Informatica Intelligent Data Management Cloud (IDMC) Reviews

Data Quality involves quality checks and data profiling. It scans through the data, providing metrics like the number of nulls and unique values. Informatica Data Quality profiles the data.

In my experience, I've specifically worked with a feature called ARS Doctor, which is part of IDQ (Informatica Data Quality). So, in my earlier project, the core functionality of ARS Doctor revolved around address information sourced from the USPS postal service. It does validate the data. This is crucial because customer addresses often contain diverse writing errors. Given the presence of multiple applications, addresses can be inputted or tagged across various systems or enter their address data differently, yet it needs to conform to a standardized format. 

Therefore, each address, even if inputted from distinct systems, undergoes validation to match a single, customizable format. We also have customized settings for these validations.

There's certainly room for improvement. One crucial area is generating detailed reports on file statuses. Presently, this is represented visually, often as graphs or charts. Such reporting could offer comprehensive insights into the areas that demand attention and further scrutiny.

I possess extensive hands-on experience and expertise in Informatica.

I do find Informatica Data Quality is stable. It generally maintains a high level of reliability and stability, making it an asset compliance in various scenarios.

In terms of scalability, you see, it is on the cloud environment, which itself gives the scalable, and flexibility in terms of accommodation of the data. So if we want to scan across the data for the quality and checks, like, not on any sample data. We really want to do this profiling on the checks on a lot of data. So it is very much visible in the cloud environment, which is cloud storage, which is provided by AWS or Azure, or GCP.

Based on my experience and involvement in reported discussions throughout my career, I would definitely give their customer service a high rating. We receive excellent support from Informatica's team, especially during activities like upgrades and other related tasks. 

Positive

When it comes to the initial setup, particularly in a cloud environment, it's primarily license-based. There are various features available, each catering to different needs. The platform can establish connections with various systems based on the connectors it offers. These connectors facilitate integration with different environments. 

When it comes to data quality, it is a license-based model. So, if you procure the necessary licenses, you gain access to the relevant options. It's all about tailoring the solution to the specific requirements of the project.

If the goal is to perform quality checks separately, there's the option to employ dedicated products for that purpose. Alternatively, data quality checks can be integrated into the data integration process. Naturally, data integration involves elements of reconciliation, verification, and quality assessment. The chosen approach hinges on factors such as data volume and the complexity of requirements. If these factors increase, the option to select different products designed for specific tasks becomes viable and can be explored further.

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

The solution gives us the visual features on how the quality is because back in few years or back some time ago. So it was, like, always a kind of hidden thing because, as a part of the data governance, we do have a lot of data dumped in the data warehouse. But relaying we have been just relying on the data warehouse. So we didn't know, like, it is really giving us the powerful insight, or it is really giving our quality data because it could be junk or anything. So, in that case, at least this solution definitely gives us the strength with the visualization part, which gives us, "Okay, these are the different types of data it exists and data. These are the different qualities where it can improve the quality." 

The solution is robust. We can connect with quality analysis tools for summarizing the data as well. It has all the essential features.

The solution's cloud-based version has a few limitations compared to its on-premise version.

I have been using the solution for eight years.

The solution is highly stable. We never had any issues with the cloud version. I rate its scalability a ten out of ten.

The solution is highly scalable. I rate its pricing an eight or nine out of ten.

The solution's technical support team is well-skilled.

Positive

The solution's initial setup is straightforward. I rate the process a ten out of ten. It takes a little time to deploy and requires minimal staff.

Our vendor manages the solution's implementation.

Our clients evaluated Profisee and Precisely before. Comparatively, Informatica provides better integration with quality analysis, data governance, and data integration tools.

I advise others to know their company's requirements before implementing the solution. I rate it an eight out of ten.

We use Informatica MDM for various clients for integration, removing duplicates, and centralizing data in one place.

It has improved our organization because it has made our data more reliable. Data is the most important asset these days, and in order to trust your data, you need these tools to make sure that your data is clean and reliable.

The match and merge function is good.

New machine learning could be added to Informatica MDM because the solution is outdated and is not moving with the current trends. The solution is good, but it definitely needs a lot of improvement and needs to speed up as per the market.

Artificial intelligence is something which they should add to the solution.

They need to do MDM on real-time data as well.

The price is a big factor. We try to convince our clients to go for Informatica, but the cost is too high, and they choose another product.

I've been using this solution for 15 years.

It's a reliable and perfectly stable solution.

It is scalable but to a certain limit.

I'm satisfied with the technical support.

Previously, I used IBM MDM, Orchestra Networks MDM, SAP MDM, and Oracle MDM. I have used a lot of MDM tools, and I've found that Informatica is the best solution out of all of them in terms of the architecture and user-friendliness. Also, the graphical user interface is very simple to use.

The initial setup is not very straightforward but not very complex either. It's somewhere in the middle.

Deployment can take six to seven months to a year or two years. It depends on the number of domains and the number of data sets you need to implement.

A team of eight to nine people can usually handle the deployment.

We mostly deploy on-premises and sometimes on the cloud. Informatica is very weak on cloud-based computing though.

We implement the solution for our clients.

Based on my clients' feedback, they have seen a return on investment in the long-term. After five or six years, they can definitely see that the value of their data is growing.

Informatica MDM is very expensive. Apart from licensing fees, they have broken down their products into multiple products, and they charge for each and every product. If the data is huge, they charge for the data. At times, we have to use third party services for data cleaning, and they charge for that as well.

If you are choosing Informatica, then you need to employ the right kind of service provider. If you don't have good implementers, you'll not be able to leverage the product. So, choose your consultant and service provider wisely; then, you will not have any issues when implementing Informatica.

I would rate Informatic MDM at eight on a scale from one to ten.

I have worked with two clients implementing Informatica MDM. One use case was for the regulatory master data in big pharma (using multidomain edition), on premise installation. The other installation was related to several data domains implemented using Informatica multi-domain MDM edition, but hosted by vendor.

Helped identifying and reducing data duplication. Helped in improving data quality.

Its data cleansing capabilities are very valuable. The match and merge and the audit trail functionalities are very useful. Review and approval workflows are widely used by the user community.

Informatica support should be improved, as resolution of some cases takes definitely too long. Scalability of the solution should also be improved.

I would also like to have a bit more modern and friendly UI for the end-users. There should definitely be a simplified way to configure the system and set it up for the end users.

I have been working with Informatica MDM for three years - on premise and hosted version. I started with MDM 10.2, and then with version 10.3 upgrade to 10.4, which is the latest one.

Its stability is pretty good. We don't have any major concerns.

It is scalable, but its scalability should be improved especially with the hosted version.

It is a strategic MDM solution in the company, so it is extensively used.

We have had some trouble with their support from time to time. Resolution time could be improved.

We have been replacing several very old solutions which reached end of extended support life and several old bespoke systems.

It is a pretty complex product, so the initial setup is also complex. You require skilled resources to deploy this product. Its deployment can take several months.

We use an experienced system integrator and seasoned external consultants.

It is a pretty good and advanced tool, but at the same pretty complex to set up. To implement Informatica MDM, you should look for very skilled resources with past experience in deploying Informatica MDM, not competitive solutions. 

Informatica MDM is one of the best in the market in the master data management area. Make sure that you realize the potential of this solution and like with all other MDM projects - plan your roadmap carefully. Start small, enable most important capabilities and then work on enabling additional features.

Don't overengineer. Informatica MDM is very flexible in defining the underlying models, setting up workflows, enabling cleansing, etc. Hence a risk of misusing the product or make it too complex and downgrade its performance of usability. If you don't have really skilled resources who have worked with Informatica MDM, there is a good chance that the project will simply fail, or it will take you much longer than expected to deploy and benefit from this product.

I would rate Informatica MDM a nine out of ten.

Primary use case is generally for product items and demonstration. 

I like that Informatica MDM doesn't require a separate IDQ. In the IBM InfoSphere, we need exclusive data quality to identify the issues in the source system. But if you use Informatica MDM, that's not the case. The MDM itself identifies the issues and we can use the data quality tools and the score card. It's good compared to other tools. Troubleshooting is very easy and I believe performance is better than any other tool. It solves any complex queries you can connect, any complex route, any complex mappings, you can do it all with Informatica MDM.

I'd like the ability to directly connect from MDM to any of the analytical tools. It's a feature that would be very helpful for analytical reporting. When you connect to the cloud, there are multi-cloud technologies that will have some problem and when you connect from on-prem to cloud, there are more data latency issues than with other tools. The product is more expensive than other similar solutions. 

I have six years of experience with Informatica. 

It is a stable product compared to other MDM products. Other solutions like Oracle CLM and CDH are similar tools but they're not great when compared to Informatica MDM. Of course, it is very stable compared to any other MDM products.

The solution is scalable but when you do the design, you have to know what the data load will be and the number of concurrent users. Based on that you have to design the infrastructure and measure capacity. 

I've implemented this solution in three or four different projects.

I rate this solution a nine out of 10. 

We primarily used the solution because we wanted to be aware of metadata management solutions for our Data Lake, in order to manage the assets in the Data Lake and also to manage the ETL or the data ingestion into the Data Lake.

The solution has an excellent data profiler.

The way that the solution scans is very useful. 

The discovery worked well for the AS400, which is a very old database.

It is not the best solution on the market. 

They don't have a good solution for SSIS scanning, and we don't have the good solution for Microsoft OLAP and Microsoft Tabular. 

Another thing that can be improved is their ability to add custom screens or custom views and manage the custom server and customs views. Currently, it is pretty closed. You cannot add columns to the views, which makes the views very narrow. In order to see data, you have to do a lot of clicks just to get to a particular field.

They have to improve their relationship discovery tool. They say that they have AI inside, but this AI did not automatically find relationships or suggested relationships between entities.

The solution needs better support for data discovery or scans.

I've been using the solution for almost two years.

The solution isn't too stable. If it crashes, it takes time to boot it back up. It's not as stable as you would expect it to be for this type of solution, which is concerning.

We have five people using the solution as of right now.

Potentially, it is scalable, but is not automatically scalable. If you needed to scale it out, then you would have to add some more nodes in order to be able to support the scalability. As long as you are in the boundaries of your initial setup, then it won't scale. However, if you are exceeding that, then you have to increase memory and data store and maybe even some machines to your cluster in order to support the scalability.

Technical support could be improved. From an implementation standpoint, their "customer success" team proved to be unhelpful and did not make what turned out to be a complex set up any easier.

We didn't previously use a different solution.

The initial setup was very, very complex. It took us a few months to complete the entire set up. There were a lot of bugs during installation. Also, when we wanted to upgrade from, I believe it was a 10.2.1 to 10.2.2, our production environment was down for a few weeks just because of the update. It was not a straightforward experience.

We had a very complicated environment, so when we worked on this, we also implemented the SDK or the API mechanism that came with the suite. Therefore, there were four people working on the setup for this environment. We also had support from the local integrator and we had a lot of support from some specialists from India.

We had an integrator and some specialists from India assist us in the implementation.

Most of the work we did by ourselves, but we wanted some help from a local integrator. They had a process that they called "customer success". We had a weekly call with them, with the customer success team. The customer success representative brought in the product team for discussions, but it didn't really help us, to be honest.

It requires between one and two people to handle maintenance on the solution currently.

We ran a proof of concept or a full selection process and we compared it with some other tools. We selected this tool because it had better support for AS400, which was our main source.

We decided to stop the project because it was too much effort and we couldn't benefit from the solution. We saw that it required a lot of effort just to make it work, so we decided to stop the implementation. We stopped using the solution about two months ago.

If other companies attempt to implement this solution, I would suggest that they try to stick to the features which are there and don't try to extend it because it is not that extendable.

In our case, we needed to get a better contract with the local integrator and make sure that they got paid only upon successful completion of the project. Instead, we paid upfront. I'd advise other companies not to make that same mistake. 

I'd rate the solution five out of ten.

Our primary use case for the solution has been in some of our smaller pilot projects.

One of the main valuable features is the user interface which is very easy to use if we have any problems to solve. We don't need to install any client machines to do this, we can access from any machine. 

For the past six and a half years I also worked with PowerCenter, so I used to see the big icons and it's very easy for me to do. But with moving to Cloud there have been some challenges but it's getting better. We are able to connect to a lot of structured data, there are a lot of provisions. 

The user interface could be more user friendly with a simplified mapping task. In general, improvements could be made in mapping. When we create mapping from uploaded data, I'd like to see integrational mapping. I possibly need some extra time to grasp it all but a general improvement in icons and the virtual interface would be good for us. We are working as developers and we're working with the solution on a daily basis so any improvement would be good in this area. 

As far as my knowledge base goes, I feel pretty good with the stability of the product. 

I think technical support is awesome. Initially it feels challenging connecting with IACS, but I am able to get assistance and then apply it immediately. I feel like we're always getting good support from Informatica, even when there are technical challenges, it's one of the best things about the solution. 

I would rate this product a six out of 10. 

I use Informatica Data Quality to consolidate master data across our organization, ensuring consistent and high-quality data. Combining MDM and data quality features, we address issues like customer data inaccuracies. Additionally, we document business terms in our data catalog for a unified view across the company.

The profiling feature in Informatica Data Quality is incredibly effective for data governance. It helps identify data types and potential duplicates, streamlining the detection process. It also suggests matches with predefined fields in our catalog.

There is room for improvement in the Data Marketplace aspect. Specifically, we found some basic functionalities lacking, like transparent integration of quality indicators. Customizability and additional features in the Data Marketplace would be welcomed in future updates. 

I have been working with Informatica Data Quality for three years.

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

Scalability with Informatica had some initial challenges, especially when ingesting metadata into the data catalog due to the large volume of source systems and data. While it eventually worked, it took considerable time. Overall, I would rate it a six out of ten for scalability at the moment.

Initially, a few hundred users were using Informatica, but now it is a few thousand. 

The technical support is good. I would rate them at a seven out of ten.

Neutral

Maintenance and troubleshooting are handled solely by the vendor.

Informatica's licensing cost is among the highest in the market. I would rate it as a five out of ten in terms of costliness. With Informatica, we have a single bundled agreement covering the entire solution based on total capacity rather than specific modules. 

Before choosing Informatica, we evaluated various vendors, including IBM and Microsoft. Initially, we considered a best-of-breed approach, but Informatica emerged as the preferred choice for three out of four key areas: MDM, data quality, and data marketplace. While there were some limitations in certain tools like the data marketplace and data catalog, we opted for Informatica's complete suite to avoid additional integration efforts and to capitalize on its strengths in critical areas.

The rule-based strategies feature in Informatica Data Quality has greatly benefited our data quality initiatives. With predefined rules in place, it provides a solid framework for assessing data quality. While data quality ultimately depends on source system updates, these rules give valuable insights and are heavily used alongside automatic profiling for effective data management.

Informatica Data Quality works within our IT setup for analyzing and reporting on data quality. It doesn't directly integrate with other tools, but it gives us clear insights. Data flows from sources to Informatica for analysis, and then to data stewards for updates, but there is no integration back to the original applications yet.

Navigating between modules within Informatica isn't always seamless. For instance, actions in the catalog might not be visible in the data marketplace.

Overall, I would rate Informatica Data Quality as an eight out of ten.