Informatica Intelligent Data Management Cloud (IDMC) Reviews

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 It ensures the continuous updating of data, preventing delays and inaccuracies that may arise from using outdated information in analyses.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.

We use Informatica Cloud Data Integration to migrate to the cloud, upgrade our data warehouse, and implement master data management. It helps us with in-depth analysis, leveraging shared history, and addressing data governance questions.

The most valuable features of Informatica Cloud Data Integration for our clients are the AI capabilities within Informatica Intelligent Cloud Services. It excels in mapping development, searching for contracts in data governance, creating data quality rules, and designing merging processes. The ability to identify duplicates and automate analysis coverage is particularly beneficial. Additionally, the cost-effective option of using Informatica Cloud Data Integration for smaller projects or departments has made it more accessible and attractive for experimentation.

One area where Informatica Cloud Data Integration could improve is in providing more accelerators for certain functionalities. For example, for master data management, having additional accelerators could streamline implementation. Additionally, enhancing compatibility with metadata sharing across different applications, similar to what is achievable with PowerCenter, would further enhance the product's capabilities.

I would like to see more connectors for on-premise databases in the next version of Informatica Cloud Data Integration. Currently, CDI free is a great option for cloud integration, but expanding the connectors to include databases like Oracle or MySQL for on-premise environments would make the tool more versatile and accessible for smaller businesses or those not fully in the cloud.

I have been working with Informatica Cloud Data Integration since 2016.

Informatica Cloud Data Integration has been generally stable, with occasional editor issues. However, SLAs are consistently respected, and we typically experience minimal downtime, averaging around two to three hours per month.

The scalability of Informatica Cloud Data Integration is high. With advanced pushdown optimization, it performs well in various environments like Snowflake and AWS. It is suitable for companies of all sizes; for small to medium enterprises, starting with fewer IPUs is cost-effective, and scalability allows for growth as needed.

I would rate Informatica's vendor support as a seven out of ten. It is generally good, but there is room for improvement, especially as they shift focus from on-premise to the cloud. We often find answers in the community for software issues, but sometimes we encounter challenges that require official support tickets.

Neutral

The initial setup for Informatica Data Integration is straightforward. Deployment is simple, involving exporting and importing development processes. The ability to pilot the Informatica Data Integration platform from various APIs makes continuous integration and deployment easy to manage through API calls.

I would rate Informatica's pricing as an eight out of ten in terms of affordability. Starting with a small IPU volume is cost-effective, and as we grow, the pricing adjusts favorably based on consumption, which makes it reasonable for our needs.

I would rate Informatica Cloud Data Integration overall as an eight out of ten. It is a comprehensive platform covering data integration, API integration, data quality, data governance, master data, and privacy tools—all within one platform. The accessibility to all functionalities with the purchase of IPUs is a significant advantage compared to the past where certain features required additional payments and permissions.

My company does not specifically focus on selling the solution to a particular sector. My company generally sells the solution to various sectors, including manufacturing and finance.

Informatica Enterprise Data Catalog is a compact tool. Many products operate as a data system solution or as a data catalog tool. The product is helpful when it comes to data transformation. If you would like to solve specific data-related problems, Informatica Enterprise Data Catalog can serve as a useful product.

I cannot specifically point out an area in Informatica Enterprise Data Catalog that needs improvement since it properly functions as a data catalog tool. You cannot use something like Atlas to get catalog ranges, making Informatica Enterprise Data Catalog a comparatively powerful tool. The UX and UI of the solution are areas with certain shortcomings where improvements can be made in the future.

If I want to get some extra features in the product, I can contact Informatica's research and development team, who can add some new features to the product and make the tool available in the market.

I have been using Informatica Enterprise Data Catalog for more than ten years. My company has a partnership with Informatica.

Stability-wise, I rate the solution an eight out of ten.

Though there are some bugs in the solution, Informatica's research and development team, along with Informatica's customer service team, supports my company in solving such bug-related issues.

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

Informatica Enterprise Data Catalog can be a good solution that is really easy to use when it comes to enterprise-sized companies, but it may pose some challenges for small and medium-sized companies.

Most companies to whom my company provides the solution are enterprise-sized businesses.

I rate the technical support a ten out of ten. My company has a partnership with Informatica, and we provide Informatica's products to the end users or customers. Informatica has to provide my company with good support in order to hold on to its customers who deal with my company.

Positive

I rate the product's initial setup a nine and a half to ten on a scale of one to ten, where one is difficult and ten is easy.

Most of the companies to whom my company provides the solution deploy it on an on-premises model. My company also sells the cloud version of the solution while also offering our customers the option to move from on-premises to the cloud version of the solution.

My wife runs a pharmacy, and she uses an ERP solution for sales-related activities, the data of which I can move to the cloud in ten minutes if she chooses Informatica Enterprise Data Catalog.

With Informatica Enterprise Data Catalog, measuring the return on investment can be hard. I rate the return on investment a seven on a scale of one to ten, where one is zero return on investment, and ten is a hundred percent return on investment.

The price of the product is something that may vary from customer to customer. I rate the product's pricing a five on a scale of one to ten, where one is cheap and ten is expensive.

If a customer or business wants to easily maintain their data domains, they can opt for Informatica Enterprise Data Catalog.

I rate the overall product an eight to nine out of ten.

I manage the environment and admin-related tasks.

I have integrated Axon into EDC, PowerCenter, and data quality tools, and I face no difficulty integrating with those tools.

I also handle installation, configuration, and troubleshooting issues, in addition to when users face access issues or need help seeing their DQ technical roles.

With Axon, you can easily call and verify DQ rules. You can also upload your business gallery, and the business team can easily verify your data because it is secure.

Some of Axon's valuable features include creating your business glossaries, importing DQ rules, and creating change management.

They could improve technical support because it is not good enough at the moment.

I am a consultant and have been working with Informatica Axon for three years.

I rate the stability an eight out of ten because I have not yet seen the environment go down.

I rate the scalability of the solution a five out of ten. We have faced some performance issues. We have about five or six Axon business users who are data owners and stewards. They are not very active with the solution.

Personally, for the last month, I have not touched Axon or the servers. There are no plans to expand Informatica Axon's usage at the moment.

I rate the initial setup a seven out of ten. The clients gave us their Linux servers, and I set up the solution on-premises.

I could set up the environment, the installation, and the configuration in one day.

My organization's initial steps required us to get licenses for the installation, and we needed specific kinds of ports opened from our environment. We first needed to install the Axon agent and Axon server on different directories. Once we did that, we needed to update a couple of files to communicate with data quality and other functions.

The solution requires some maintenance. I might have to perform a sync-up or make sure the environment is not down, but that is very rare.

The solution was implemented in-house, with me deploying the solution single-handedly.

I rate the pricing a six or a seven out of ten because the price is neither too high nor too low.

Informatica is a big name in the market and the tools are trustworthy, which is why our client chose Informatica Axon-EDC. I rate the solution an eight out of ten.

Test data management is a common use case. When conducting testing in lower environments, we want to avoid exposing sensitive information. To achieve this, we use Data Masking to modify the data. 

For example, we change personally identifiable information, phone numbers, and emails so that they cannot be viewed. The modified data retains the structure and format but doesn't reveal the actual information.

The tool is mainly valuable for testing teams, as it helps protect sensitive data during testing. It can also be used to mask production data for different users, ensuring that only authorized individuals can access sensitive information. These are the main reasons why we use this tool.

I think there's only one area that could be improved. Currently, when we apply the Data Masking rate, we don't have a way to view the masked data. It would be helpful if there was a feature to allow us to see the actual information.

Once the data is masked, it cannot be reversed. Having the ability to revert it back to the actual value would be beneficial, especially if we need to see the original information. Although our enrollment has decreased, it would still be helpful to have that feature.

I have used Data Masking as part of my work.

Stability is good. It's definitely reliable.

Scalability is good. It's definitely scalable to handle higher volumes across different platforms as well. It performs well in terms of scalability. 

Additionally, when it comes to implementing more source systems, there haven't been any issues.

Our experience with customer service from Informatica has been excellent. They are always available and responsive.

Positive

The initial setup is generally straightforward. However, there can be some challenges during the on-prem installation process, even though we have the steps and prerequisites. Dealing with installation issues is quite common, but overall, it's not excessively complex to set up.

The need for maintenance depends on the team. Sometimes, the solution you configure in the tool determines the level of maintenance required. However, overall, maintenance hasn't been a significant issue.

Overall, I would rate the solution an eight 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.

We don't use profiling as much, however, we do use it, in certain cases, for profiling. We use the Analyst tool to do out-of-box, high-level profiling of data to see high-level quality of completeness, and uniqueness, et cetera. Mainly, we use the Developer tool to connect to the sources and to write data quality rules.

It has improved our organization. 

We started from just pretty much having flat files, and then doing some basic transformations, then writing back to Excel or QFD files. 

We gradually moved to more analytical tasks. You don't just do statistical data quality you also do analytical. You do lots of joins with other sources and do the consistency checks, and to do more complex logic, and build metrics. 

We use Tableau on the back of it to present the data and data quality, and then monitor it. We use it more like a batch process to build pipelines, and then, using Tableau, monitor the results of it and those metrics. Now, we work more with live updates and do that more than the batch.

It's probably one of the leading lights in ETL. They have really good built-in functionalities, or algorithms, that you can use to transform or process data and validate and standardize.

The solution is stable.

It's not too had to set up the cloud version. 

Support is helpful and responsive. 

We are in this transition mode, where we haven't yet got IDMC, the cloud version, so we don't actually have hands-on experience and have not actually seen the features. All we rely on, at the moment, is just the available documentation. What I don't like on the IDQ side is just the fact that in the on-premises version, you have all these applications, with separate configurations. In the cloud solution, it is fixed so that you have everything on one platform.

The performance isn't as good on-premises. For example, when you install clients, it's slow compared to the cloud. Still, we need to see. We haven't experienced it ourselves. 

The upgrades are a downside. On-premises you manage all the changes in the software. You have to do that yourself, and if there's some problem with compatibility, it makes things that much harder. With the cloud, everything is managed by Informatica on the servers.

Managing the licenses with the on-premises version was difficult. However, with the cloud, it will be much simpler. 

I've been using the solution for the last six or seven years. 

Once you set everything up, it is pretty stable. It's reliable. There are no bugs or glitches and it doesn't crash or freeze. It is way more stable than Hadoop and other applications. 

In terms of scaling, we used the clusters, and the processing was on Hadoop side. If we needed any extra space or any service, it was just managed there, so it was outside of Informatica.

Originally, we had 20 people using the solution, and then it was reduced to less than ten.

We do use it as much as we can for its purposes. In the past, we used that for the whole ETL process with data loads, and then we moved to Hadoop storage. At the moment, we are only going to be using Cloud Data Quality and others for cleansing, standardization, and deduplication, and then using some other Azure capabilities.

I've dealt with support in the past. There were issues, and we had to deal directly with Informatica for some hotfixes. They were good. They just got straight to the point and were helpful overall.

Positive

It is way more complex to install on-premises than in the cloud.

With the cloud, the installation will be way easier since you only install these secure agents. They have many different connectors, so it is definitely less hustle to install all these machines, and all these applications. On-premises, it was more user-based. Now, it's service-based, and you just pay for what you use and the licenses as well. 

We had myself, an architect, and a developer as well as help from Informatica while handling the setup.

We have about two or three people that can deploy and maintain the solution. They also cover other applications, not just Informatica.

We had Informatica support, and we had an internal group of people with Informatica knowledge who handled the solution. For some parts, we were involved as well, and we handled them ourselves. 

We're still in the early stages of moving toward the cloud. We have not seen an ROI yet.

When you are using the on-premises version, managing the licenses is quite difficult. However, on the cloud, you just pay for what you use, and it's a lot easier. With the cloud, if you want MDM, you pay for it, and if you want PowerCenter, you pay for it; however, if you don't want it or don't use it, you don't pay. We'll just pay for Data Quality, as it has all of the features we need inside it. 

I'm not involved in the conversations around licensing and agreements. That said, my understanding is that Informatica is pretty expensive. I'd likely rate it two to two and a half out of five in terms of affordability.

We definitely considered others and had StreamSets used for some other purposes. The company that I moved out of was going to be switching off Informatica at some point due to licensing, et cetera, and they just chose to go to StreamSets with Snowflake for storage. 

I haven't researched enough about other products in relation to Informatica.

We are moving to the cloud version. On-premises, we were on version 10.4.2, and that moved to 10.5. Soon, we will be on the cloud.

We're using IDMC, which is not just Data Quality. It has governance, Axon, and other applications in it.

We're just a customer.

I'd advise people to research use cases before beginning. Companies need to understand what they are trying to achieve, figure out their requirements, and then appraise the solution. 

While Informatica is good in terms of Data Quality and is probably the leading option, you need to be clear about budget, et cetera.

I would rate the solution seven 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.