Informatica Intelligent Data Management Cloud (IDMC) Reviews

I use the solution for preparing the data according to the data quality rules.

The mapping and mapplet features are valuable. The product improves data quality. The processes are running smoothly. The interface is good. Data integration is easy.

I use the solution to integrate on-premise and cloud products. There are issues with connectors to cloud applications. The integration process is not easy. The customer experience must be improved. When we implemented it, we did it with the help of Informatica professionals. I would not recommend them as an implementer. They didn't have any experience. It was very hard. The customer experience was not good. It's hard to understand the new features of the HR list. The tool must have more options for connectors. It is hard to connect to some of the applications. The remediation process is not straightforward.

I have been using the solution for one and a half years.

I rate the tool’s stability an eight out of ten.

I rate the tool’s scalability a six out of ten. It is a bit complex to scale. We have 20 users.

The technical support is not good. The support team must improve the quality of support.

The product is cloud-based.

We got a 50% discount.

We couldn’t deliver the full project. I will not recommend the product to others. Overall, I rate the solution a seven out of ten.

The solution is mostly used to automate MDM, send keyword dimension sites to the engineering team, or address historical records for the training-based employee.

The valuable feature is that we can automate the integration part. Also, it's suitable for data quality. The solution also helps create the data that has been helpful in data governance. We performed some effective or administrative charges in real-time and, most recently, in a real-time solution. So, it allows enrollment to capture and transform the data anytime.

Most of the demand is about how MDM can be automated so the changes occur automatically.

The whole server will change the storage engine, like any tool key, so everything can be automated.

Informatica MDM has limitations with connectivity. This is evident when we connect with our console, especially sometimes the process gets filled. With the tools we are locally running from our end, there should be some specific instance to register that is helpful and can support Informatica in running its modeling.

More automation is much required nowadays, as mainly the work will convert into a complete normal manual process.

There should be some specific integration tools, the managed services, involving the application, and then the code they use. That should be sufficient, meaning there should be leverage to openly adopt any new integration environment like PySpark that we will use. Some resiliency with the particular application, the code, and the type of files only can we address.

I have been using Informatica MDM for more than ten years.

It is a stable solution.

It is a scalable solution for sending any new setup or data. Approximately six hundred users are using the solution.

The technical support team is good. The administration has access to both servers. They can only provide access to run the tool, allow authentication, and how data can be secured. I rate the service and support as ten out of ten.

Positive

Previously, I have used Microsoft SSIS and AWS Glue, but Informatica is capable of doing multiple things for integration purposes, but also for data evaluation.

The initial setup is straightforward. The deployment took ten to fifteen minutes, and almost fifteen administrators were needed for the deployment.

I would say that based on the current scenario, the market trends show that it is not required for the price to be increased. But, functionality-wise, and considering that now as the trend of microservices is going on in the market if Informatica MDM can be replaced in a similar way with particular tools or components to meet the client's demands, we can use only those particular things for the DDoS service covering, for the backup, for the security, and data encryption. So that can be helpful. Part-wise, if somebody needs only the pipelines to be created, someone needs to get a complete data flow task, or someone requires only the MDMs to get in place and not complete information that they need to make. We have licenses, and we are provided with certain particular services in the solution.

I urge those planning to use the solution to understand how they are modeling data encryption and data governance activities. Suppose you are implementing without knowing your data quality and data governance. In that case, the installation of those sources through MDM is not affected. So better to better understand the basics.

Then it will be helpful to use something specific.

I rate the overall solution a seven 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.

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.

The solution is used for real-time validation of the addresses entered by end-users in the MDM solution and validation of the addresses which are received via the inbound interfaces. 

Apart from validation, this service is used to enrich the address data, for example, entered addresses include country, city, and street name. The service returns additional characteristics, for example, postal code (if it can be derived from the other attributes), which are then written back in the requesting system. It's used for Master Data Management in our case.

The overall quality of the addresses associated with other master data entities (Customer, Supplier, physical locations, etc.) has improved significantly. Addresses have now standardized format per country of origin - this means that addresses located in one country have a bit different template than in others. This is a consequence of the fact that Informatica uses various country postal authorities to provide the content used by the Address Verification service. As explained earlier, we use the results of AV service to enrich the address information in some cases. 

Due to improved quality of addresses, the user satisfaction of our MDM solution has increased. Also, the connected systems receive more complete data from MDM. Address Verification service helps in ensuring proper data governance of the master data which is used in many critical processes across the whole enterprise.

The product is easy to set up thanks to pretty good documentation. 

It supports several ways of using it (real-time, batch mode) and has testing capabilities. 

The pricing model is clear. 

The service returns good results which vary depending on the country of the address origin. In case there are multiple matching addresses, this service returns all of them which allows our end of the process or the end-user to select the best matching record. The speed of returning the validated addresses is really great.

The product is really good in its current form; it's hard to imagine what can be improved. It's easy to integrate via the exposed APIs, hence, also in this aspect, I don't see much that can be changed.

The only thing that I can imagine that might be improved is how the available transactions verify addresses used. These transactions have a valid end date and must be used within the agreed timeframe. Sometimes it's difficult to predict how many transactions will be required. In the worst case, some of them might be lost if not used on time.

I've used the solution for more than one year.

There is no single issue with the stability since we started using it (more than 1 year ago).

The scalability is very high.

We previously used Google APIs, however, that was for another client. Hence, there was no real switch as such.

The product is very easy to set up and offers good documentation.

We handled the implementation in-house.

I'd advise users to try to predict the expected usage of the service. The unused transactions may be lost if not used on time.

We looked at both Google and Experian.

It is generally used for the data integration between multiple ERPs. We have ERPs, and then we have third-party exchanges that sell products. The third parties are partnered up with some of the customers, so they create deeds, and we pull in orders and quote requests.

We're trying to get to the latest version. We're two revisions behind right now. It is a local install. 

It is on-prem, and we're trying to get to all-cloud. We do use the cloud for configuration, but we deploy it to the agents locally. We're using the cloud instance of Informatica to deploy to, and we're currently on Azure.

In the latest version, I like the outlay of the business roles creation. I like seeing that visualization as you're building it, as opposed to going through metatables or XML mappings. We liked that piece, and it makes it more intuitive for the business. 

Its GUI interface definitely helps visualize what we're trying to accomplish. There is always a disconnect between IT and the business, and it helps in creating the feeds that follow the business process flows with some of the types involved with the business.

It is so broad in what it can do. Their services have expanded beyond what they originally built it out to be. The best thing I like about it is that each time they add a new service to the platform, it easily integrates with the core, which is really nice.

The biggest pain point for us is the documentation. Typically, you have to go through knowledge forums and knowledge groups to find out about the syntax issues for interfacing with new products. Typically, you've got to deal with someone who has been through the pain before. Their documents are not really up to date with current innovations happening in the industry. As big as they are, you can't really expect it, but that's our pain point.

We've been using this solution for about four years.

We love it. It is very stable. It is probably the best thing we've seen in a while.

It can out scale our ERP. So, scalability is not an issue for us. However, it can overload our system, but that is not related to the scalability of MDM. It is related to the scalability of the system it feeds.

We have five business roles that are using it, and there are two admins who are supporting it. Basically, it is supporting an environment of about 5 billion in revenue. That's a lot for that amount of revenue. It is a lot of people.

We're trying to extend or expand more modules. We have MDM, and we're going into Supplier 360 and Product 360. We found that it is the most robust platform to integrate with our e-commerce platform. Basically, we have four different e-commerce realms, and we're going to consolidate them. So, Informatica helps with the supplier stuff coming in, harmonizing the data, propagating it out to the sites. In the future, the four sites are going to be combined and consolidated into one site, and then we'll be dealing with four different ERPs, and Informatica will be very key in that as well.

Their technical support is excellent. Whenever we had issues, they were pretty quick to respond. There was never an issue in finding them. The longest we had to wait for getting a resolution was a couple of hours.

I walked into this, so I don't know what they had before.

I wasn't involved with its setup.

It is expensive. That's probably the biggest drawback. The business has heartache paying the license, but that's mainly because they don't realize what value it brings. The key thing about the MDM solution is that it is in the backend, and no one sees what it is actually doing. You don't know it is a problem until it is not there.

I would advise making sure that you have a very well-defined design before you decide you need an MDM. In our case, after MDM was in place and we turned it on, we realized that there are other processes that we needed to refactor for the purpose of MDM, which extended the rollout. This was not an MDM issue. It was a process issue in the business. That's why you need to make sure that the design is well defined. It helps to have their partners involved as well. We're dealing with Informatica consulting today to help design a Supplier 360 portal. 

It is hard to find people who are well versed in Informatica. It is hard to pluck one out of the place. You've got to go and poach for them. They're not out there open and looking for jobs.

I would rate Informatica MDM an eight out of 10.

We are simply service providers; I don't think our relationship with Informatica is that strong. We have a financial client that has a very good relationship with Informatica. They were recently using PowerCenter and IDQ, but a couple of years ago, they purchased DIH. Recently they have been doing some POC using Informatica, Enterprise Data Catalog. They have a great relationship with Informatica. 

We don't use Informatica Data Integration Hub extensively. I enjoy using it to create multiple publishing models.

The solution is good but recently, we have stopped using this product because we were not using it extensively. If you are using Data Integration Hub, it should be as a centralized repository, where it can communicate with many systems. For our current client, we are only using it for two source systems, which are not driving big revenue. For this reason, we stopped using Data Integration Hub and started publishing the news directly.

At present, I am not sure how many sources it can communicate with (how many multiple connectors are available). Nowadays, they're coming up with many connectors. It can communicate with all of the Cloud connectors and Cloud databases. If they could leverage social media connectors, I think that would be great a great asset. If they added this feature, it would be much more scalable.

I have been using this solution for almost two years. 

We encountered a few bugs in the coding page, but we faced bigger issues with Informatica PowerCenter. The data was not loading correctly for certain multi-regional datasets; when we analyzed the data, we tracked it to the same code page from the starting point to the end. Other than that, we never faced any difficult situations.  

We never had to use their technical support. We resolved any issues ourselves and thankfully, we never experienced any problems that we could not handle. 

The initial setup was not very straightforward. Not complex, but not very simple either.

Deployment took roughly one week — 40 hours max from start to finish.

We have a team of 30 to 40 people who handle all maintenance-related issues. 

Informatica products are always increasing in price. Nowadays, many of their customers are leaving and seeking other data integration tools. That's the only drawback with Informatica. Performance and flexibility-wise, they're very user-friendly, but comparatively, their prices are a little bit too high.

Presently, everything is moving to the cloud, and moreover, many people are moving to Snowflake Data Warehouse, as it provides more scalability. I feel the usage of DIH is very limited compared to Snowflake because Snowflake holds and stores highly compressed data and allows you to use different cloud-based tools, including AWS services, DCP, and other services. Snowflake also comes with Matillion, which is a very good ETL tool.

The use of DIH is very limited. Anything that we do with DIH, can be done with Snowflake, regardless of the subscription you may have. There are plenty of use cases — you can use it to build tables and consume it from the downstream. For these reasons, I believe that DIH is currently not doing as well as Snowflake in the market.

On a scale from one to ten, I would give this solution a rating of seven. Performance-wise, it could be better. The performance-related Issues could be due to low infrastructure, but for whatever reason, sometimes the performance is slow.

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.