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 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.

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.

I'm a freelance consultant, so I work for a few different clients on different projects. Sometimes I do system integrations, and sometimes it's more of the deployment of the tool itself. 

Informatica Axon is mainly used for master data management because it's quite a powerful tool. Lots of clients are struggling because Collibra is not an MDM tool. Azure has some possibilities in the data factory for MDM, but in the end, it doesn't have the engine that Informatica has. I see quite a few clients bring Informatica into the architecture for ETL processes. They use it to extract, transfer, and load data, in addition to MDM, since they're a bit restricted with other tools.

I think definitely what my clients find strong about the solution is all of the processes that it can do. You can extract and transfer your data as you wish it to be consumed later. I definitely hear that this adds value to the tool. 

Another thing I hear clients say is that you can use the MDM modeling functionality as a kind of engine to do data cleansing before you consume the data.

Also, for example, Collibra works closely together with Azure, which works closely together with Informatica and Google because the clients have needs that can't be fulfilled all by one platform. Solutions needs to fit into that architecture, and Informatica can fit in there, and that's appreciated in the market.

There is always room for improvement in making the look and feel more user-friendly. There are also some technical issues sometimes with integrations because clients have a lot of different types of data sources.

One thing I miss with Informatica is the sandbox environment. I do freelance consulting, meaning I give trainings, and sometimes clients ask me to give a training in my own environment, my sandbox environment. 

I have an environment that Collibra provides me with for certifications of training, so I can use a kind of sandbox to actually show a few things to clients.  I have the same thing with Microsoft. With Informatica, it's a bit more difficult. They're not that willing to provide the sandbox to an individual consultant, so I'm just on my own. That's a bit of a pity because sometimes if a client has something that is not configured, I can quickly configure it in my own environment and then show it in a demo. I don't have that opportunity with Informatica. I have to work on the client's system, which then sometimes causes security problems.

I don't have complaints about the stability, and I don't see it as a big issue coming up with my clients. The app sometimes had issues for some clients but it was not business critical or actually impacting them.

I think it is scalable, but that is not really the focus of my work. There are a lot of reasons I can give that the scalability might be affected, but they are actually not really related to the tool itself, but just how you build it in.

If I have a problem with the client and I'm a bit stuck, the support is really good. I can fall back on the people from support and they're quite willing to help. 

It can also help the client because I do a project for six or twelve months, and then I'm gone. If the client has a question after that, they can talk to the support and it's really good. 

From what I have experienced, I would give the technical support an eight out of ten. 

Positive

I think the setup is quite easy if you are data-minded. If you don't have any clue about data management or don't have that background, you're not going to be able to do it. You need to have a bit of technical understanding to do it in the correct way. If you're completely new and you don't have that background of experience, then it's a bit harder, and you'll need to follow a step-by-step plan.

I see clients starting to set it up from scratch and it takes three years. If a client says they want to deploy it within their whole organization, then, in general, you need to count about three years because it's not only the tool. You also need to set up your governance and your organization on it. All of your processes need to be aligned with the tool, so it's a three-year program in general.

Both for the business end users and for the technical people, the maintenance is more on the technical side. For example, for the API connections, the batch processes, and the real-time processes, it's not always easy. One of the things that I always say to my clients is that they need to document everything, and that helps. I tell them to build into their project a documentation pillar where they document everything that they do, like their MDM and rules. It's easier if they have good documentation, but it's still a challenge. Without documentation, it's hard.

I think definitely starting it up gradually, meaning don't buy the tool and then start trying to put everything in from the beginning. First, think about: What do I want to bring into the tool? Which sources do I want to go integrate with the tool? Which data, which business areas do I want to cover with that? You need to do a modeling exercise. You need to do some preparation work first and take it slow. Start small, take a specific business unit or data domain, and then show the value for your business. Then the budget will come, and you can do more with the tool. 

I rate this solution as an eight 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." 

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.

We primarily use it as an enterprise-level firewall. 

I have to incorporate my particular data, schema into Axon. I can do it in two to three ways. Either I have to do a bulk upload feature in Axon, and I have to create an Excel sheet and I have to incorporate all the columns, all the attributes, all the asset columns, and their definitions, and everything into the Excel sheet and then I have to upload it. That is a manual process, and an SME has to be required to accomplish that feature.

The feature of auto-onboarding of the assets, enterprise assets via EDC is good. EDC will scan the data within the technical metadata, and then you can associate that technical metadata, and then Axon can consume that technical metadata and associate the business metadata to that technical metadata. Following some Axon systems, we have to create some systems to associate that technical metadata, as there has to be some logical hierarchy that has to be followed. It allows for some flexibility. You can have related features like policies, business glossaries, or maybe some regulatory compliance feature policies, et cetera, as well as governance.

If you have a DQ rule, data quality rule, on any particular subject area or any particular column, then one cannot create directly a rule in Axon. It has to ingest the technical tool we create in IDQ then into the Axon.

Informatica Axon itself is not a very complete tool. It's highly dependent on Enterprise Data Catalog and IDQ. Blending data catalog and IDQ makes it complete. When I say blending, I mean in the sense they have internal plugins, internal listeners. Axon has internal listeners for reading EDC, as well as IDQ components. EDC is Enterprise Data Catalog, which's a metadata catalog from Informatica.

I would like to have broader connectivity. Axon currently is limited. It cannot connect to any other application. It does not have any connectors for other applications. I want more applications to have connectivity to Axon. Axon should create more plugins for connecting to other applications, which are currently dominating the market.

The solution still is a bit manual in its functionality. We want t to be more automation-driven.

The solution needs to be more resilient.

I've been working with the solution for the last three years.

Currently, what happens in a week or two, the server goes for a toss because Axon still uses PostgreSQL as its database. They have all the services and they, basically, fetch all the backend tables. All the tables are in the PostgreSQL database. That is also a kind of constraint for Axon as PostgreSQL nowadays is a solution that no one uses. That's why the server always goes for a toss and we have to restart the server. They have to make it more resilient. The resilience is missing. 

For example, in EDC they have multiple nodes. When one node goes down, you can still use the backup node. You have to just configure it. In Axon, this does not work like that. They have to make it more vigilant instead of having to restart the cycle and again restart all the services, pre-configured services to get it up and running. That thing is a bit scary sometimes as, over in product staging and dev, it works, however, for production, if it goes down and we need our scanning and some processes running, then it's pretty tough.

Technical support, nowadays, is a bit of a let-down. They will reply once you raise a ticket. They normally categorize their ticket as a P1, P2, or P3. A P1 ticket is for production for the first failure and the P2 and P3 are for normal failures. They reply promptly, however, the response is not very good. Earlier, GCS, Global customer support used to make sense and be helpful. However, nowadays, their quality of service is really going down. The person that comes to attend the ticket is often not very equipped, or not technically not very capable.

Therefore, you need to have a regular follow-up. Normally what they do is not solve the problem. They will ask you, source this, the source that, and then send some kind of justification instead of trying to solve the issue. Sometimes the client is not technically equipped to answer their ticket. They want to see some logs which get embedded. They ask businesses for those logs. Then, the business has to log into Unix, find a particular folder, and access that backlog. These become a challenge for our business as there are not that many Unix-friendly people. In any case, it lengthens the process and draws out the resolution.. 

When I started, I was using version 6.3 and now it's 7.2.

The solution is on-prem in the sense that it's a web browser. It's browser-based so that you can use it on your desktop for unblocking your firewall. It's an enterprise firewall, you can deploy it. Since it's browser-based, it does not matter where the server is. The server can be on-prem and it can be deployed on an iPaaS service or other infrastructure at your service.

Informatica has created the Axon brand in such a way that it's kind of an interesting strategy for them. Once you have Axon you cannot buy it as a standalone product. You will always have to buy IDQ and EDC. That's a sales strategy. However, they really need to improve on their customer support. I really would advise Informatica to work on support. They really need to catch up on this, and they really need to add more qualified engineers to their customer support team to meet the client's expectations.

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