Informatica Intelligent Data Management Cloud (IDMC) Reviews

We have used it to elaborate on a project for Golden Record, for IDQ data quality, and create business cases for the control parties.

The product could be improved in the area of architecture and technology. All the parts are old.

I would like to migrate it to a new technology. It's better to have a new method for every IT system. Integrate with API, Kafka, and JMS, as API has in Jira code or Jira.

I have used Informatica MDM for ten years. I have used Version 8.6 and 9.1 of this solution.

I think that it's a good solution, but it's an old solution. It is stable because we have the experience to deploy this solution.

I think it's based on ODBC drivers, and they are not good for scalability.

We have not contacted customer service.

The initial setup was complex. It must have taken around eight or nine months to deploy all Informatica systems. The deployment processes for on-premise and cloud are different. For on-premise, we must deploy the data models, and then we must deploy the rules. We must also deploy a .Go file extension and an exposition of the vendor code, among other things.

It's different if we have an on-premise solution. The stability is for the on-premise infrastructure. It builds the IT of enterprises of clients because Informatica is at 'Legacy' level.

So, there are plans for licensing. There are subscription-based and usage-based licenses. Also, there are licenses for exceptional analytics, etc. In short, there are different models of licensing for every enterprise.

I think there is a new Jira-driven event, Jira-driven data, for the flows and extensions. So in this power center technology, I think that it's complex to navigate through the solution without new technology. Overall, I rate the solution a seven out of ten.

We use Axon for controlled and governed data sharing as well as for the policies and principles from a data governance perspective. Our use case was for an airport company and we used Axon in tandem with Datacat Log EDC. We customize data search and data sharing. We have a partnership with Informatica. 

The management of the policy is very useful. The ability to customize data search and data sharing is useful. The solution has all the necessary features. 

The GUI needs to be a little more user-friendly and appealing. Salesforce, for example, although in a different category, is very user-friendly and I think if they were to include some of the Salesforce principles, it would be helpful. Informatica needs to do a better job in terms of educating users. 

I've been using this solution for three years. 

The solution is stable and dependable as long as we keep an eye on the servers. 

The solution is scalable. 

The support process needs to be more agile. 

The initial setup took a few days. It wasn't very complex but there were some initial challenges because we were trying to setup the Informatica Data catalog, EDC, at the same time. The deployment was reasonable but not very smooth. We have around 300 users.

Licensing costs are generally on the higher side.

Collibra was a solution we evaluated but Informatica was the final choice.

I rate this solution seven out of 10.

Our organization operates in the financial industry and we utilize the solution to gather and incorporate high-quality data, making it available in the data marketplace.

We are satisfied with the entire solution in its current state and eagerly anticipate its transition to cloud technology.

The tools required to migrate existing mappings and server rules through cloud data quality are not available. Additionally, there is no alert mechanism in place for the existing IDQ that can be integrated with email alerts.

I have been using the solution for over ten years.

I give the stability a ten out of ten.

I give the scalability an eight out of ten.

The technical support responds quickly.

Positive

The initial setup is straightforward. I give the setup a nine out of ten. The deployment took around one and a half hours and two administrators.

The implementation is completed in-house.

I give the solution a ten out of ten.

We have a two-person admin team that takes care of the maintenance.

I would recommend Informatica Data Quality as it has been consistently identified by Gartner as one of the leading solutions in the market.

We use Informatica MDM for master data maintenance across our organization. We have multiple departments, like material real estate, trading, and supply. We use it for consolidation, harmonization, and central master data maintenance. We are also integrating it with the nonrecipient systems.

I like that Informatica MDM has robust matching technology. Informatica MDM is also porting the external Java applications for validations. I can consider that a must-have. It is also exposed to Rest API calls, and we can engage in real-time integrations with any third-party systems.

The configurations could be better. It is a bit confusing because we must develop two tools when building a data model in Informatica MDM. Even though Informatica MDM is a single tool, we have our hub console plus the provisioning tool within that. Whatever data model we are building in the hub console, we have to develop it in the provisioning tool again. It is double the work to create a data model. 

We are also using external calls or the Java custom plans functions. This can be both positive and negative. Since MDM as a client does not support any complex validation, we have to depend on the external call or a Java call. Every time we deployed, the entire solution was impacted if something went wrong. 

I have been using Informatica MDM for four years.

Informatica MDM can be more stable. There are some issues and some crashes, and sometimes, with the data load, we usually feel like we are doing an initial data load for any project. Sometimes, it could also be down to the production environment.

On a scale from one to ten, I would give stability a six.

Informatica MDM is a scalable solution. We probably have 1000 direct and indirect users with multiple use cases. But people solely working with Informatica MDM might be around 200 or 300. Most users are from business IT data support.

On a scale from one to ten, I would give scalability an eight.

Technical support is very responsive.

Positive

I was using SAP MDM, which is currently end of its life, so we migrated from SAP MDM to Informatica MDM.

The initial setup is straightforward. We have to make a jar file which we have to download from the link and download it as a client in our local mission. However, there are some challenges if we deploy Informatica MDM with IDQ on-premises. The deployment time depends on the use case. One or two people can maintain this solution.

We have seen a return on investment. From a business perspective, there have been many improvements since we migrated from SAP MDM.

I would recommend Informatica MDM to potential users. Even though Informatica MDM does not come with data quality, Informatica as a whole has some of the right tools. We have embedded the MDM with the IDQ informatic data quality in ways we can interact. It is the best fit for non-SAP systems.

On a scale from one to ten, I would give Informatica MDM an eight.

The primary use case of this solution is to extract technical metadata, tag the data dictionary, and profiling. We also use it for lineage and relationship aspects.

I recommend Informatica to my clients based in the finance and banking sectors. It has been very helpful.

The most valuable feature is its ability to extract metadata from various sources- be it an old SaaS application or the latest cloud application. They have a custom resource that allows us to customize no matter which source system we have, and we can customize it to extract the technical metadata.

They are moving from on-premises to the cloud. I expect all the on-premises features in the cloud version as well.

I have been using the product since 2019.

It is a perfectly stable solution and a leader in data governance tools in the current market.

The scalability is tough. For example, if you want to increase the scalability in the middle of the project, it would be a challenging process, but it is doable. As consultants, we analyze the requirements from the client end and, based on that, suggest the infrastructure for scalability.

Customer service is a piece of cake if you are a premium member. You need to raise a ticket, and they will immediately respond. For example, they will let you know if it is a limitation; if it is a bug, they will provide you with emergency bug fixes.

Positive

The initial setup is easy. If we compare version 10.4 and version 10.5, they had a major architectural change in terms of infrastructure. The setup for version 10.5 became easier.

The deployment was straightforward, and it took 10-15 minutes to deploy the solution, including migrating technical metadata (importing and exporting).

I would recommend that rather than implementing it on a complete whole enterprise project, start with some small system or a small project first. And from there on, you can move on one step at a time.

I would rate the product an eight out of ten.

We are working with our clients to help them build a data governance product for their enterprise data warehouse. By using Informatic EDC, Informatica Axon, and Informatica Data Quality, they can ensure the quality of their data governance.
Here, we are sharing the data with the consumers. We are using automated tools via Axon to ensure that the quality of data is good and that it is trustworthy. The average threshold for good-quality data is above 85 percent, so we have set a conformance threshold. Data quality is important when scanning data in Axon. We can determine the quality of the data and, if necessary, reach out to the data storage to correct it. Cloud data quality is important in this process because it can correct or reference data.

The most valuable feature is the rule specification. This is where we can define the rules and have our clients verify our transformation. The rule specification is a major transformation used in cloud data quality and especially in rule specification, we can create the business logic. If our business case or our use case deals with any kind of address verification, then we can go with address verification transformation as well.

With the on-premises version, we had many abilities to connect with any kind of server. But when it comes to cloud data quality, there are certain limitations to connecting. For example, we may be using an AS400. There are scenarios where some clients are still using old technology, such as the mainframe. However, for data quality, they mainly deal with the latest tools, such as Snowflake, the cloud database, Azure, Google, and AWS. Informatica has not considered the old version of the software for SaaS applications. The integration with older technology and cloud quality needs improvement.

I have been using the solution for one year.

The solution is stable.

The solution is scalable. We just need to add more licenses.

The technical support is good.

Informatica Cloud Data Quality is a cloud service. All we need is to have a secured agent installed in our local machine or in the VM. Once that is done we get a license and when we have a run time, everything is easy. Since this is a cloud service, we don't need to worry about maintenance. But there are some hurdles in data quality, such as if any one of the services goes down due to reports of our database being full, and there are multiple conditions. So there are pros and cons when compared to on-premises and cloud, And for maintenance, the cloud data quality is the best fit when compared to on-premises. The initial setup is simple.

We pay for a yearly subscription.

I give the solution a nine out of ten. I've been working with Informatica solutions for the last decade. I have worked on other ETL tools as well. But always, Informatica stays close to my heart.

I've been closely working with Informatica's salespeople across the Asia Pacific. Right now, Informatica is pushing all the cloud products to the customers, not the on-premises. Informatica has everything in the cloud except data privacy management. They have canceled or they have stopped the data privacy management of on-premises itself. Right now, Informatica has end-to-end solutions in the cloud. They have all the services starting from data integration, and they have application integration. If it is a web-based application integration, We have CAI cloud application integration. Informatica has a data catalog, data quality, and master data management. They have everything in the cloud. Right now, all the clients are pushing only cloud products to their customers.

Depending on an organization's business requirements and budget, I can recommend Informatica Cloud Data Quality.

Informatica Axon is based on the needs of business people. A business analyst or salesperson would be able to make the most of its features. It is important to have three tools for a successful data governance project. These are Informatica Axon, a data catalog, and data quality. They need to be integrated, whether it is an on-premise or cloud project. The purpose of Informatica Axon is to help us manage our technical metadata and business metadata. Technical metadata is information about our source systems, such as what type of system they are, for example, Oracle, SQL, Snowflake, Cloud; and what data is being extracted from them such as table columns or source systems. Business metadata is information about our data, such as its meaning or purpose. When it comes to business metadata, we can mention that starting from the roles, responsibilities, policies, processes, and whatever the complete organization follows. We can bring all these business metadata, and we can map or tag each technical metadata and business metadata using glossaries. Informatica Axon could be a one-stop shop where we can understand the data. If we want to understand the data, we need to know where it comes from, whether this data can be trusted, whether the data quality is good, and whether this data has access to everyone or whether we are restricting the user privileges. These are the things we'll be considering when using Informatica Axon.

The best thing about Informatica Axon is that it integrates with the Electronic Data Capture and the Axon system. We have policies and processes in place to ensure that everything runs smoothly. However, it's important to work closely with the business person to ensure that all their needs are met. We need to coordinate with the business team as well because the inputs have to be communicated from both the end IT and the business team as well.

The AC integration between EDC and Informatica Axon has room for improvement for the on-premises version, but that has been taken care of with the cloud.

The stability and the integration of the solution have room for improvement.

I have been using the solution for three years.

The solution is not stable.

We can only achieve scalability on the cloud. However, if we want scalability on-premises, this can be a tricky process that takes time because we need to increase the number of code, and CPU.

The tech support team is very good. They have a brilliant team knowledgeable on whatever solution we need help with. The technical support team always tries to find a solution or workaround themselves before asking for help from others. If the solution is on the cloud, the support is quicker, but on-premises, it may get delayed because the technical support team needs to apply the emergency bug fix.

The initial setup on-premises is straightforward. Setup for EDC is a little difficult when compared to versions 10.4 and 10.5. The major architecture change in the enterprise data catalog made it easy to set up.

We only have to run the installer and follow the instructions. There is no deployment process. Whether we will have the solution in dev, UAT, and SAP. There will be only two types, non-prod, and prod. There is no manual setup. We need to do whatever we are doing in non-prod and prod as well. There is no migration with the EDC tool or data quality.

I give the solution an eight out of ten.

There are three types of users, super admin, admin, and web users. The number of total users depends upon the license. Informatica Axon provides a license based on the number of users we have.

The best data governance tool on the market is Informatica Axon. Axon EDC, Axon Data Catalog, and the data quality are the very best combination for cloud for data governance.

We use the solution for Salesforce data integration, multi-cloud approaches and processing bottlenecks. We deploy the solution in a hybrid format.

The serverless capability and the packaging application of the solution are valuable, as all tools come with the solution and do not require additional license purchases.

Although the solution seems complete currently, it could be improved by including a buffer that saves data when there is a connectivity issue.

We have been using the solution for a year and a half and are currently using the latest version.

The solution is very stable.

The solution is scalable.

The initial setup is straightforward. It takes a couple of days, but for migration, if you have to move over the code from one tool to another, it takes a lot of time.

I rate the solution an eight out of ten. The solution is good but can be improved by a buffer that saves data when there is a connectivity issue. I recommend the solution because it has existed for a long time, and a lot of people already understand the tool. Additionally, the learning curve is effortless compared to the other tools.

The product is used for data governance. It's a tool for data governance, a technical metadata dictionary, and a data lineage repository.

So far, we have been pleased with its capabilities. 

It has a wide coverage of technologies. 

The solution scales well.

It is stable and reliable. 

The technical support has been helpful.

The initial setup is very, very difficult. 

The solution is quite expensive. 

I would like them to extend the coverage to other technologies like web services and programming languages.

I've been using the solution for six months. 

It is stable, and it is reliable. The performance is good. We haven't dealt with bugs or glitches. It doesn't crash or freeze. 

We can scale the product.

We have about 50 users on the solution right now. It's not used too extensively just yet. It will be in the future, however. We do also have plans to increase usage. 

We've used technical support previously and found them to be quite good. We are satisfied with the level of support we can get. 

Positive

We did not previously use a different solution. 

The initial setup is not straightforward. We found it to be quite difficult. It took us about two weeks to deploy it.

We have ten people that can handle deployment and maintenance tasks, including a team leader and project manager. 

The implementation can be done in-house with a lot of effort.

I'm not sure of the exact cost, however, the range is in the hundreds of thousands of dollars. It's very expensive. 

I'm not an experienced user of it. I used it in workshops, and I use other Informatica products, so I have some relevant knowledge.

I deal with the latest version of the solution. 

I'd rate the product nine out of ten and can recommend it to others to use. 

We are using Informatica Cloud Data Quality for data quality operations.

The most beneficial feature of Informatica Cloud Data Quality is it's cloud-based. 

Informatica Cloud Data Quality could improve by adding more algorithms for matching and mastering. We currently only have five or six. Additionally, the parallelism in data is better in other solutions, such as IBM.

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

Informatica Cloud Data Quality is stable.

We have approximately 200 people in my company using this solution.

I have used IBM solutions similar to Informatica Cloud Data Quality.

This is a good data quality tool. I can't comment more because I have not used the solution extensively.

I would recommend this solution to others.

I rate Informatica Cloud Data Quality an eight out of ten.