They need to focus on any minor enhancements to the solution and provide support with any bugs, issues, or questions users might have with the data.

I have heard from customers that the product comes with a huge license cost. Under contractual terms, Informatica does not let us have full control of our own datasets, but that comes down to how the billing and licensing work. The licensing is a bit complex and expensive.

I have experience working with Informatica MDM. However, I have been comparing it against MS MDS to see how each stands. More from a costing perspective, a licensing standpoint, or any roadmap from a product's perspective, for which MS MDS has no plans to expand or evolve to a newer product with more capabilities. That's something I am checking in the background. Given the current landscape in my organization, both tools coexist, but we are trying to see if we need to replace one with the other.

At the moment, Informatica is the market leader within the MDM space, expanding into the latest data integration and management advancements. I don't see MS MDS in these areas. But then again, MS MDS has been treated as a legacy system within the organization, and we're trying to find a roadmap to replace it with Informatica by understanding what it offers comparatively.

The solution is pretty evolved from an MDM perspective, and it seamlessly integrates with its product suite.

We work with the on-prem version. We have seen the cloud version, but we're not there yet because it takes a long time to onboard all the businesses onto the cloud. The cloud version is still at a proof of concept stage.

Before purchasing the solution, the user must understand the licensing and cost structure, as well as their professional support. All these aspects are important on an ongoing basis. Depending on the wide suite of products they offer, it's best to understand which products would suffice the business needs rather than having to roll out a full-blown MDM solution, which is not the case with all the clients.

I rate the product a seven out of ten.

I manage the environment and admin-related tasks.

I have integrated Axon into EDC, PowerCenter, and data quality tools, and I face no difficulty integrating with those tools.

I also handle installation, configuration, and troubleshooting issues, in addition to when users face access issues or need help seeing their DQ technical roles.

With Axon, you can easily call and verify DQ rules. You can also upload your business gallery, and the business team can easily verify your data because it is secure.

Some of Axon's valuable features include creating your business glossaries, importing DQ rules, and creating change management.

They could improve technical support because it is not good enough at the moment.

I am a consultant and have been working with Informatica Axon for three years.

I rate the stability an eight out of ten because I have not yet seen the environment go down.

I rate the scalability of the solution a five out of ten. We have faced some performance issues. We have about five or six Axon business users who are data owners and stewards. They are not very active with the solution.

Personally, for the last month, I have not touched Axon or the servers. There are no plans to expand Informatica Axon's usage at the moment.

I rate the initial setup a seven out of ten. The clients gave us their Linux servers, and I set up the solution on-premises.

I could set up the environment, the installation, and the configuration in one day.

My organization's initial steps required us to get licenses for the installation, and we needed specific kinds of ports opened from our environment. We first needed to install the Axon agent and Axon server on different directories. Once we did that, we needed to update a couple of files to communicate with data quality and other functions.

The solution requires some maintenance. I might have to perform a sync-up or make sure the environment is not down, but that is very rare.

The solution was implemented in-house, with me deploying the solution single-handedly.

I rate the pricing a six or a seven out of ten because the price is neither too high nor too low.

Informatica is a big name in the market and the tools are trustworthy, which is why our client chose Informatica Axon-EDC. I rate the solution an eight out of ten.

Test data management is a common use case. When conducting testing in lower environments, we want to avoid exposing sensitive information. To achieve this, we use Data Masking to modify the data. 

For example, we change personally identifiable information, phone numbers, and emails so that they cannot be viewed. The modified data retains the structure and format but doesn't reveal the actual information.

The tool is mainly valuable for testing teams, as it helps protect sensitive data during testing. It can also be used to mask production data for different users, ensuring that only authorized individuals can access sensitive information. These are the main reasons why we use this tool.

I think there's only one area that could be improved. Currently, when we apply the Data Masking rate, we don't have a way to view the masked data. It would be helpful if there was a feature to allow us to see the actual information.

Once the data is masked, it cannot be reversed. Having the ability to revert it back to the actual value would be beneficial, especially if we need to see the original information. Although our enrollment has decreased, it would still be helpful to have that feature.

I have used Data Masking as part of my work.

Stability is good. It's definitely reliable.

Scalability is good. It's definitely scalable to handle higher volumes across different platforms as well. It performs well in terms of scalability. 

Additionally, when it comes to implementing more source systems, there haven't been any issues.

Our experience with customer service from Informatica has been excellent. They are always available and responsive.

Positive

The initial setup is generally straightforward. However, there can be some challenges during the on-prem installation process, even though we have the steps and prerequisites. Dealing with installation issues is quite common, but overall, it's not excessively complex to set up.

The need for maintenance depends on the team. Sometimes, the solution you configure in the tool determines the level of maintenance required. However, overall, maintenance hasn't been a significant issue.

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

We use Informatica Cloud Data Integration because we have multiple sources for data integration, and we transform that data and load it into the database or QuickBooks.

There are fewer than 10 people using this solution in my organization.

I'm an integrator. I'm working with the latest version. 

It's deployed on cloud.

Data integration is the most valuable feature. The ability to connect to any of the sources and enterprise applications makes our lives easier.

We would like to have accessibility to the repository. We had that feature in Informatica PowerCenter, and we were able to have access to the repository query, which helped us build some tools, audit tools, and review tools. In Informatica Cloud, accessing the repository query is a challenge.

I have used this solution for about six years.

It's very stable.

It's scalable. 

We reach out to technical support frequently. We've had good experiences with them.

We previously used PowerCenter, DataStage, and Oracle Data Integrator.

I prefer Informatica Cloud Data Integration because of the ease of connecting to various connectors and various enterprise applications. The UI is also a valuable feature.

Initial setup isn't straightforward or complex. It's about medium difficulty. 

Deployment took about one week. It's not difficult to maintain.

Deployment was done in-house.

From the usage perspective, there is minimum ROI.

The pricing is high compared to other tools on the market.

We chose Informatica Cloud because we have Salesforce. If you're using Data Integration, App Integration, and many other features like operational insights, then the price is worth it. If you're only using the solution for data integration, then the price definitely isn't worth it.

We export APIs, and anyone can seek those APIs to have the data for target use cases. We hit the APIs that are exposed by external systems, and we get the data from them and process it.

We're using the latest version. It's deployed on cloud.

There are about five people who are using this solution in my organization.

We chose Cloud API Integration to connect to Salesforce.

The OAuth feature is the most valuable for authentication.

Recently, we're trying to connect to the Amazon API. There's no direct way to connect to Amazon APIs from Informatica Cloud. From Postman, there's a signature site called AWS Signature, which would actually generate the signatures for us with AWS APIs. In Informatica Cloud, we have to build the logic, and then we can generate the signature and hit the AWS APIs. Instead of generating that signature, it would be better if we could have the same connector in Informatica Cloud.

Sometimes when I open the processes or any service connectors, the labels are not properly displayed. The backend names are displayed rather than the front end label. I usually log out and log back in, and sometimes it disappears, and sometimes it doesn't.

I have used this solution for six years.

It's pretty stable. We don't have any concerns.

It's scalable.

I would rate technical support as six out of ten.

Setup is straightforward. It takes a week to do the installation and configuration.

It's not difficult to maintain.

I would rate this solution as eight out of ten. 

I would recommend this tool to other users.

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.