Informatica Intelligent Data Management Cloud (IDMC) Reviews

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. 

Informatica MDM is used for all data management practices use cases, such as centralized master data, cataloging, and metadata management.

The most valuable features of Informatica MDM are its reliability, match functions, and integration capabilities. The out-of-box functionality of deduplication and built-in data models ensure faster implementation.

Informatica MDM could improve the interdependency with integration. The solution sometimes becomes a bit difficult to change considering a lot of interdependency with the integration. There can be some improvement in the workflows and they can introduce more artificial intelligence.

In a future release, Informatica MDM could improve the UI and create an easier way to change the existing setup.

I have been using Informatica MDM for approximately 20 years.

Informatica MDM is stable.

Informatica MDM is scalable. However, sometimes it becomes difficult to perform the change. When it comes to volumes, it's fantastic and very fast.

We have an entire organization of approximately 80,000 using the solution.

The technical support from Informatica MDM is good.

I have previously used IBM, SAP MDG, and Parallels.

If an organization has a quite complex setup with different systems then I would recommend Informatica SAP MDM because of the integration capabilities. If the organization only has one ERP, then it's not advisable to use Informatica MDM because SAP MDG is quite integrated with SAP.  The IBM solution I use quite a long time before, but I don't know how they are doing today.

The setup of Informatica MDM is easy.

We have two people that do the development and maintenance of the solution.

Informatica MDM recently changed its pricing model. It's usage-based but I don't have much insight into the current pricing.

Whether to use Informatica MDM or not is highly depends upon what is the use case and the core structure you have in the organization. If you have a small company with limited systems, then you use something lightweight MDM. Where you have more than one ERP, all technology interacting with each other, then I would suggest a solution, such as Informatica MDM, it is a good deal.

I rate Informatica MDM a seven out of ten.

I use Informatica Enterprise Data Catalog for searching for PII data, tagging different kinds of data, and for data lineage.

These are the features I found useful in Informatica Enterprise Data Catalog: one is its data profiling is good. The data lineage is also okay, though it had a few issues to be solved. The data domain discovery for the solution is good, though it was hard to implement.

Informatica Enterprise Data Catalog is hard to set up, so this is an area for improvement, e.g. it would be good if they make it easier to set up, because the project was made 80% of the time of the setup. Another area for improvement is its ease of use, because the interface is not as user-friendly.

I've been using Informatica Enterprise Data Catalog for the last three years, and the last time I used it was three days ago.

Informatica Enterprise Data Catalog is not as stable.

Informatica Enterprise Data Catalog is an easily scalable solution.

The technical support for Informatica Enterprise Data Catalog is not so good, because it took a lot of time for them to solve simple problems.

The set up for this solution was not easy.

My advice to other people who want to implement Informatica Enterprise Data Catalog is that they need to be sure that it can deliver the expectations they have about the data catalog, because after our implementation, we weren't able to use it a lot.

I'm rating Informatica Enterprise Data Catalog seven out of ten.

We use the tool to collect, integrate, and process the data from different sources. Later, we direct the processed data to the required solution for analysis purposes.

It is a cloud service integration platform providing flexible and scalable data management architecture. It enables seamless integration with large data ecosystems, including Hadoop and NoSQL databases. It supports real-time data streaming platforms as well.

They could provide more robust performance for data integration processes. It would help in improving the data quality more efficiently.

We have been using Informatica Data Integration Hub for the past six months.

I rate the platform’s stability a seven out of ten. The complexity depends on the types of data. It has a robust software architecture.

The product offers two types of scaling mechanisms. We can add more nodes, integrate the service grid, and distribute workloads across multiple processing units. Also, we can add more resources, including CPU memory. It enhances the capability to handle large data volumes.

We can even utilize the load-balancing feature while handling high volumes of data. I rate the scalability an eight out of ten for efficient adaptability, pricing, and performance.

The technical support services are good.

The complexity of the initial setup depends on several factors, including types and volumes of data. It also depends on the data integration and configuration.

Working with a healthcare client with diverse locations, we faced the challenge of analyzing data in isolation, making it difficult to generalize findings across different areas. With the help of Informatica Data Integration Hub, we can collect data from various locations and enhance business insights.

We are familiar with centralized publishing and subscription models. It ensures the enforcement of data governance policies across all data sources and consumers, promoting data consistency and quality.

The automated artificial data synchronization facilitated by the data integration hub has proven invaluable in supporting our daily operations. It ensures the continuous updating of data, preventing delays and inaccuracies that may arise from using outdated information in analyses. This capability became particularly crucial during the sudden changes brought about by the COVID-19 pandemic, allowing us to adapt swiftly to the evolving business landscape. However, they could provide us with real-time data to increase the efficiency of manufacturing processes.

I advise others to understand the different data resources available in the organization before making the purchase decision. I rate it an eight out of ten.

We use Informatica Axon to make sure our data is in good shape across different apps. It helps us work with clients to set rules for data and keep things organized. For a bank, it makes sure customer info, like contact details, is correct and follows privacy rules. Axon also made it easy for our team to check and trust the data we were using. It is like a tool that brings everyone together and helps us find and use data better.

The most valuable feature of Informatica Axon has been the data marketplace. It has been a favorite because it not only boosts user engagement but also fosters collaboration. Implementing it was straightforward, and it seamlessly became a part of our organizational culture, making it easy for people to work together and share information.

One area I would like to see improvement in Informatica Axon is achieving feature parity between the on-premise and cloud versions. It would be great if the cloud version could match the full range of capabilities available on-premise. This would ensure a seamless experience and allow users to leverage all of Axon's features regardless of their deployment environment.

I have been using Informatica Axon for almost two years.

I would rate Informatica Axon at eight out of ten for stability. The main thing to improve is making the features and interface consistent between the on-premise and cloud versions. The cloud interface looks modern with DDGC, but the on-premise one is a bit outdated. Aligning them would be a big plus.

It is quite scalable. We had approximately 500 end users.

The standard support is good – they usually get back within the agreed time. If you have a higher-level support contract, like gold, silver, or platinum, you get a faster response, but the support team is generally effective and helpful.

Setting up Informatica Axon varies, but it generally depends on having a good grasp of data concepts. If you understand data well, the setup becomes more straightforward. Deploying and maintaining Informatica Axon depends on the use case, but I would say not too many people are needed. I would recommend at least two people per department or business unit to start with. It is good to have a mix, like an admin or engineer and a developer. One person could handle the technical side, while the other, who understands data and processes well, can provide expertise.

The licensing for Informatica Axon is expensive, but it provides value for the investment. With the new cloud platform, they have introduced a consumption-based license model, where you only pay for what you use. This change has made it more affordable and easier for users.

For those looking to start using Informatica Axon, my advice is to do thorough research, especially on available solutions, as integration with other software plays a big role. With the Informatica cloud solution, you have the flexibility to choose features that suit your needs. Starting with data quality is usually a good move before diving into more complex tasks. Consider exploring tools like robotics for repetitive or tedious tasks. Having someone experienced with data is a significant advantage, as these projects often have long cycles. Experienced individuals can guide you, help set realistic expectations, and emphasize the need for patience, as data governance projects take time to show results. Overall, I would rate the solution as 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 are customers of Informatica PIM and I'm a senior architect. 

Informatica comes with a predefined data model which is the way in which you enrich your products. It acts not only as master data but also as a product enrichment tool. The product provides flexibility; you can go for an undefined number of attributes that define a product. You can plug it in with any e-commerce website. That's its value to us and why we need it. 

Database access is highly restricted with PIM. If you're using the cloud version, you probably won't have database access or a view of it. If you're wanting a customized application, you can develop the out-of-the-box PIM solution with a little bit of customization here and there without even needing a database. That's a very big drawback. As a developer or as an architect, you need to have a data model. I know some people use it without database access and the issue is that they don't know what that data model is built on other than just seeing it through UI tabs. The one thing I'd really like to see is for the solution to be made scalable. 

The solution is stable, in terms of bugs they're very good. They keep evolving their toolset. I have encountered many bugs in Multidomain MDM, but to date not in P360.

Scalability depends on your use case. If you're using it as an integrator, then it is definitely scalable. That said, it would require an altogether separate MDM solution. If you don't have MDM, then there are likely to be some limitations. We're in the process of installing now but in my previous company, we created the core set of attributes through MDM. From there it went worldwide through an e-commerce website. We have 50 to 60 people internally using it as a tool. If you're exposing your data through an e-commerce website, then it's accessible to all, although just for reading and not for updates.

If you're working with Informatica, you need to interact with them on the out-of-the-box features. They are very efficient and quick in their response times. 

I've trained in Stibo which is a little bit better than PIM and I've used Oracle PDH and CDH. Those were basically a package MDM solution. If you're using SAP, I would suggest Oracle products. But there's been a very big evolution over the past decade when it comes to enterprise MDM tools. Most people working in companies are disbursed in different locations and using multiple toolsets, they can't be restricted to one technology. That's the reason that Informatica, Stibo, Riversand, and other technologies are very useful and very powerful. When comparing PDH to PIM or CDS to Multidomain, managing the Informatica toolset is easier in terms of effort required in comparison to managing Oracle MDM or Oracle CDH or PDH because they have their own set of limitations. The good thing is that they can be very easily coupled with an ERP solution. Here, you have to build real-time or multiple interfaces. 

The setup is relatively easy I would say. But if you need additional attributes, it gives you a repository manager feature where you can use XML, add your own attributes and then configure it. To my mind, the setup is simple to moderately complex.

Licensing costs are a little pricey. For my previous client, as a support contract partner, we were making less money than Informatica was charging them. 

Informatica 360 PIM was bought from Heiler and is a very good tool if you already have MDM in place and you simply want to use it as an enrichment tool. With Informatica, you perhaps need to go somewhere into the roots of Multidomain. P360, Multidomain, and C360 are all different things. Managing a thousand plus attributes into that data model is going to be very complex. If they could come up with a standard data model that Oracle offered customers like PCH or PDH, similar to what P360 has, that would be my preference. Also, my recommendation is to always utilize your team as an integrator rather than being a master data manager.

I rate the solution eight out of 10. 

I use the solution in my company and have worked with two tools from Informatica, both on on-premises and cloud models. I have experience with Informatica Axon, and I have used the cloud services under Informatica CDGC.

The use case of the tool is basically in the banking sector. It is used to optimize certain areas of a project. In Europe, we have a GDPR implementation. In the Middle East, there is the Central Bank of the UAE and UAE data protection law. Implementing data protection laws and ensuring that all the policies are enforced for financial security is my use case. I have to make sure the bank or financial institution meets the requirements of the Central Bank of the UAE. Data quality is another use case where my company handles corporate and retail customer data, and protecting their information is known as PII. The tool ensures that the system holds the PII data properly.

For data lineage, we look for things at a transformation level and how the data is transforming and managing the ETL mapping. Every tool gives this information about how the data goes, but our company is interested in knowing how the data is transforming and the transformation logic between the two data sources.

There are some tool limitations. Some connectors do not scan the metadata properly. If I want to scan the metadata from the data lineage or the Python code, such areas can get tedious in the tool. To manage such areas, one needs to have a lot of coding knowledge, and you need to know how to apply the code, and only then can you get it fixed. There is no user-friendly enterprise.

There are certain shortcomings even if we opt for subscription-based technical support.

I have been using Informatica Axon for four years. I work as a consultant.

It is a stable solution. Once it is implemented, we will handle everything for the business. Stability-wise, I rate the solution an eight out of ten.

It is a highly scalable solution. Scalability-wise, I rate the solution an eight out of ten.

The tool is meant for enterprise-sized businesses.

I rate the technical support a six out of ten.

Neutral

I have experience with Informatica Data Governance.

If one is difficult and ten is easy, I rate the product's initial setup phase an eight out of ten.

The solution is deployed on the cloud, specifically if you have cloud-based virtual machines. If there are compliance issues, and you need to hold the metadata only on-premises models, you can do that, too.

The solution can be deployed in a few days.

It is an expensive solution. I would say it is the most expensive solution in the market.

For the features of the software, the price is justifiable.

Speaking about how the tool enhances data governance tasks, I would say that we have three types of users, consisting of the consumer, who are normally a business user, then we have a developer and finally the admin. Our company onboards the user, and then the user can collaborate, comment, ask questions, give ratings to their assets, publish the data to the marketplace and go for downloads.

One needs to resolve the problem that stems from the fact that different people can have different understandings of the concepts associated with the tool. A database administrator may see an area as a table, but for a business, it may be a person. The tool gives you a common understanding of the business concept. The tool also provides lineage data and how the business data is performing. It provides an interface between organizational policies, the different processes governed by a certain policy, and the different systems governed by which policy. The tool gives you a 360-degree holistic view of the data.

The cloud version of Informatica Axon utilized the AI for the classification purposes, data domain and automatic data tagging. In my company, we use the tool's AI capabilities.

I will recommend the tool to others.

I rate the tool an eight out of ten.