Informatica Intelligent Data Management Cloud (IDMC) Reviews

We are currently working on a project with the Oracle Fusion system, so we have multiple use cases and often need to pool data in different source systems. In the project, we have multiple sources and target systems. Based on the requirements, clients, and what they propose, we need to make decisions or check the technical feasibility of whether it is possible to complete the integration.

Product-wise, compared to other on-premise tools, Informatica Cloud Data Integration can be deployed on-premises and cloud. So when we were working on-premises, there were a lot of challenges with the hardware. For example, there were memory space issues, but once we switched to cloud, there were no more issues. 

There are challenges when we use Cloud Application Integration (CAI). We want add-ons when we complete data integration and merge images. The current features are a bit complicated, and we need to write big scripts and test.

We have been using this solution for more than six years. We are using a cloud version and the most recent version, 10.4. We have also used versions 8.6, 9 and 10, and we have observed that there isn't that much of a difference between versions, just additional features added. We do not have private or public cloud for Informatica Cloud Data Integration, just cloud.

The solution is stable. 

The solution is scalable. We have more than 20 people using this solution.

We hardly raise an SR for this solution. But, whenever we require technical support, we do not get a satisfactory response. This is because their knowledge base may not be developed.

We used this same tool but on-premises in the past. We have also worked with AWS Snowflake, an ELT tool similar to Informatica Cloud Data Integration but with a different architectural approach. If we had to rank them, Informatica Cloud Data Integration would be the best, followed by Snowflake, then AWS.

Informatica Cloud Data Integration has some advantages over the others. It has a more UI-based tool, and the scripting is good. AWS also has an ETL tool called Glue, but it does not have everything we need to write in a script. We still need to write a script if we want to perform a small task. AWS is also challenging to teach. Informatica Cloud Data Integration and Snowflake are easier to use.

The initial setup is easier for cloud compared to on-premises. Deployment does not take much time and takes about 20 to 30 minutes.

The pricing of Informatica Cloud Data Integration and other solutions are almost the same but with slight differences. It differs from project to project, their use case, source and target. Unfortunately, I do not have information on precise licensing costs.

I rate this solution a nine out of ten. Regarding advice, it is a great solution, but users should understand their source and target system. For example, we also deal with Oracle Fusion, and it's a bit challenging to push data because Oracle has multiple models, financial supply chain and HR. Hence, it is difficult for a developer. Therefore, it is difficult to push data.

They should decide whether they are comfortable using Informatica Cloud Data Integration as their middleware tool or whether they want to use Oracle or OCI. OCI is a different middleware tool owned by Oracle.

Regarding additional features in the next release, Informatica Cloud Data Integration doesn't have image merging transformation or capability. We can do it without the solution, but it is a lengthy process. So, it would be helpful if they added the transformation to play with images and deal with invoices and financial data. We sometimes need to add 200 out of 800 invoices, and it's a bit challenging without the additional features.

We were trying to publish a compendium of all our various assets using an Oracle-based data warehouse. We also had vendor-based solutions like Epic for electronic medical records on an SQL Server base. We had many research systems on various platforms because it's a cancer research institution. 

We wanted to pull together a comprehensive data catalog to show people all the different assets we had and where they could go to find things. If there were vendor-based definitions of things, we'd pull in the definitions and various attributes. It's a heterogeneous environment data-wise. We get a lot of value from a comprehensive enterprise catalog.

It's available on our intranet through a data governance portal. You could go there for a catalog, quality reports, etc. In a year, there may have been 500 unique visitors. It was my job to publicize it, but I didn't necessarily do a good job. I worked with research groups and clinicians to get their stuff on it, and they would tell other people about it. The nice thing about Informatica is that it was easy to link from our internal web portal to their catalog. I had excellent developers working for me. It didn't require much development, and it took less and less as time went on. 

I like EDC's self-service capabilities. You can put the catalog on the intranet inside the organization, so users can search for something. People in the research world have specialized systems, and you might find data from various places that sound similar. 

The purpose of the Enterprise Data Catalog was to build an internally searchable catalog of stuff. You may not have permission to see this data but at least you could find out where it was and contact the person who owns it. 

Interoperability is one area where EDC has room for improvement. It was challenging when the faculty took over the data world and had specific vendors they wanted to use, and some were not particularly open platforms. 

It was a challenge to promote data visibility while also jumping through hoops to take some of the proprietary things and make them part of the calling, especially when the vendor doesn't necessarily support interoperability. You need to export things from a vendor program and import them again. 

We used Informatica for a lot of the data governance stuff I worked with when I joined the company, including things like cataloging and profiling data. The organization has really changed a lot in the last year and went with Informatica EDC. They're moving from the on-prem version to the cloud.

Informatica is a strong company, and EDC is a solid platform. 

The scalability is excellent. Informatica really knows what it's doing. They're smart people and great engineers. 

Informatica's customer service and support were decent. They listen to their customers. If something is missing or wasn't working, they will put it on their roadmap. They were listening to customers for roadmap stuff. 

We wound up building a staging database to pull stuff out of the EDC, stage it, and then access that. It was open, so we would often have an intermediary layer at Oracle. If we wanted to show, for example, data quality over time, we would have a weekly quality process that would run. We staged that in an Oracle database, and the portal could access that.

We had to build Informatica pipelines and do some Azure work to feed data to them. With data warehousing, you typically have static data that is timestamped daily or weekly and sometimes monthly or annually.  We were trying to get real-time data, like blood pressure monitoring and stuff like that. That was a lot of work. I didn't do it. The integration team. 

When I joined the company, it was an Oracle-based solution. Then Epic took over, which was SQL Server-based. After that, they went to Azure. Now, all the analytics are supposed to be on this platform, and it's not particularly open. 

Setting up Informatica EDC is usually pretty straightforward. The challenge is working with vendors like Oracle and Microsoft, which have APIs for integrating things. You can query what they have. They want it to play well with other vendors because they know customers don't only have one brand of product. In some cases, you get vendors in there that are, "No, we're not going to do that because we're so special." It was a challenge. The platform of choice for data initiatives at the cancer research institution is Palantir. 

We didn't look for an alternative, but Azure has its own catalog.

I rate Informatica Enterprise Data Catalog nine out of 10. It's a great solution, and I was happy with it. It did everything I wanted, and Informatica dramatically increased the integration points over time. When we started, it was like Oracle and SQL Server, but now they're adding NoSQL databases and others.

Informatica has user groups and listens to user input. One of the people that worked for me hosts an annual Informatica user group in Houston. You can try to build your own Oracle-based or SQL-based solution. They listened to the market, and they're working on improving the interoperability. Maybe it works better with Palantir since I left, but they work across all platforms. They're making it Cloud-based. I didn't know anything about them before I got here. I was dropped into a department where Informatica had been for at least five or six years, and it was a good choice.

We essentially use Informatica Axon to set up a data governance framework for a corporation, usually a medium-sized or large organization.

The dictionary, the search, and the ratings are without a doubt the most beneficial components of this solution. 

Socializing data governance is one of the examples, but I'm not sure what the others were. For instance, if you locate a specific data attribute, you can grade its accuracy by assigning it a star rating between 0 and 5. 

When someone else conducts a search, they might discover whether employees at the company believe the data to be of high quality.

In terms of additional features, I believe it is quite rich. As I previously stated, it is a fairly mature product.

The main issue probably has nothing to do with end users, but installation can definitely be simplified. Also, I believe that this is something that they are already working on it, but it needs to be provided as a service. 

The Microsoft version, Purview, is now available as a cloud service, it must be provided as a service rather than just installation. You do not need to go through the installation, you literally create an account in five minutes. That is something they need to do. I believe that it is already something they are on working on, but I don't believe it has yet been released.

Over the past year, I have definitely used Informatica Axon.

I have worked with Informatica Axon for two years.

We are always working with the latest version.

Informatica Axon is a stable product.

It's a fairly mature product. For many years, it has been the market leader.

Informatica Axon is a scalable solution.

The smallest organization would have 500 users.

Any of the multinational corporations could be the largest. It's quite pricey. 

It is commonly used by large multinational corporations.

It has two or three user interfaces, one for everyone in the organization, one for specific data analysts, and one for IT technical staff.

Like many organizations, technical support responds quickly at times. It can take some time. It's about average, in my opinion. I wouldn't say it's particularly good or bad. It's average.

I would rate the technical support a three and a half out of five.

Neutral

I am just really familiar with Azure DevOps as a deployment technology.

Some of the Azure services, such as Database and Purview, and Informatica tools, such as Axon, and Data Governance, are among the things I am familiar with.

Informatica Professional Services should absolutely perform the installation due to its complexity. Additionally, training is required for end-client configuration. It is not something you can pick up and configure immediately.

Although there is no cloud version of it yet, it can be deployed in the cloud as a virtual machine, or VM.

Axon itself, you normally allow anywhere between five and ten days to conduct the installation configuration together, and that's not elapsed time. It normally takes a week to two weeks to install and configure an initial setup. This is elapsed time, not necessarily man hours. You will always need additional configuration to be done. Although the actual installation and configuration might be completed in a few weeks, getting it ready for use by the organization might take six months.

We do not have a technical team. I was the person who deployed this solution.

It was a challenge, but I did it for the POC.

Informatica Professional Services was consulted when it came time for the client's actual installation.

Axon can typically be present; the technical installation only requires one person, and a second data specialist is typically required for configuration. Normally two. Additional technical setup and data configuration are required.

It is definitely high if used properly, but many organizations spend all of the money and then fail to use it to its full potential. It is unquestionably a good investment if used properly.

It depends on how the client uses it.

Pricing is determined by the number of licensed users as well as the number of Core CPUs. 

You can imagine how expensive it would be for a company with 10,000 users, but it all depends on how many analyst user licenses they require. 

I believe there is a flat fee for the end user. 

It is not expensive, but individual licenses are required for technical users, data analysts, data stewards, and the data governance team, which can add up if you have a large number of them.

Different clients may have different licensing costs, but it is based on a yearly paid license. It is renewed every year. There is an initial licensing fee as well as an annual renewal fee.

They are very expensive, and they charge a lot because they know they are number one. I would rate them a five out of five. Five being the most expensive.

I would definitely recommend it. If they can afford it. I strongly advise them to use it. But, before diving into Axon or any of the other governance tools, make sure they understand their data landscape thoroughly because the tool will not help them with that. They will fail if they do not have good data practices in place.

I'm a freelancer, but the consultancy I went through is also independent, but they do have a partner relationship with Informatica, as they do with many vendors.

I would rate Informatica Axon a nine out of ten.

We use the solution to validate emails, telephone numbers, and postal codes. It can also create some data quality rules using the Cloud app's data quality function.

It offers enhanced usability with the ability to create rules quickly using its AI engine. This feature simplifies rule creation by allowing users to specify their needs, and the system generates the necessary scripts, acting as a significant accelerator. 

Another advantage is its seamless integration with other Informatica capabilities, making data quality a deeply embedded part of the solution. Informatica has a strong history in data quality with its on-premise product. All those powerful capabilities are now available in the cloud, making this product even more robust.

Accessing data as a service is essential, especially for validations requiring external data services. This goes beyond basic syntactic checks, like ensuring an email address contains the @ symbol or .com domain. Instead, it's about advanced validation, such as verifying if an email address exists or if a phone number is valid. 

These services are in high demand, especially for regions like China, Argentina, and other parts of Latin America. While such capabilities were initially more common in the United States, they are now increasingly required globally.

Five to six people are using this solution.

Informatica Support is one of the best services available in the market now.

Positive

Many clients acquired this product because of the ROI.

Informatica is one of the most expensive solutions available in the market.

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

We've 300-400 data quality rules and different kinds of rules for completeness, conformity, and timeliness. We're using Informatica to implement those rules in Cloud Data Quality.

Informatica has CDI. So, if you find some issues, you can always integrate your CDI and then fix your data.

The reusability factors are nice. The Cloud Data Quality is much better. A major flaw in the previous version was integration with the catalog, which is now seamless.

I have been using Informatica Cloud Data Quality as a partner for three months.

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

We want to keep costs down, so we are not getting enough resources.

It is suitable for enterprise level.

I rate the solution's scalability as nine out of ten.

Support response time could be better.

Positive

I use Collibra Data Quality. I switched to Informatica because Collibra cannot integrate. Colibra Cloud Data Quality is a very basic tool. There is no integration capability. If you have problem records, there is no fix to remediate them using the same tool. With Informatica, you can integrate with CDI and then create a remediation plan.

The initial setup was straightforward, and we were able to start configuring the rules quickly, etc.

It took about half a day to deploy since we are also learning.

There are different tiers based on consumption, but there is no flexible option. The catalog grows slowly over time. It would have been nice to use a flexible feature at the beginning and then transition to a model where you have a fixed set of units that you consume and pay for. If you exceed those units, you move to the next tier. We were expecting a flexible pricing structure, which we did not get.

We would have preferred a pay-as-you-go model. Although pay-as-you-go is slightly more expensive, we know our consumption will not be high initially. 

It is easy to integrate cloud data quality with IT workflow. We haven't faced many challenges. It is fairly straightforward.

I recommend the solution. 

Overall, I rate the solution a ten 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 MDM is used for our customers' master data management journey. The solution meets our client's requirements for their customer-supplier or any other entities.

The solution's most valuable features are its data quality, match-merge engine, and CLAIRE AI engine, which helps with AI automation.

Compared to other tools in the market, Informatica MDM is costly.

I have been using Informatica MDM for 13 years.

Informatica MDM is highly stable compared to any other tool in the market.

Informatica MDM is a highly scalable solution. Our clients for Informatica MDM are mostly medium and enterprise businesses.

I rate the solution eight and a half out of ten for scalability.

Technical support refuses to support us if we customize the tool. We customize the product based on the customer's needs, and we expect Informatica to provide support during that time as well.

Positive

On a scale from one to ten, where one is difficult and ten is easy, I rate the solution's initial setup an eight out of ten for on-premises and nine out of ten for the cloud version. Setting up the tool in the cloud via IDMC doesn't take much time.

The solution can be deployed within a few hours.

Our customers have seen a return on investment with the solution.

Informatica MDM is an expensive solution. On a scale from one to ten, where one is cheap and ten is expensive, I rate the solution's pricing nine and a half out of ten.

I would recommend the solution to other users because of its reliability and stability. Compared to other product vendors, Informatica MDM always has additional features. Informatica MDM has a CLAIRE AI engine, which helps with AI automation.

Overall, I rate the solution eight and a half 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.

You have to deal with a minimum of five, even if you want to go and check only a particular logic, making it an area with issues where improvements are required.

Certain shortcomings in the product's UI make it an area where improvements are required. The tool should provide ease of use and flexibility.

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

Stability-wise, I rate the solution a five out of ten.

I see that my company faces frequent challenges in the tool when it comes to the area of UI and related to the area of characters. In my company, we have experienced some issues that occur when upgrading the tool.

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

Enterprise-sized customers can choose Informatica Cloud Data Integration.

The technical support for the solution is helpful, but it takes them time to figure out the issue. The time taken to close the ticket depends on the support that Informatica gets from their backend technical team. It takes a long time to close a ticket. I rate the technical support a seven out of ten.

Neutral

The product's initial setup phase was not difficult.

The product's deployment phase can be carried out by linking a .exe file provided by the solution with your server.

The solution is deployed on the cloud.

Against Informatica Cloud Data Integration, I recommend SnapLogic, which is a cheaply priced product. People know about SnapLogic, as it comes with very good features and ease of use.

The feature of the product that I find the most beneficial for data warehousing tasks is the use of the tool for extracting and loading purposes, which depends upon the connector's availability. Many connectors in Informatica are not free or out of the box, and you have to purchase them. The tool has quality connectors.

I haven't used the tool for real-time data analytics, but I have used it in my company for batch-oriented purposes. Data integration will not be supported in real-time in Informatica Cloud Data Integration. For real-time data integration, you have to go with either the application integration or other products like Informatica PowerExchange.

In Informatica Cloud Data Integration, the transformation feature was almost the same as that of Informatica PowerCenter. In Informatica Cloud Data Integration, the transformation features may offer a couple of more functionalities.

In terms of the ease of learning that the product provides, I would say that those who have experience with Informatica PowerCenter can easily adopt Informatica Cloud Data Integration. A person who has worked on Informatica Cloud Data Integration may not be comfortable with Informatica PowerCenter. In terms of ease of use, I consider Informatica PowerCenter to be easier than Informatica Cloud Data Integration.

I rate the ease of use experience attached to the tool a six out of ten.

Only after considering the use cases of people can I recommend the product to them. If a person only wants a product for extraction and loading purposes, then I feel that there are many cheap products in the market that can satisfy their needs. Suppose someone is looking at a tool that offers widespread features, like application integration and real-time functionalities. In that case, all of it comes under Informatica, which can be a good option.

The tool is the most expensive one compared to any of the other products in the market, especially in terms of ETL functionalities or integration features.

My company has integrated SAP, many databases, and APIs into Informatica Cloud Data Integration.

I can see that the performance of the product keeps improving with every new release, especially in the area of job executions, even though the hardware may be the same.

I rate the tool a 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.