Informatica Intelligent Data Management Cloud (IDMC) Reviews

Our use cases were related to the financial and banking sectors. We created data and transferred it to the enterprise level. 

The most valuable feature of Informatica Axon is features, interfaces, and data mapping. It represents clusters nicely. 

The solution should improve its integration. 

 I have been using the product for three years. 

Informatica Axon is stable. 

The product is scalable. 

The tool's support is fine. 

Informatica Axon's deployment is straightforward. 

I rate the product an eight out of ten. 

We have a customer with a lot of data. We see a lot of quality issues, so we have implemented a data quality solution on-premises. Since everything is moving to the cloud, we are also moving our data quality solution to the cloud. We are building data quality goals for profiling, matching, and enrichment. There are other use cases, one example is matching data in our on-premises MDM system. To do this, we need to clean the data and profile it to understand its quality. We can then use data quality rules and matching modules to identify and resolve data quality issues. We also use it to validate customer email addresses and phone numbers on the fly in our in-house customer applications. Other use cases include data integration and data governance.

The user-friendliness and performance of Informatica is quite impressive. It’s easier to grasp and understand data quality, and how data governance tools work, as they are built on the same underlying architecture. The QCA addresses performance issues, whether it’s related to data, PowerCenter, or any other aspect. The shared underlying architecture enables me to pinpoint parameters for optimization. Informatica can handle large volumes of data without compromising performance. While other tools may offer similar capabilities, Informatica consistently delivers impressive results.

Informatica Cloud Data Quality provides many of the capabilities found in on-premises solutions. While the cloud edition offers additional features, it has also deprecated certain functionalities, such as connecting to web services. In the on-premises version, features like web service consumer and web service provider are available, but these functionalities are currently unavailable in the cloud edition. Vendors offer options for custom solutions, although they may not offer the same functionality as the on-premises version.

I have been using Informatica Cloud Data Quality for years. We are using the latest version of the solution.

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

I rate the solution’s scalability an eight out of ten.

The team is acquiring knowledge. In our previous on-premises environment, we had a team of experienced engineers who were familiar with the system and could provide instant answers. However, in the new cloud environment, there’s a learning curve in the new cloud environment, and it may take some time for them to understand and respond effectively.

Positive

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

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." 

In my company, we use Informatica Cloud Data Integration because I work in the insurance sector, where we use the tool for data migration from one environment to another. We also use Informatica Cloud Data Integration in scenarios where the clients switch from their legacy system to Informatica Cloud using Azure Synapse, because of which we have to migrate all the data to Azure Synapse.

The most valuable features of the solution are pushdown, optimization, and partitioning, which can be used for frequent data loading, especially when we have a huge data volume in our company.

While my company operates on the cloud, we have seen that Informatica Cloud Data Integration has some performance issues causing it to lag. I feel that Informatica is still in the process of improving its cloud. Sometimes, there are connectivity shoes in the product causing it to have multiple issues, because of which the solution hangs or lags. The product may have issues because they are new to the market and are trying to improve their services.

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

Stability-wise, I rate the solution a six out of ten.

The solution can be easily scaled up since we just need to take the aid of some PIM processor and increase the data volume as per what we want.

Scalability-wise, I rate the solution a seven out of ten.

The solution's technical support is good. I rate the technical support a seven out of ten.

Neutral

I have an experience of more than ten years with Informatica PowerCenter.

Informatica Cloud Data Integration's on-premises version is very good, considering the faster performance and efficiency it provides. Informatica Cloud Data Integration's cloud version is also getting enhanced since Informatica has been regularly doing some patching to increase the product's performance. Considering the current scenario, Informatica PowerCenter is a good product, especially its on-premises version.

The deployment doesn't take much time, and only a few minutes are needed to deploy the solution.

I rate the product's price a seven on a scale of one to ten, where one is the cheapest and ten is the most expensive. The product is a bit expensive.

In the cloud, Informatica has migrated to a different environment in a single platform named IDMC, on which one can have cloud data migration, cloud application integration, data quality, and data governance, making everything combined with a single platform. Earlier in our company, we had to rely on different software or platforms for each functionality, but now we can use a single URL and work on a single platform.

I would like to speak about Informatica Cloud Data Integration's performance, which is too slow but works overall as a tool. To those planning to use Informatica Cloud, I would say that it is the second-best product in the marketplace, and soon it will become the leading product.

On a daily basis, the product has been increasing their overall availability and performance .On a weekly basis, the product gives out some new updates while fixing its old defects. It will be a good product in the coming years. Improvements in the current product will continue for some time.

I rate the overall product a seven out of ten.

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 the solution for data modularization.

The solution has the best feature for parameterization. We can apply it at the mapping and task flow levels. It helps with auto-linking and dynamic linking options for flexible data integration.

The solution's capability to handle large volumes of data compared to its on-premise version needs improvement. Its features for partitioning and optimization could be better as well. There needs to be more options for partitioning, including database partitioning, pass-through partitioning, etc. Additionally, it doesn't support XML data types for SQL server databases. Also, it captures success and targets rows only within a system-defined area. It should be able to capture and track the number of rows processed by each pipeline.

Presently, users need to write code against the existing APIs to access information data. It is a complicated process due to the limited functionality of APIs. Instead, there could be an option to write queries against repository tables to fetch the data like its on-premise version.

We have been using the solution for two years.

The solution's technical support team could be responsive. We have to contact their global support team to raise new feature requests. Currently, we encounter issues with parameterizing email IDs at the task level to configure features for success, warning, and failure. We sent a request to them back in 2020, but they are yet to add those features.

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 have used it to elaborate on a project for Golden Record, for IDQ data quality, and create business cases for the control parties.

The product could be improved in the area of architecture and technology. All the parts are old.

I would like to migrate it to a new technology. It's better to have a new method for every IT system. Integrate with API, Kafka, and JMS, as API has in Jira code or Jira.

I have used Informatica MDM for ten years. I have used Version 8.6 and 9.1 of this solution.

I think that it's a good solution, but it's an old solution. It is stable because we have the experience to deploy this solution.

I think it's based on ODBC drivers, and they are not good for scalability.

We have not contacted customer service.

The initial setup was complex. It must have taken around eight or nine months to deploy all Informatica systems. The deployment processes for on-premise and cloud are different. For on-premise, we must deploy the data models, and then we must deploy the rules. We must also deploy a .Go file extension and an exposition of the vendor code, among other things.

It's different if we have an on-premise solution. The stability is for the on-premise infrastructure. It builds the IT of enterprises of clients because Informatica is at 'Legacy' level.

So, there are plans for licensing. There are subscription-based and usage-based licenses. Also, there are licenses for exceptional analytics, etc. In short, there are different models of licensing for every enterprise.

I think there is a new Jira-driven event, Jira-driven data, for the flows and extensions. So in this power center technology, I think that it's complex to navigate through the solution without new technology. Overall, I rate the solution a seven out of ten.