Informatica Intelligent Data Management Cloud (IDMC) Reviews

The most valuable features of Informatica MDM are the IDQ and RDM data management. PowerCenter is the most widely used feature of Informatica MDM.

Informatica MDM has a complex user interface, which could be improved.

I have been using Informatica MDM for four years.

I rate Informatica MDM an eight out of ten for stability.

I rate Informatica MDM a ten out of ten for scalability. We plan to increase the usage of the solution in the future.

I rate Informatica MDM a four or five out of ten for ease of initial setup.

Our organization's deployment process for Informatica MDM took two to three months. A third-party team did the solution's deployment. Around 10 to 12 IT specialists and engineers were required for the solution's deployment.

Informatica MDM's pricing is not cheap but comparable to other vendors.

I advise others looking into using Informatica MDM in the future to have their use cases in order and know what they want to use it for.

Overall, I rate Informatica MDM a six out of ten.

I am a consultant and I use the solution to scan databases and lineages for my clients.

We can scan anything. We can scan reports, XML and JSON files also. That's a good thing about the Informatica Enterprise Data Catalog.

IEDC can improve the comparison of lineages, which is one thing I see in other data catalog tools that Informatica does not have, basically data catalog tools.

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

I rate the stability of the solution an eight out of ten.

I rate the scalability an eight out of ten. We currently have ten to 15 users using the solution and our client is a medium-sized business.

I rate the initial setup a seven out of ten, because it is pretty straightforward. The solution took two to three days for the initial setup.

When deploying IEDC, one should have a server ready and a lot of open ports, but otherwise it is straightforward.

I rate the solution an eight out of ten.

We used the solution for data storage, and data cleaning to improve data quality. The solution also served as a data lake for reporting purposes.

The solution has made it easier for us to retrieve and maintain the data as well as saves us time.

The ability to clean out data and improve the data quality is the best feature.

The solution is user-friendly and easy to navigate.

The cost of Informatica MDM is expensive and has room for improvement. Although the solution is good, it is not worth the high cost.

I have been using the solution for five months.

I give the stability a ten out of ten.

I give the scalability a ten out of ten.

We had ten people using the solution in our organization.

We previously used EXAScaler and switched because we were moving to the cloud.

I give the initial setup a nine out of ten. The deployment took us one month. We prepared the environment and the deployment was completed by the Informatica engineer.

The implementation was completed by an Informatica engineer.

The solution is very expensive. I give the cost a three out of ten.

I give the solution an eight out of ten.

The solution is good and I recommend it as long as the pricing fits the organization's budget.

We primarily use the solution for data integration as well as application integration.

Currently, we have a multiple-source system. With Oracle ERP, it's very hard to pull data from Oracle ERP, since it's API based. Therefore we have to make use of Informatica Application Integration to pull data from Oracle ERP.

We are pulling our supplier information, customer data, and data for projects related to information.

It's a beautiful tool. It eliminates the use of a third party or some other tool as it provides beautiful functionality.

In an earlier version, when we are working with an on-premise tool, it was hard since we had to concentrate on the configuration, et cetera. However, now, when we are working with the cloud, most of the time it's very easy to handle.

Data integration happens seamlessly and is pretty fast.

The application integration will give you more flexibility when dealing with APIs.

Every week, we seem to get notifications of new features and updates. They are always trying to improve the product. 

When we're dealing with huge amounts of data, we need to reach out to Informatica. There are some kinds of API records that we need to modify configurations for. 

Application integration, as compared to data, is a bit slow, and it can't handle millions of records.

There could be a lot more application integration. Like data integration, we find there are a lot of places where we can go ahead and improve performance. When it comes to application integration as a developer, we don't have that much flexibility. We have constraints. Our hands are tied, and we can't do anything. We need to speak with either the target system or the core system and say, "Okay, do this thing." 

I've been working with the solution for more than two years. 

It is a stable, reliable product. Sometimes there is a bug or a cache issue. We might get an error when connecting and when that happens, we reach out to support. We find it's a pretty common issue. It might be a glitch. 

It is very scalable. We have some challenges around application integration, and that requires speaking with support. We tell them we need to change a configuration to a specific size. They can assist us when that happens. That's only for application integration, not data integration. With the cloud, we can easily handle millions of records of data.

A variety of people use the solution in our company. There are 50 to 500 users, approximately. 

Technical support seems to take their time in responding. We'd like a faster reaction time. Sometimes it takes one to two days to get a response.

Positive

We did not previously use a different solution. Currently, we're working with data and application integration with Informatica only.

We've mostly dealt with on-premises deployments. As a developer, most of the time, we face a lot of challenges, which are overcome when it comes to Informatica Cloud. Informatica Cloud is much more convenient, as well as fast, and gives good performance as well. With the cloud, we don't have to install software and there aren't any dependencies. It's much more convenient and easy with Informatica Cloud.

The deployment hardly takes more than a few minutes. 

When it comes to the cloud, there is no maintenance necessary. Informatica takes care of any support tasks. They do the updating, et cetera, as well. 

We handled the initial setup in-house. There were no third parties involved in the deployment process. 

We have not looked at ROI.

The solution is subscription-based. Users are charged based on how many resources are used.

The pricing is pretty good. I'd rate it 8.5 to nine out of ten. 

We did not evaluate any other solutions previously. Our client already had this as a pre-existing tool and did not want to switch. 

I'm working with the latest version of the solution. 

Informatica is a stable, easy tool. New users should go and explore it. There is improvement required in Informatica Application Integration; not the cloud.

I'd rate the solution eight out of ten. We're quite happy with the product. 

We are using Informatica Cloud Data Integration in a large organization, and we have customers all across the world. 

Informatica Cloud Data Integration is for migrating data from a source to a target. The major advantage of working with this solution is that it can handle large amounts of data. The drawback is the performance is a bit slow but it can handle a large amount of data compared to other tools.

The most valuable feature of Informatica Cloud Data Integration is Pushback. You are able to push the data to the solution itself, and it can handle the queries. It helps us a lot. With other tools, the burden is kept on the server.

Informatica Cloud Data Integration can improve by being more user-friendly. When you're working with the solution a lot of technical knowledge is required. It's not a solution that anyone can use properly, you need knowledge of what's happening at the back end, such as SQL. When you get stuck, you need to look into your logic. For other tools, such as Dell Boomi, anyone can use them.

In a future release, the UI should be more developed to allow more features.

I have been using Informatica Cloud Data Integration for approximately four months.

Informatica Cloud Data Integration is stable. 

I rate the stability of Informatica Cloud Data Integration a four out of five.

There are some performance issues sometimes.

We have more than 50 developers using the solution in my company.

I rate the scalability of Informatica Cloud Data Integration a three out of five.

The support from Informatica Cloud Data Integration is great. They respond quickly and if there is an issue it can be resolved fast.

I rate the support from Informatica Cloud Data Integration a four out of five.

Positive

Informatica Cloud Data Integration is famously known for its high price. The vendor targets large enterprises, and not medium or small companies. These large companies, and organizations, handle large amounts of data. If you go into any large bank, such as American or Canadian banks, these banks use this solution because it is more reliable, secure, and has more functionality.

There can be extra changes, such as using the cloud.

I rate the price of Informatica Cloud Data Integration a two out of five.

This is a good tool and others should use it. This solution is known for its ability to handle large amounts of data and in the market, there are not that many tools available. However, there are competitors in the market, such as Oracle and IBM.

If an organization's data is very limited and they are not using large amounts of data, then I would suggest going for a smaller targeting solution, such as Dell Boomi. When it comes to large and secure data, I would recommend others to use this solution or SAP BODS or IBM.

Informatica Cloud Data Integration has a nice GDP rating and a good European market.

I rate Informatica Cloud Data Integration a seven out of ten.

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. 

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.

A lot of times, we use it for basic profiling. That's its most common use case. Currently, we are also in the process of establishing a set of ongoing processes around Data Quality that would feed into and augment our current metadata. So, from that standpoint, our usage is primarily around some of the basic dimensions of data quality, such as completeness, conformity, consistency, timeliness, accuracy, etc. We measure each of those or at least create quality rules that measure each of those aspects. We're in the process of doing this for all of the data that's currently feeding into our analytics engine. These are some use cases that we're currently doing on a daily basis.

There are a couple of valuable features. One is that it is very quick on the profiling. So, you get a very fast snapshot of the type of data that you're looking at from the profiling perspective. It can highlight anomalies in the data.

The other valuable feature of the Data Quality tool is the flexibility of using their Analyst tool to create a mapping specification, which allows you to join multiple sources of information. You can then create rules within that data set. You can apply aggregations and all other types of functions, and then you can feed that into the profiling tool. From the profiling tool, you can then create your scorecards. It can be two-step where you're using that mapping engine to integrate multiple sources. If you don't have a need for that, you can do a lot more sophisticated mappings inside their Developer tool, and then maybe do an analyst type of mapping engine. So, you can do straightforward data quality within the Analyst tool, or you can do more sophisticated data quality within the Developer tool, at least as far as the rules are concerned.

Their UI needs improvement. Their scorecards and reporting also need improvement. Their data quality reporting, especially their dashboards and scorecards, is lackluster at best. Its reporting capabilities are limited. If you want to do anything beyond its limited reporting capabilities, then you're going to have to use an external reporting tool such as Power BI or something like that.

It has a few glitches that they haven't fixed. For example, while creating a new scorecard, when you get up to a point, you have to stop and save what you've done. You have to exit and then go back into the tool to finish up your work. From the development aspect, using their scorecard tool has a couple of glitches in it. This might be a tool that they're going to eventually phase out. So, they're just not doing a lot of work on it. I've been living with it for a few years now. I've learned that I got to save my work, and then I got to get back into it to finish up what I was doing.

I have been using this solution for at least five years.

It is pretty stable.

As far as I know, it scales pretty well. The part of the problem that we have is with the way it saves the results. When it saves the result, it creates a physical copy of some of the data results and stores it. So, when we're processing, for example, 500 million rows of data, depending on the type of rules that we have and how we're doing it, it can quickly use up a lot of space. We've had some issues with some of the space and storage. It scales, but you still have to be careful how you configure it so that you don't use up all your resources. We've added a lot of disk space, and we still occasionally have problems.

Currently, we have maybe half a dozen heavy users, but we're probably going to scale that up to 20 to 25.

It is straightforward.

I would rate it a six out of ten.