Informatica Intelligent Data Management Cloud (IDMC) Reviews

What I like best about Informatica MDM is its structured, table-based approach. Unlike Reltio, where data is only visible through the UI and cloud-based, the solution allows access to normalized tables. This means I can directly query and see data in each table. For instance, I can easily get all customer details from the customer table. However, for more complex queries, like seeing all customer interactions with the organization, some SQL knowledge is needed to join different tables and retrieve the details.

The tool could be improved in terms of ease of use, particularly for those without technical expertise. Understanding and extracting data from the table-based structure requires some SQL knowledge and technical skills. Additionally, while Informatica MDM has moved towards a cloud-based MDM with a UI similar to Reltio, I haven't used it, so I can't comment on its effectiveness.

I have been working with the product for six months. 

I haven't had any issues with the tool's stability. 

I'm not entirely sure about scalability, but I've heard that adding custom features can be complicated. We have to go through several steps. First, we need to determine if we're adding a column to an existing Informatica MDM table or creating a new one. Then, we have to contact Informatica with our customization request. They do the customization. After that, we have to check if it's working correctly.

In our organization, we use Informatica MDM in a specific way. It's primarily based on tables; users don't directly log into it. The process works like this: data flows into the MDM tables as an inbound process. Once the master data merge has been completed, the output data flows out as an outbound process.

The tool's support team is good. The product is quite technical, and so is the support team. When we have questions, we reach out to them, and they provide answers. Their response time is also good—we don't have to wait long for replies.

I rate the overall product a seven out of ten. If you don't have the budget for Reltio, then you can go for Informatica MDM. 

On one of my projects, we used Informatica Intelligent Cloud Services for ingestion purposes. Secondly, we used it as a regular ETL for performing heavy transformations.

In our current scenario, we are moving our on-premise artifacts, which are on PowerCenter, to the cloud. It was surprisingly quick to get everything working, which has been beneficial for our operations.

Informatica Intelligent Cloud Services offers a wide variety of services, including Cloud Data Integration, which is akin to a replica of PowerCenter on the cloud. I particularly like the mass ingestion service.

The cloud version of Informatica, although easier and more advanced than PowerCenter, still requires a deep dive to fix bugs. It could be improved by making the process as intuitive and easy to follow as PowerCenter.

I have delivered two projects using it, so from my experience, the tool is very good.

There are some bugs and glitches, which for a beginner, can take time to resolve. This may be because I have spent less time on the tool compared to others.

Scalability doesn't impact Informatica technically, but it does take a lot of money when we keep adding users.

Informatica technical support is excellent. I would rate it a nine. They are top-notch.

Positive

The initial setup is easy and not complex.

Pricing is a bit high, similar to a premium version or a high-end product, and requires a budget ready to manage it.

During POCs, we explored other ETLs like Firetran for ingestion purposes, but Informatica's capabilities are robust.

For a robust use case, especially for large enterprises, Informatica Intelligent Cloud Services is a good tool with good support. However, make sure to have a budget ready.

I would rate it an eight out of ten.

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.

Data quality is missing enterprise-wide in our bank. We use the solution for all the customer data to judge the metrics of software data quality from the source systems.

Server maintenance, server hosting, backup, restoration, and DB capabilities are not needed in the cloud. There is no crashing of the servers. The admin part is very seamless in the cloud, while administration is a big task for the on-premises version.

The on-premises version is very mature, but many of the on-premises features are missing in the cloud. It is still in the development stage and has not yet matured in the cloud. The tool has a lot of product errors that need to be fixed. We face a lot of internal product errors while doing the configuration and quality checks.

The on-premises version has many use case transformations, but they are missing in the cloud. The cloud version has only four to five types of use case transformations. You cannot import the data discovery rules you create in the solution to the Cloud Data Governance and Catalog (CDGC).

I have been using Informatica Cloud Data Quality for six months.

We face many glitches during the configuration because it is a new product. It will take another year to mature.

The solution's scalability is seamless in the cloud. You can scale the solution within one or two hours.

The solution's customer support is wonderful, but they are not up to the mark knowledge-wise.

Positive

The solution can be implemented in one or two days. There are steps available to deploy the tool. One person is enough to procure the VM or the server.

Informatica Cloud Data Quality is a costly solution.

The solution's competitors include Oracle Data Quality, Collibra, and Azure Purview.

The solution provides data standardization capabilities. Since Informatica Cloud Data Quality is a SaaS solution, it does not require any maintenance. Since it is a cloud product, many connectors have configuration issues. They have to add some other parameters in the tool levels. We face such challenges in the cloud, not on-premises.

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

We use Informatica Cloud Data Integration to load data from files to TelSource or Oracle tables. We also apply business rules to transform the data before loading it into the respective targets.

Most of the features are good. The advanced features like task flow and conditional integration are particularly useful. There are multiple transformations we can use in Dashflow, which are beneficial. We don't use features like centralization and data marketing because they aren't relevant to our use case. Our primary focus is on task flow, which allows us to design our jobs and execute them conditionally.

Some features require an additional license, such as Elastic Mappings. Most of the features provided are through Elastic Mappings, not the data integration service which causes restrictions. For example, the recently enabled source partitioning isn't applicable to Salesforce, which we use as our target or source. We primarily seek features that enhance performance for Salesforce and ICS Integration, aiming to reduce job execution time.

We don't have the license for Elastic Mapping, so we can't use that feature. Most of the new features added by Informatica are through Elastic Mapping. It would be helpful to have features like multithreading or partitioning for Salesforce to enhance performance.

I have been using Informatica Cloud Data Integration for five years.

The product is stable.

I rate the solution’s stability a seven out of ten.

20-30 users are using this solution.

I rate the solution’s scalability a five out of ten.

Support is good.

Positive

The initial setup is very easy. When I first started using it, I installed a 30-day trial version. I personally explored it during that period, and it was good.

It takes 30-40 minutes depending on the jobs.

I rate the initial setup a ten out of ten, where one is difficult, and ten is easy.

The team is very user-friendly, meeting our expectations much like PowerPoint does.

It supports integration with most cloud sources, including AWS, and has various cloud connectors. So, It's a good choice for anyone.

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

So my use case was on migration.  I've been using these products for migration activities. And providing any QA solution for the integration to other platforms like Databricks.

There are newer technologies in the market that offer better solutions compared to traditional ETL operations. For example, if we use Spark on Databricks, it's more optimized and runs much faster due to its backend capabilities. Whereas Informatica Inc.'s Cloud Services provide cloud-based solutions. The ETL works on the Informatica engine, which is comparatively slow. But the compatibility of data and other integration and data warehouse works well for IICS.

The interface is really good. Another valuable feature is that it is user-friendly.

There are a few improvements which can be done. So those are on data governance and making an image of each object that is being created on top of Informatica, I mean, on top of applications. So those need areas to be improved.

The logging methods are really traditional. So logging, in order to track any operations happening on this interface, will catch a log file. That needs to be more precise.

In future releases as well, I would like to see additional features. So there is no platform where code conversion can happen easily. For example, if you want to move Informatica jobs in various areas, it's quite easy and straightforward. But still, you require some manual intervention for code changes that need to be done throughout the platform. So these things need to be improved. 

And other things are the compatibility of other services. For example, if you have a running Spark code and you want to run the Spark code into Informatica IICS, which is not compatible, so you need to rewrite the whole syntax to make it compatible. So those are the areas that really need improvement.

I have been using Informatica for three years. We currently use the version Informatica Cloud IICS.

Stability is good. I would rate it a seven out of ten. 

Scalability is good since from on-prem to cloud, there's a huge performance boost. So on a scale from one to ten, I would rate it eight.

The setup is complex. Because it's not about the data; it's about the complexity of the pipeline, the complexity of models which have been designed for data engineering. And it's not something straightforward, and the migration cost goes higher on this aspect for this reason.

We have multiple platforms with it. Some of them are running on-prem, and some of them are running on the cloud.

There is definitely an ROI because many companies are preferring to put data in the cloud, and they want to reduce the migration cost. So without any major efforts or challenges in the migration activities, if that's the case, then moving from Informatica on-prem to IICS is a better choice.

Comparatively, other services are providing a lower price, but since moving from Informatica on-prem to IICS, the pricing factor is much better. So when we compare two platforms of the same vendor, it's a good price.

On the evaluation, I have personally evaluated the migration work that I have done. So it is really easy for Informatica users who have been using the same on-prem product. For them, there won't be any challenges in learning any technical aspects of the cloud. So it is almost straightforward. And there are good services provided by Informatica, like integrated things and driver compatibility. So, everything looks much better when it is in the cloud.

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

We use the solution for ETL.

It's a powerful tool to create data warehouse solutions for our clients. We take unstructured data and use Informatica Cloud to structure it in various ways, making it usable on a reporting front end. This enables clients to make informed business decisions based on the data.

It's the accessibility and the range of features that stand out. Before using Informatica Cloud, we were working with Informatica PowerCenter. The transition from PowerCenter to Cloud wasn't entirely effortless, but it was seamless enough for our developers to adapt and continue their work smoothly.

Our main issue is transitioning from on-premise to cloud data storage. As many clients move their data to cloud platforms like Azure, Snowflake, and AWS, we're encountering problems with Informatica. Errors that were straightforward and clear with on-premise databases now appear ambiguous in cloud environments. Our developers spend significant time reducing these generic errors, often simple issues like a column not accepting null values. This lack of clarity is causing unnecessary delays as they have to sift through logs or contact support to diagnose problems that would have been more easily identified in an on-premise setup.

I have been using Informatica Cloud Data Integration as a financial partner for over five years.

We have about seven developers. It is a scalable solution.

When errors arise, contacting support can be frustrating. Sometimes, the technician can't solve the issue and transfers us to someone else. This makes us less confident that the person helping us is truly equipped to resolve the problem.

Neutral

The initial setup is simple and depends on the task. However, it usually takes a couple of hours if development is complete and we're moving from the development environment to production.

ROI is strong because we have a structured portal that ensures development is done correctly. It is shareable, scalable, and equipped with enough monitoring tools to quickly address any issues. Ultimately, the client doesn't care what tools we use. They just want problems resolved quickly. Informatica provides the necessary tools and features to help us do that effectively.

It has premium pricing. Depending on what we're working on and which features we're using within Informatica, there can be additional costs. It's mostly data integration, but you might need to upgrade your license to include other aspects of Informatica. Certain connectors require a license upgrade to access.

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

We use the solution for data cataloging and lineage.

The valuable feature is metadata management. If you want to trace sensitive data, you can auto-classify them. You can search for sensitive information through EDC. Using Discovery, you can identify if there is any type of data set.

EDC is only used for cataloging and meetings. Currently, not many different databases are integrated with it. The ETL logic should be visible within the tool. If EDC is integrated with Axon, you will see the data lineage and catalog because of EDC. If EDC is removed, you cannot see any lineage or catalog.

We need EDC on the application level. Currently, it is only at a system level. It can be shown as an application layer between policies or regulations. This kind of feature can be enabled.

The integration with other data management tools can be enhanced. For instance, there is no integration with tools like Collibra or Hubview.

I have been using Informatica Enterprise Data Catalog for seven years.

The solution is stable.

EDC needs many ports to run. Therefore, to improve performance, you need to increase the number of cores.

The initial setup is easy and takes two weeks to complete. One person is enough to deploy it.

EDC gives you a better understanding of architecture and the system used. You cannot use EDC completely unless you have access.

The product is expensive.

EDC is a standalone application, so it doesn’t really make much sense. It doesn’t give you a lot of features that way; it’s primarily for cataloging and classification. Nobody would buy EDC as a standalone application. When people are buying EDC, it’s always with Axon.

I recommend buying the solution altogether with Axon.

Overall, I rate the solution as seven out of ten.

Informatica Enterprise Data Catalog was used by our company as proof of concept for projects related to comprehensive data governance. 

The solution has multiple valuable features for metadata collection from multiple data sources or technologies. The solution manages data and acts as a central hub for setting up data governance processes. 

The automated scanning of metadata from data sources is one of the most vital features of Informatica Enterprise Data Catalog. The solution comprises attribute features and AI capabilities for automatic relationship discovery between different datasets.

Another powerful feature of Informatica Enterprise Data Catalog is data lineage. The whole path of data transformation from one location to another using certain technologies is represented in Informatica Enterprise Data Catalog. The solution integrates seamlessly with other products from the vendor and allows the creation of comprehensive data governance processes.

The aforementioned integrations facilitate the coverage of semantic layers in addition to the technical data. There is another business glossary product from Informatica that easily integrates with Informatica Enterprise Data Catalog to consume data harvested by Data Catalog, which makes a powerful combination. 

The user interface of the product needs to be improved. Informatica Enterprise Data Catalog captures huge amounts of data and along with this data, the interface becomes comprehensible only for users with advanced technical knowledge. Even for advanced users, it becomes challenging to move around vast amounts of data collected by the solution. 

Some competitors of Informatica are trying to implement some brilliant ideas, but they lack the coverage provided by Informatica Enterprise Data Catalog. The data lineage feature can also be further improved.

While using the solution, the data is being transmitted outside the client's network to the Informatica cloud, which can be a security concern; the vendor can solve this by enabling the product as part of a public cloud like Azure, AWS, or Google. The aforementioned scenario can be a concern for institutions like banks where there are legal restrictions and data needs to be fully under control. 

I have been using Informatica Enterprise Data Catalog for a year. It was used in two different projects in our company, each of them concluded in six months. 

I would rate the stability of the product as seven out of ten. 

The customer support is satisfying, but the turnaround or response time is quite long as the vendor needs to support a huge number of customers daily. At our company, we have noticed that there are experts in the support team who can provide effective solutions. 

The tool's initial setup is complex. I had experience with the on-prem deployment of Informatica Enterprise Data Catalog, but I believe the cloud version is easier to set up. The solution's deployment takes around three to six months.

About four to five professionals are required, including technical administrators and data governance experts, for the on-prem deployment of the solution; for cloud deployment, three professionals might be enough. 

It's a very expensive solution. 

Informatica covers the widest area of technologies in comparison to other vendors and they also have a network of partners who develop add-ons for extending functionalities or data source technologies which could be integrated with Informatica Enterprise Data Catalog. The solution provider has a wide partner ecosystem to provide features on APIs and special custom formats that could be imported or integrated into varying processes. 

The solution's features can be extended and the vendor provides useful documentation and training on it. Informatica Enterprise Data Catalog is a reliable platform due to its extensibility and cooperation with other partners. I would overall rate the product an eight out of ten. I would definitely recommend others to use the solution, given that there isn't a requirement for in-depth analysis. 

The critical data lineage feature acts as a link between every aspect of data governance, including an explanation of the data journey and its history which reflects the business growth. The powerful AI capabilities of the solution allow you to automate the management of massive amounts of data, especially the aspect of associating technical metadata with business terms.

When dealing with millions of data attributes its not possible to manage data manually, therefore Informatica Enterprise Data Catalog is needed to automate 60 to 80 percent of data association between business terms and harvested technical terms.

If the Informatica Enterprise Data Catalog deployment is carried out efficiently, it can greatly impact your organization and enable business capabilities to further improve business processes. 

The main purpose of this tool is for file transfers related to our Python server.

The data integration and synchronization features in IICS improve the data handling processes.

I haven't had the chance to explore all the features in-depth since we've only been using them for a couple of months.  

I appreciate that it's a cloud-based solution. With a good internet connection, it works smoothly.

It also offers multiple features. 

There's definitely room for improvement in terms of user-friendliness.

One example is that you can't search for jobs directly by file name. You can only search by job name. So, if you want to find a job that works with a specific file, you have to go through each job individually to find the right one.

So, I'd like to see a faster search, one where I can search directly by file name.

Moreover, the support team could improve by adding things like file transfer status updates. Also, if someone modifies a job and then leaves the company, that shouldn't disrupt the job for active users. It would be better if the job continued to run smoothly regardless of who modified it.

I have been using it for seven to eight months. 

It is a pretty stable product. 

Scaling is easy. It's not overly complex. In our team, we have around 10 to 12 people using it. Additionally, there's a separate IT team dedicated to IICS with over 50 people. Other private projects likely use IICS as well.

We sometimes face challenges when implementing new features. In those cases, we contacted support, and they've been very helpful.

wWe're happy with the support team.

It is a cloud service. We use AWS and Azure Cloud. I'm not fully sure about the installation details, but I know we use AWS and potentially other cloud features as well.

If you have experience with similar tools or a general understanding of IT concepts, it's easier to grasp. Learning the features takes time, but with an IT background, you should be able to figure out the basics. 

We all encounter challenges sometimes and need to learn new things. Overall, it's not overly difficult or overly simple. It's manageable if you have the right mindset.

It's definitely a good tool, especially if you're using cloud services and an S3 bucket. It has many features to simplify your work and make your life easy. It's not overly difficult to learn, but proper training is essential to understand and make the most of all the features.

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