Informatica Intelligent Data Management Cloud (IDMC) Reviews

The main use case we had with Informatica Cloud Data Quality was real-time data quality monitoring. When customer information was entered into a tool in real time, we were able to run data quality rules using Informatica Cloud Data Quality before the data was passed on to the database. This was integrated with Service Bus, and the rules were executed successfully.

Informatica Cloud Data Quality was most valuable for our real-time data quality monitoring needs. We could run data quality rules as part of Service Bus, which ensured the integrity of customer information before it was entered into our database. This system was quite successful in maintaining data quality in real time.

The downside of Informatica Cloud Data Quality is that it requires a developer to write rules and maintain the systems. This creates a significant cost and time burden, especially since we followed a strict software development life cycle process, which made creating each rule time-consuming and expensive. As a result, we had to explore alternatives like Collibra Data Quality.

Their support is good. I would rate it about an eight.

We had to think outside the box for our data quality monitoring needs, which led us to Collibra Data Quality due to the limitations and costs associated with Informatica Cloud Data Quality.

The initial setup for Informatica Cloud Data Quality was straightforward thanks to their good support.

It takes a good two years to see the return or the value in data with Informatica Cloud Data Quality. Compared to Collibra Catalog, where the value is noticeable within six months.

The pricing for Informatica Cloud Data Quality is super expensive. The issue with Informatica Cloud Data Quality comes when you have to purchase the full suite, as having only bits and pieces can cause problems with integration.

I have experience with other tools such as Collibra and Informatica Cloud Data Quality, but not Microsoft Purview, which is why I didn't provide a review for it.

If I rate Collibra an eight, I would rate Informatica Cloud Data Quality about a six. I advise considering the cost and time investment when deciding on a data quality solution.

I use Informatica Data Quality for data profiling before starting any migration projects to understand what the data looks like. I also run quality reports on it, with mappings written for different rules to see what data needs fixing and to identify data issues.

I build our use cases in a very customized way depending on the business needs. There are out-of-the-box features and standard profiling options that provide quick visibility of the data within a few minutes, making it easy to start discussions with the business.

One of the features that I'm looking at is match capabilities at a material level, which is currently not customizable. I often have to write code and tweak the features. Additionally, the user interface requires some technical knowledge; a more business user-friendly UI would be beneficial.

I have been using it for six years now.

The product is almost stable. I experience some restarting issues once in a while, maybe once every two to three months, which require a restart, but otherwise, it's stable.

I have never had any issues with scalability. I have used this product over multiple systems and was able to generate reports for large datasets without any performance issues.

Customer service has been decent. I am currently working to upgrade myself since I have gone out of service support. Otherwise, the response whenever I raised tickets has been satisfactory.

Positive

I previously used another solution called Suniti, which was SAP-centric. The main differences were in pricing and the connectors included in the original licenses. Informatica required me to add certain connectors to my licenses, while Suniti included many connectors in its initial licenses.

I worked with another solution called Suniti before.

I would recommend Informatica Data Quality to others. It's more user-friendly, but it would be great if the UI were more intuitive for business users. Overall, on a scale of one to ten, I would rate the solution a nine.

Other

Informatica Data Quality offers functionalities such as profiling and address standardization. It identifies discrepancies in data through profiling, providing statistical insights similar to other data quality tools. What sets IDQ apart is its integration with PowerCenter, Informatica's flagship data integration tool. IDQ includes a developer tool with a wide range of transformations like Cost, Standardizer, and Cleanser, which are essential for data quality management. It operates as a batch-based tool, distinguishing itself in the market. While IDQ focuses on these aspects, it doesn't directly relate to tools like TDM or MDM, which are separate solutions.

Whenever I open and close Informatica Data Quality, I get consistent results. However, since I moved away from Informatica in the last two to three years, I have also evaluated other products. There is an ETL tool by SAP, specifically Business Objects Data Services, which has some pros and cons. It can integrate more files.

We use parts and standardization for most of our testing. We purchase the US Postal Service address database, which is updated periodically. Many useful tools, such as Google Maps, can detect and mark new businesses or changes in business locations. Informatica captures and updates this information. Some periodic maintenance is involved, but setting it up is not overly complicated.

Informatica Data Quality has its data warehouse, primarily using Oracle and some SQL databases. You need a database to host the data. The cleansed version of the data is stored in the data warehouse. It integrates with PowerCenter and other Informatica tools. The integration details can be complex, but a regional setup is involved in this process.

Profiling smaller datasets, such as 10,000-50,000 records, worked fine. However, unexpected issues could arise with larger datasets, such as thousands of records or more, especially with tables containing many columns. Handling tables with fifty or more columns can be challenging, even in Excel. A mismatch in data types could cause the entire system to crash.

Continual enhancements are being made to address these issues, which can be unique to specific industries like finance and healthcare.

I have worked with Informatica Data Quality up to version 10.4, around 2020, about two or three years ago. During that time, there was a code bug at the driver level when connecting to hardware. When attempting to profile data, the system would crash. We had to collaborate with engineers from Informatica to fix the bug, which was eventually resolved in the 10.5.1 release.

Informatica Data Quality has its client tool. You can build your code on your laptop and then upload it to the database metadata. However, for some parts of the development, you might need to log into the server to complete the tasks.

Informatica Data Quality can build dashboards and integrate with reporting tools like Tableau and Power BI. It also supports integration with tools like Microsoft, Cognos Business Intelligence, and SAP Crystal Reports. This flexibility is a crucial feature of Informatica. As for SaaS, Informatica does offer SaaS options. Additionally, it can interface with statistical software like SAS, allowing users to build code in SAS and then import it into Informatica. This simplifies the process and eliminates the need for manual coding.

If you remove the PowerCenter tools, the next closest competitor would be IBM's InfoSphere DataStage. Additionally, there are free, not free, and less expensive community editions of various tools. For instance, Talend offers an open-source ETL tool, while Pentaho has a miniature business version of ETL. Microsoft itself provides ETL tools like SSIS and reporting tools. Data quality is not necessarily tied to any vendor—data is data, and various tools can manage anything that flows in.

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

I work in the insurance industry.

For this build, the cloud offering provides scalability and agility for my current project, which is in the insurance domain for CNA insurance. We do end-to-end data management as well as follow a microservices architecture. Additionally, we are using AI and machine learning for tasks such as data discovery, data quality, and generative AI applications for development purposes.

Some of the most valuable features with Informatica Intelligent Cloud Services include master data management, API management, data governance, data quality, and cloud application integration. We can utilize both ETL and ELT capabilities and have the ability to integrate data with different data lakes, even integrating with Snowflake.

The cloud-native platform provides scalability and agility for my current project. Informatica Intelligent Cloud Services allows us to manage the entire data lifecycle in the insurance domain, supporting microservices architecture and leveraging AI and machine learning for data discovery, quality, and integration.

I still have to look into potential improvements, but what I have currently provided input on is what I'm using. I still need to work on it and check for any potential improvements.

One thing to consider is that while Informatica Intelligent Cloud Services already integrates with AI platforms, we need to use these tools rigorously and check all these aspects, including machine learning and analytics. I feel that more work needs to be done on this aspect.

I have almost three years of experience.

Product deployment generally takes place as we have an integrated version with various applications, and while we don't deploy daily, we follow a CI/CD pipeline closely for performance.

Different organizations may have different practices; some might have a release plan, but for my project, we manage deployments every one to two days without experiencing significant delays or issues, so I consider it user-friendly.

The solution is stable as of now.

It is scalable. The solution has good scalability and powerful capabilities.

The initial setup for Informatica Intelligent Cloud Services is straightforward for me because I'm not facing any issues with this.

I am part of the initial setup and deployment.

For the deployment team, we have a production development team that isn't just one person; it's a combination of almost eight or nine teams working together. Depending on the team's requirements, they handle deployments at different times, so around ten people are involved.

The reviewer needed more time to provide information about differences with other integration platforms.

I have experience with Informatica solutions, specifically with Informatica Intelligent Cloud Services. This is for my project basis, as IICS is the cloud-native solution they supply us for this purpose. I focus on ETL, ELT, reusable integration artifacts, and cloud data integration, including Snowflake. Everything is there, including scalability and performance, which are also good.

On a scale of 1-10, I rate Informatica Intelligent Cloud Services a 9 out of 10.

We use Informatica Cloud Data Quality in a medium business environment.

The quality of the data improves with Informatica Cloud Data Quality. There is an address cleansing feature called AddressDoctor that cleanses and enhances the quality of the data. Additionally, several algorithms are available for use, such as correcting typo mistakes in the data, whether in alphanumeric, upper case, or lower case forms.

Informatica Cloud Data Quality has significant room for improvement. It is not stable, and there are several issues, especially on the cloud side, unlike the on-premise version which was very stable. There are problems with upgrades and patches that do not make sense and can negatively impact the existing code.

There are substantial stability issues with Informatica Cloud Data Quality on the cloud. The on-premise version was very stable, but on the cloud, the product experiences many issues with patches and upgrades disrupting functionality.

On a scale, scalability with this product would be rated as five or six out of ten.

I deal with technical support daily. The support is not very good; each ticket starts from scratch as there is no continuity between personnel handling the same ticket.

Neutral

From my experience, I have always used Informatica. I transitioned from the on-premise to the cloud version of the product.

Connecting to the cloud allows access to many connectors, which is a positive. However, the stability and performance remain issues. In terms of scalability and cloud connectivity, it is number one.

I am not involved in the pricing details. It appears to use a model based on usage, such as how many rows are processed.

I would rate the solution overall as five to six on the cloud. I would prefer my review to remain anonymous due to my H-1B status. The overall solution is rated as five to six out of 10.

Public Cloud

Other

I have used Informatica Intelligent Data Management Cloud (IDMC) for customer data management and analytical product master data management solutions. The first use case involved finding unique customer references with match and merge functionality. The second use case was creating a master data repository for products for use in the analytical layer.

The match and merge functionality is invaluable for discovering golden master data records. Additionally, the integrated data transport and master data creation capabilities are significant. The platform's ability to pull in and push out data from other platforms without the need for an additional integration tool enhances its appeal. The availability of data quality tools within the platform is another bonus. The presence data governance tools for meta data management adds to the benefits. 

There are various areas for improvement in IDMC. Enhancements on basic data management functionality and the UI front, such as multiple templates and improved grid views, would be beneficial. Bulk data management features could be improved from the UI perspective to get to the level of the on prem versions of Informatica MDM. 

The tool needs to mature but missing small but important features, like restricted dynamic attributes functionality, data inheritance rules in master hierachies, identifiers not being passed in jobs is a drawback.

I have been using IDMC for the last three years across two projects

Stability is crucial because IDMC holds business-critical data, and it needs to be available all the time for business users. 

I have rated the stability a ten out of ten due to a high level of satisfaction.

As a SaaS platform, IDMC is quite scalable and provides complete flexibility. Users can increase data capacity on demand based on licenses, which facilitates easy and fast scaling.

The customer support team is good at response and issue resolution. However, due to the tool's maturity limitations, solutions are not always simple and often require workarounds, indicating a need for further improvement.

Positive

The Informatica on Prem MDM product suite is very mature as a tool and still a very good option. 

I rated the initial setup of IDMC as a six out of ten. Many tools within IDMC are new, and those familiar with on-premises versions find the features limiting. This necessitates assistance from the Informatica support team and architects for ensuring quality of implementation. 

The pricing is high and is based on the number of master data entities managed within the platform including refrence data entities. It can range from a quarter million to a couple of million a year. IDMC is often described as the 'Ferrari of Master Data Solutions,' implying that while expensive, it is still the best as a business-critical platform and, therefore, justified.

As an integrated enterprise solution, IDMC is quite good, however, the platform needs to mature in the capabilities it currently provides. 

Overall, I rate Informatica IDMC a seven out of ten.

Public Cloud

Microsoft Azure

The typical use case of Informatica Intelligent Data Management Cloud (IDMC) is governance activities for data quality and data cataloging. I need to look at the request type from whom I am getting to provide the details.

The most helpful features in Informatica Intelligent Data Management Cloud (IDMC) are data cataloging and the data marketplace.

In terms of data quality management, Informatica Intelligent Data Management Cloud (IDMC) helps with data governance overall.

There are some improvements needed in Informatica Intelligent Data Management Cloud (IDMC), especially from a user experience point of view over the last year. They are improving, and there is still scope for enhancement.

The observability concept in Informatica Intelligent Data Management Cloud (IDMC) needs improvement as the capabilities are not up to the mark compared to the industry.

In terms of cost effectiveness, Informatica Intelligent Data Management Cloud (IDMC) is more than 20% costly compared to the industry.

Regarding AI features in Informatica Intelligent Data Management Cloud (IDMC), there is always improvement and clarity present, but compared to the competitors, they are still lacking. The AI features are helpful, but when compared to its competitors, they need enhancement.

I have been working with Informatica Intelligent Data Management Cloud (IDMC) for five and a half years.

The deployment of Informatica Intelligent Data Management Cloud (IDMC) is user-friendly, but if the software is available, it takes some time.

I have contacted the Informatica technical support team, and they have good technical support, but there is always room for improvements. My experience with Informatica technical support overall rates around three, which is above medium, but not extraordinary.

Neutral

Informatica Intelligent Data Management Cloud (IDMC) takes about a couple of days to configure, depending on the services.

I am aware of its competitors, and I will provide the details once I know them more thoroughly.

I definitely would recommend the Informatica solution to other people.

I am satisfied with Informatica Intelligent Data Management Cloud (IDMC), even if it might be lacking in some areas. The expectations will be somewhere, and the tool can support somewhere, with opportunities to improve, considering the features they are building and their strengths.

I would rate Informatica Intelligent Data Management Cloud (IDMC) at around seven.

I use Informatica Intelligent Cloud Services predominantly for data integration. I utilize it for building data pipelines, which is a critical aspect of my job.

The most valuable feature of Informatica Intelligent Cloud Services for me is the availability of connectors. A connector is a piece of software that allows access to specific solutions such as D365, Snowflake, and various databases. The connectors serve as the main functionality, making data integration processes more efficient by saving time and effort that would otherwise be spent accessing data via other methods like APIs.

The tool is quite good overall, but sometimes the number of modules can be overwhelming. If the development interface could be optimized to have fewer modules, it would be greatly beneficial.

I have been using Informatica Intelligent Cloud Services for a year. Before that, I operated in a different environment, and I am now fully in the cloud.

I would rate the stability of Informatica Intelligent Cloud Services as seven or eight. At the moment, everything seems fine and I don't have any issues with its stability.

I rate the scalability of Informatica Intelligent Cloud Services as eight. There are many options available, and the licensing model is quite good, supporting our needs effectively. It's quite important to maintain its current licensing model.

The customer service and support for Informatica Intelligent Cloud Services is rated as eight. My impression of their support is positive, and everything is functioning well.

Positive

Previously, my solution was not cloud-based and was hosted in our data center. However, I've now transitioned to a cloud-based approach with Informatica Intelligent Cloud Services due to its suitable licensing model.

For me, the initial setup was very easy because Informatica primarily manages that. I am not responsible for setting up anything since it is provided as Software-as-a-Service.

The developers maintain their own pipelines, job schedules, and so on. I don't require dedicated people solely for maintenance.

I haven't observed a return on investment in hard figures yet, but Informatica Intelligent Cloud Services does save me a significant amount of time.

Informatica Intelligent Cloud Services is affordable for my specific use cases, with the pricing being rated three or four on a scale where one is very cheap. The affordability may vary based on how much data is manipulated.

I evaluated a couple of options before selecting Informatica Intelligent Cloud Services. The most suitable licensing model was the deciding factor in my choice.

The overall solution is rated as eight. I plan to continue using Informatica Intelligent Cloud Services for data integration whenever required.

Public Cloud

Other

I use the solution for financial institutions, where we push our data into the warehouses and analytics platforms. We query the Kafka messaging services and see whatever message we get. We used to take the API responses and load them into different target systems, some cloud-based and some on-prem. For some security reasons, we used to push the data to the on-prem and then the cloud versions.

In Informatica, we can export the metadata in XML format, and then we can see what all are available. Metadata querying is right now not there in Informatica Cloud Data Integration. Informatica Cloud Data Integration needs to make metadata querying available in the tool, and Informatica needs to put more reports to get the lineage details and then the source system, if at all there is a need for us to identify them. It is an area where we face big challenges. I started using Informatica Cloud Data Integration recently.

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

The solution's technical support is pretty good, especially since the turnaround time is good. When we raise tickets with the tech support team, we get support within the shortest span. I rate the technical support an eight out of ten.

Positive

I have used IBM Cloud Paks and Informatica Cloud Data Integration. Sometimes, we have to go with our client's perspective, especially if they have pre-existing licenses and get any discounts. My company has suggested IBM Cloud Paks, but with the existing things that our clients work on in Informatica, sometimes they prefer the same vendor. We did PoCs for both IBM Cloud Informatica Cloud Data Integration to help clients figure out the overall run time cost and then the number of credits that they are after, based on which they have opted for Informatica.

I have previously worked with IBM Cloud Paks and Snowflake, and both of them were client-specific tools for which we had to choose. If some tool was already in place, then it has already been paid for as a part of the procurement process, so we should continue with it. If it is a new proposal, then we have to go for it and list out to our customers all the things that we have in our pocket, and where we can take care of all the accesses, billing per hour for users, number of hours, and all such related details. After that, we suggest to our customers to take a call depending upon the amount of budget that needs to be allocated for the technical stuff.

For the last few months, I have been working only on Informatica Cloud Data Integration. Some people are interested in the Azure Databricks for their pipelines. Some of the partners who are providing tools to customers are also interested in Azure Databricks.

Instead of Informatica, I recommend IBM products to others, especially if someone already has other products from IBM's family or has purchased some information catalog. My company suggests that such customers go with IBM Cloud Paks since it allows you to lift and shift some of the existing jobs or processes to the IBM Cloud Catalog. If somebody wants to go for a cross-platform, then there was a time when my company used to suggest they go for Azure Databricks. It all depends on the existing infrastructure and a user's broader plan. Based on it, we used to suggest tools to customers. My company also used to look at what our customers were using and what their target was.

When it comes to the impact of the mapping and transformation features on data integration processes, Informatica has an existing license system where we directly map it to the existing cloud and then run it over the cloud. Any new development activities that we are doing are done directly on the cloud. Informatica has provided this migration tool for lift and shift purposes. With the tool, almost 80 to 90 percent of things are directly convertible from on-prem to cloud services, but through reports, we figured out that 10 percent can't be done, so we have to redo such areas in the cloud.

Speaking about the ease of use and learning curve of Informatica, I would say that my total experience is close to thirteen years with ETL tools. I have worked on multiple ETL tools on different clouds. I don't see much difference between IBM Cloud Paks and Informatica Cloud Data Integration. For me, these are more or less similar tools, with just a change in cosmetics.

Speaking about Informatica Cloud Data Integration's performance and scalability and how it meets our company's project needs, I would say that we have to buy CPU units. Initially, we had some 10,000 CPU units, and with that, we knew how many credits there were. Most of our systems are in production, so only with the peak loads, our threshold is not going beyond 60 to 70 percent of utilization.

Informatica Cloud Data Integration is associated with a bigger integration part where we have around 200 mappings and it works well. I don't see many issues in the tool except in the area of metadata querying. If I want to figure out a particular column of the table that is impacting the number of mappings, previously, we used to go for query, or we used to query in XML format. Currently, we have to call the APIs, but the information that we are after is not that precise.

Informatica Cloud Data Integration can be integrated with Salesforce. We can also have some other API integrations. If you have any specific systems, then considering whatever ERPs or legacy systems we have used with the tool, we don't see many issues.

I would recommend the tool to others. I would recommend the product to mid-sized companies. At the end of the day, everything is about the number of CPUs or the units that are needed to run it. Everything depends on the number of mappings of the growth prospect of the ETL pipelines that one is going to build. If it is mid-level and companies are above the mid-level zone, Informatica and IBM Cloud Paks are preferable to the other tools.

I rate the tool a seven and a half to eight out of ten.

We are cataloging datasets across the organization. Cataloging information across all the tables and other files is the major use case.

The feature that allows me to search across the entire organizational database and then look through what objects are in which tables and which locations is quite handy. Informatica Intelligent Data Management Cloud (IDMC) can connect to pretty much any application, including Oracle Analytics and Power BI, and it works quite seamlessly.

I haven't really used AI yet, but I would like to use it. I may be in a better position to answer this question once I explore that feature. I also want to see integration with other Informatica products, such as IICS, to leverage the metadata from EDC.

I have been using it for about four years, I guess.

My experience with deployment of the solution was pretty straightforward.

We usually get support from our vendor and Informatica, and so far it's been great.

The response time is pretty good because we have someone in-house, who is an expert from Informatica, in our team who can help us with any sort of queries usually. The response time is pretty good. I can't complain.

Positive

I didn't work with anything similar before.

My experience with the initial setup was pretty straightforward.

We hired a vendor. They were helpful.

Unfortunately, I can't really quantify it at this stage, but I can see that there's a lot of time saved.

I think the costs are reasonable for the kinds of features that Informatica Intelligent Data Management Cloud (IDMC) has.

I would rate it 9 out of 10. I really want integration with other Informatica products. For example, we have IICS.

Public Cloud

Other