Informatica Intelligent Data Management Cloud (IDMC) Reviews

Our clients need to perform data masking to comply with GDPR rules or the company's internal data security policies. Data masking restricts who can look at the private customer data. Informatica provides a comprehensive solution for on-the-fly or real-time data masking. 

One use case is masking the data for a test environment, so developers and testers can't see production data. This is something you have to do regularly with large amounts of data.

The second use case is in a production environment. Sometimes you need to mask the data on the fly when the data consumers are retrieving reports from the data platform. You are masking the data for certain groups who don't have permission to see that data. 

Informatica should simplify the rules for setting classifications and user access management permissions. It's too complex to define, configure, and make work.

One feature I would like to see is the ability to do data sampling when anonymizing a test environment. It would save you the trouble of having to replicate or perform complex configurations when moving to another environment for testing or development. You should be able to easily configure the data sampling when you are preparing an environment with anonymized data.

We are a system integrator, and we've been one of Informatica's biggest partners for around two years. My team integrates Persistent Data Masking for our clients, but I don't use it personally. I understand the product and its capabilities, and the clients give me feedback on it.

Persistent Data Masking is stable and ready to scale. It has to be. You are working with large amounts of data.

I rate Informatica support eight out of 10. Informatica provides standard support during deployment. A vendor that doesn't offer support isn't a good company. Informatica is willing to make a straightforward deployment because they care about feedback from the client. 

They don't mind investing some money at the beginning to make it run. They care about retaining clients for a long time. Client satisfaction is essential.

Positive

I rate Persistent Data Masking eight out of 10 for ease of setup. It's straightforward. You can deploy a proof of concept in three weeks. It takes two or three people to deploy, but one guy is fine for maintenance. Then again, it depends on the scope and how many anonymizations you have to do, but it doesn't require a big team.

It's usually a yearly subscription, but customers can go with a different pricing model. Typically, it's a yearly subscription for the cloud solution. If you're buying an on-premise solution, it's a one-time payment and annual license for support.

I rate Informatica Persistent Data Masking seven out of 10. 

We use Informatica Cloud Data Integration to load data from files to TelSource or Oracle tables. We also apply business rules to transform the data before loading it into the respective targets.

Most of the features are good. The advanced features like task flow and conditional integration are particularly useful. There are multiple transformations we can use in Dashflow, which are beneficial. We don't use features like centralization and data marketing because they aren't relevant to our use case. Our primary focus is on task flow, which allows us to design our jobs and execute them conditionally.

Some features require an additional license, such as Elastic Mappings. Most of the features provided are through Elastic Mappings, not the data integration service which causes restrictions. For example, the recently enabled source partitioning isn't applicable to Salesforce, which we use as our target or source. We primarily seek features that enhance performance for Salesforce and ICS Integration, aiming to reduce job execution time.

We don't have the license for Elastic Mapping, so we can't use that feature. Most of the new features added by Informatica are through Elastic Mapping. It would be helpful to have features like multithreading or partitioning for Salesforce to enhance performance.

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

The product is stable.

I rate the solution’s stability a seven out of ten.

20-30 users are using this solution.

I rate the solution’s scalability a five out of ten.

Support is good.

Positive

The initial setup is very easy. When I first started using it, I installed a 30-day trial version. I personally explored it during that period, and it was good.

It takes 30-40 minutes depending on the jobs.

I rate the initial setup a ten out of ten, where one is difficult, and ten is easy.

The team is very user-friendly, meeting our expectations much like PowerPoint does.

It supports integration with most cloud sources, including AWS, and has various cloud connectors. So, It's a good choice for anyone.

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

A wide range of solutions exist because data is primary, and my company looks over many overall data management solutions, from which Informatica Data Quality becomes one of our biggest priorities.

I cannot just go into details of the product's features randomly because if you look at a very wide range of overall requirements, be it Informatica or Talend or more data lake solutions like Snowflake. My company goes through an entire range of areas, making it difficult for me to just speak about the features.

Accuracy is one of the key areas a client looks at before using a solution. Considering internal data from legacy systems, it is quite difficult to know if Informatica Data Quality meets that high level of accuracy criteria. The aforementioned area can be considered for improvement in the solution.

I have been a consultant for Informatica Data Quality for two years in my company. I don't directly use the solution.

From a stability point of view, I haven't heard of any complaints about the solution from any of my company's clients who use it.

I don't go into the technical side of Informatica Data Quality much since I mostly work on the procurement side and market knowledge area related to the product. Scalability remains one of the requirements of the clients who buy the product, especially for future growth. My company caters to a mixture of clients, consisting of small, medium, and enterprise-sized businesses.

I do not go into the complete deployment areas of Informatica Data Quality.

The solution is deployed on a hybrid cloud.

Informatica Data Quality is a product that is worth the money.

I rate the product's pricing a seven on a scale of one to ten, where one is the lowest price and ten is the highest price.

I do look at a number of data quality tools, but Informatica, Talend, and Ataccama are a few of the top solutions I have come across.

My company deals with Informatica Data Quality since Informatica is a big vendor in the overall data management area.

I won't be able to speak on how I can recommend the solution to others since my suggestions will have to be based on the product's features and technical details. I wouldn't be able to point out anything about the product in detail, especially since I am not much of an end user.

Based on the feedback that I have received about the product from my company's customers, I rate the overall product a seven or eight out of ten.

The primary use case is for data governance, data quality, data lineages, and data cataloging.

It is used by an internal team for data discovery. However, we are not able to provide business area-level access to other users because of data security.

It's a good product, and the features for data quality, data cataloging, and UI are excellent. It has a lot of advantages.

The major points of improvement are stability, integration, and permission to sub-folders or categories of data. If you want to provide access to a particular type of data discovery to a team, it exposes a lot of data points which in turn makes Axon not that useful for them.

Permissions, scalability, and connection with other informatic tools are the main areas that need development. Integration with other tools, such as IDQ, is challenging. The management of data discovery is highly challenging because many data points have identical definitions.

Mostly, this will come under the data security permission level or admin access.

I have been using Axon for a year, but I have been using other solutions from Informatica for five years now. 

I currently use the latest version of Axon.

I would rate the stability a three or four out of ten. It's not loading at all and it keeps on getting down.

I would rate the scalability a six out of ten. There is room for improvement. 

We developed something on IDQ on the data quality side. If there is a huge data or a big workload, it takes a lot of time to run and we don't get the result in Axon. 

There are around 10 to 15 end users using Axon in our organization. 

There is a different team for platform maintenance, management, and deployment. There are around ten people on the team. It's a mix of engineers and developers.

The platform team had some difficulties with admin-level things and keeping Axon up all the time because it's on-premises. 

The solution is expensive.

Not on the governance, but I have used Databricks, Azure Synapse, Oracle, and other services by Azure.

Databricks is my personal favorite because of the scalability and the runtime it takes to load a large amount of data from a data engineering and data science perspective. 

I'll probably look for another solution because it has stability issues. When it's needed, it's usually unavailable.

However, it is a good product the way it's designed. It's a very good product, and it has a lot of features that are required for data governance. It moved all the Excel work to our web page, which can be accessible to everyone. It's a good product, but it needs some improvement.

Overall, I would rate the solution an eight 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.

The most valuable features of Informatica MDM are it is cloud-enabled and has all the elements that are supposed to have in terms of MDM as a solution. All the features that are there. It is very well-integrated with any of the SAP and non-SAP applications. It is quite user-friendly. The user experience that you receive in Informatica MDM is quite good.

From multiple masters that are there in Informatica MDM, we can improve the financials.

I have been using Informatica MDM for approximately four years.

The stability of Informatica MDM is good.

Informatica MDM has very good scalability. When we say scalability it refers to the ability to add custom fields as per the requirement and then upgrade the overall data model the way you want for the client. 

The scalability is one of the most important features because the clients do not want to use a common data model. They want to have scalability so that they can upgrade the data model the way they want.

We have approximately 25 people using this solution in my organization. The users of the solution include data stewards, business data owners, data sponsors, technical architects, and testers. All kinds of people are using the solution.

There are certain challenges with the support from Informatica MDM, however, I did not directly contact them. It was somebody in my team who did.

I rate the support from Informatica MDM a three out of five.

I did not use another solution previously.

The initial setup of Informatica MDM is complex but is okay if you have experience. The full deployment took approximately five to six months.

Where one is the easiest and five is the most complex, I rate the complexity of the initial setup of Informatica MDM a two out of five.

The deployment of Informatica MDM was done by a whole team, approximately eight to ten people involved, and they had multiple roles. Each person looked after a different section, such as data, validation, and testing.

My advice to others is they need to first ensure that the functions of the solution are stable and the people who are supposed to implement it should have a good functional understanding. It is important that the team that is working on, in terms of standardization and data quality check, that it is a robust team, a strong team to take care of the solution. If we upload data in the system and then the data is not correct, then it becomes a very difficult job to clean afterward.

I rate Informatica MDM an eight out of ten.

Our primary use case of this product is for data management relating to customers and contact information. It's a global resource, we ensure the quality of our customer information and primary attributes. I'm a principal data architect and we are customers of Informatica. 

The solution has improved our organization by providing data quality.

The evaluation service is a valuable feature of this product. 

Because we are moving everything to cloud and our platform is in Azure, it has an infrastructure as a service. I'd like to see a platform as a service, to avoid having to take care of the payments as an upgrade for the platform. I'd like to have email as a service, it would allow us more flexibility. But we already know that Informatica have a cloud integration service but it's not mature enough to do what's required. The service model can also be improved. 

I've been using this solution for seven years. 

The solution is not as stable as we'd like. We need to do a lot of work on the operational side because it crashes frequently, at least once a week.

Scalability is not a problem. You can't count the number of users because it's a platform that has an operational model in which we move the data. We have the data and we clean the data, but users don't have direct contact.

The technical support is very good. 

Initial setup is not complex, it takes about a week to install. We have very good consultants that carried out the deployment for us so although licensing is tricky, the development and the installation is okay.

I believe licensing is around $700,000 annually and we pay around $300,000 for support. The licensing is tricky because sometimes we need to pay for additional connectors and those are hidden costs for us.

We evaluated SAP Master Data Governance. We noticed that more people use Informatica and because it's the most widely used platform we went with it because we knew we'd be able to get access to consultants.

I would rate this solution a seven out of 10. 

We use the tool to collect, integrate, and process the data from different sources. Later, we direct the processed data to the required solution for analysis purposes.

It is a cloud service integration platform providing flexible and scalable data management architecture. It enables seamless integration with large data ecosystems, including Hadoop and NoSQL databases. It supports real-time data streaming platforms as well.

They could provide more robust performance for data integration processes. It would help in improving the data quality more efficiently.

We have been using Informatica Data Integration Hub for the past six months.

I rate the platform’s stability a seven out of ten. The complexity depends on the types of data. It has a robust software architecture.

The product offers two types of scaling mechanisms. We can add more nodes, integrate the service grid, and distribute workloads across multiple processing units. Also, we can add more resources, including CPU memory. It enhances the capability to handle large data volumes.

We can even utilize the load-balancing feature while handling high volumes of data. I rate the scalability an eight out of ten for efficient adaptability, pricing, and performance.

The technical support services are good.

The complexity of the initial setup depends on several factors, including types and volumes of data. It also depends on the data integration and configuration.

Working with a healthcare client with diverse locations, we faced the challenge of analyzing data in isolation, making it difficult to generalize findings across different areas. With the help of Informatica Data Integration Hub, we can collect data from various locations and enhance business insights.

We are familiar with centralized publishing and subscription models. It ensures the enforcement of data governance policies across all data sources and consumers, promoting data consistency and quality.

The automated artificial data synchronization facilitated by the data integration hub has proven invaluable in supporting our daily operations. It ensures the continuous updating of data, preventing delays and inaccuracies that may arise from using outdated information in analyses. This capability became particularly crucial during the sudden changes brought about by the COVID-19 pandemic, allowing us to adapt swiftly to the evolving business landscape. However, they could provide us with real-time data to increase the efficiency of manufacturing processes.

I advise others to understand the different data resources available in the organization before making the purchase decision. I rate it an eight out of ten.