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.

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.

In the past, people used Informatica MDM because it was one of the leading tools at that point in time to work on an on-premises model. It was the leading tool in the market, offering vast customization options and matching and merging options that were better compared to other solutions. The way the data lineage or the customization options it gave, the tool was good. Now, the tool has a changed dynamic, and it is currently available on the cloud. Apart from Informatica MDM, there are other tools, as well as the market, that are completely on the cloud.

The feature of the product that has been most helpful in improving data quality revolves around Informatica DQ or IDQ, which is one of the tools Informatica offers. IDQ helps cater to the scoring of the data, clean up the data, and integrate it.

In terms of the room for improvement required in the product, I would say that the product is still in the maturing phase, specifically on the cloud. The product is not too user-friendly to do the configurations. There are a couple of areas in the product where I feel improvements can be made, but if I consider the algorithms used in the match process, the tool is very robust.

I have been using Informatica MDM for nine to ten years. My company is a partner of Informatica, and we also implement the tool.

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

In terms of scalability, I would say that the product is currently more available in the cloud. Scalability-wise, I rate the solution a five out of ten. The scalability on the cloud is good. On the cloud, by default, the tool becomes quite scalable.

Informatica provides premium products. The product is mainly meant for enterprise-level customers because the tool is available at the premium cost.

I have not used the technical support provided by the product. If you asked me about the support offered for the tool's on-premises model, I would say they were really good. We really liked Informatica's support. With the cloud, I'm not aware of the support.

If one is a difficult setup and ten is easy, I rate the product's initial setup phase as a five.

If you are talking about the product on the cloud, the initial configuration must be done. There is quite a lot of refresh which takes place every time we have to publish something, and then we have to wait for some time. It is not that you make a change, but you can see it immediately in the tool. The wait period is quite long. If you are a first timer, it takes time for that person to figure out the product. Once you get the hang of it, then it becomes easy.

An end-to-end implementation would take nine to ten months, or maybe a little more than that, depending upon the customer's desired features.

The tool does give a good ROI.

The product is not very pocket-friendly for small and medium-sized businesses, and it is understandable because of the kind of features the tool gives.

On a scale of one to ten, if one is a cheap solution and ten is an expensive one, I rate the tool's price as seven.

Informatica MDM is able to handle complex data integration scenarios with the help of IDCM, which offers the power of an ETL tool.

Speaking about the AI part, I feel the product is still in the maturing phase.

My first preference would be for Welkio, and only after that would I prefer Informatica MDM, so I would say that it won't be my first choice.

I rate the tool a seven out of ten.

We use the solution for ETL.

It's a powerful tool to create data warehouse solutions for our clients. We take unstructured data and use Informatica Cloud to structure it in various ways, making it usable on a reporting front end. This enables clients to make informed business decisions based on the data.

It's the accessibility and the range of features that stand out. Before using Informatica Cloud, we were working with Informatica PowerCenter. The transition from PowerCenter to Cloud wasn't entirely effortless, but it was seamless enough for our developers to adapt and continue their work smoothly.

Our main issue is transitioning from on-premise to cloud data storage. As many clients move their data to cloud platforms like Azure, Snowflake, and AWS, we're encountering problems with Informatica. Errors that were straightforward and clear with on-premise databases now appear ambiguous in cloud environments. Our developers spend significant time reducing these generic errors, often simple issues like a column not accepting null values. This lack of clarity is causing unnecessary delays as they have to sift through logs or contact support to diagnose problems that would have been more easily identified in an on-premise setup.

I have been using Informatica Cloud Data Integration as a financial partner for over five years.

We have about seven developers. It is a scalable solution.

When errors arise, contacting support can be frustrating. Sometimes, the technician can't solve the issue and transfers us to someone else. This makes us less confident that the person helping us is truly equipped to resolve the problem.

The initial setup is simple and depends on the task. However, it usually takes a couple of hours if development is complete and we're moving from the development environment to production.

ROI is strong because we have a structured portal that ensures development is done correctly. It is shareable, scalable, and equipped with enough monitoring tools to quickly address any issues. Ultimately, the client doesn't care what tools we use. They just want problems resolved quickly. Informatica provides the necessary tools and features to help us do that effectively.

It has premium pricing. Depending on what we're working on and which features we're using within Informatica, there can be additional costs. It's mostly data integration, but you might need to upgrade your license to include other aspects of Informatica. Certain connectors require a license upgrade to access.

Overall, I rate the solution an eight out of ten.

What I like best about Informatica MDM is its structured, table-based approach. Unlike Reltio, where data is only visible through the UI and cloud-based, the solution allows access to normalized tables. This means I can directly query and see data in each table. For instance, I can easily get all customer details from the customer table. However, for more complex queries, like seeing all customer interactions with the organization, some SQL knowledge is needed to join different tables and retrieve the details.

The tool could be improved in terms of ease of use, particularly for those without technical expertise. Understanding and extracting data from the table-based structure requires some SQL knowledge and technical skills. Additionally, while Informatica MDM has moved towards a cloud-based MDM with a UI similar to Reltio, I haven't used it, so I can't comment on its effectiveness.

I have been working with the product for six months.

I haven't had any issues with the tool's stability.

I'm not entirely sure about scalability, but I've heard that adding custom features can be complicated. We have to go through several steps. First, we need to determine if we're adding a column to an existing Informatica MDM table or creating a new one. Then, we have to contact Informatica with our customization request. They do the customization. After that, we have to check if it's working correctly.

In our organization, we use Informatica MDM in a specific way. It's primarily based on tables; users don't directly log into it. The process works like this: data flows into the MDM tables as an inbound process. Once the master data merge has been completed, the output data flows out as an outbound process.

The tool's support team is good. The product is quite technical, and so is the support team. When we have questions, we reach out to them, and they provide answers. Their response time is also good—we don't have to wait long for replies.

I rate the overall product a seven out of ten. If you don't have the budget for Reltio, then you can go for Informatica MDM.

I use the solution for financial institutions, where we push our data into the warehouses and analytics platforms. We query the Kafka messaging services and see whatever message we get. We used to take the API responses and load them into different target systems, some cloud-based and some on-prem. For some security reasons, we used to push the data to the on-prem and then the cloud versions.

In Informatica, we can export the metadata in XML format, and then we can see what all are available. Metadata querying is right now not there in Informatica Cloud Data Integration. Informatica Cloud Data Integration needs to make metadata querying available in the tool, and Informatica needs to put more reports to get the lineage details and then the source system, if at all there is a need for us to identify them. It is an area where we face big challenges. I started using Informatica Cloud Data Integration recently.

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

The solution's technical support is pretty good, especially since the turnaround time is good. When we raise tickets with the tech support team, we get support within the shortest span. I rate the technical support an eight out of ten.

I have used IBM Cloud Paks and Informatica Cloud Data Integration. Sometimes, we have to go with our client's perspective, especially if they have pre-existing licenses and get any discounts. My company has suggested IBM Cloud Paks, but with the existing things that our clients work on in Informatica, sometimes they prefer the same vendor. We did PoCs for both IBM Cloud Informatica Cloud Data Integration to help clients figure out the overall run time cost and then the number of credits that they are after, based on which they have opted for Informatica.

I have previously worked with IBM Cloud Paks and Snowflake, and both of them were client-specific tools for which we had to choose. If some tool was already in place, then it has already been paid for as a part of the procurement process, so we should continue with it. If it is a new proposal, then we have to go for it and list out to our customers all the things that we have in our pocket, and where we can take care of all the accesses, billing per hour for users, number of hours, and all such related details. After that, we suggest to our customers to take a call depending upon the amount of budget that needs to be allocated for the technical stuff.

For the last few months, I have been working only on Informatica Cloud Data Integration. Some people are interested in the Azure Databricks for their pipelines. Some of the partners who are providing tools to customers are also interested in Azure Databricks.

Instead of Informatica, I recommend IBM products to others, especially if someone already has other products from IBM's family or has purchased some information catalog. My company suggests that such customers go with IBM Cloud Paks since it allows you to lift and shift some of the existing jobs or processes to the IBM Cloud Catalog. If somebody wants to go for a cross-platform, then there was a time when my company used to suggest they go for Azure Databricks. It all depends on the existing infrastructure and a user's broader plan. Based on it, we used to suggest tools to customers. My company also used to look at what our customers were using and what their target was.

When it comes to the impact of the mapping and transformation features on data integration processes, Informatica has an existing license system where we directly map it to the existing cloud and then run it over the cloud. Any new development activities that we are doing are done directly on the cloud. Informatica has provided this migration tool for lift and shift purposes. With the tool, almost 80 to 90 percent of things are directly convertible from on-prem to cloud services, but through reports, we figured out that 10 percent can't be done, so we have to redo such areas in the cloud.

Speaking about the ease of use and learning curve of Informatica, I would say that my total experience is close to thirteen years with ETL tools. I have worked on multiple ETL tools on different clouds. I don't see much difference between IBM Cloud Paks and Informatica Cloud Data Integration. For me, these are more or less similar tools, with just a change in cosmetics.

Speaking about Informatica Cloud Data Integration's performance and scalability and how it meets our company's project needs, I would say that we have to buy CPU units. Initially, we had some 10,000 CPU units, and with that, we knew how many credits there were. Most of our systems are in production, so only with the peak loads, our threshold is not going beyond 60 to 70 percent of utilization.

Informatica Cloud Data Integration is associated with a bigger integration part where we have around 200 mappings and it works well. I don't see many issues in the tool except in the area of metadata querying. If I want to figure out a particular column of the table that is impacting the number of mappings, previously, we used to go for query, or we used to query in XML format. Currently, we have to call the APIs, but the information that we are after is not that precise.

Informatica Cloud Data Integration can be integrated with Salesforce. We can also have some other API integrations. If you have any specific systems, then considering whatever ERPs or legacy systems we have used with the tool, we don't see many issues.

I would recommend the tool to others. I would recommend the product to mid-sized companies. At the end of the day, everything is about the number of CPUs or the units that are needed to run it. Everything depends on the number of mappings of the growth prospect of the ETL pipelines that one is going to build. If it is mid-level and companies are above the mid-level zone, Informatica and IBM Cloud Paks are preferable to the other tools.

I rate the tool a seven and a half to eight out of ten.

It improves the workflow.

In terms of the user experience, it's very Integrated, and the implementation is very fast. You can integrate the platforms for different services to deliver all the banking needs.

It is expensive.

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

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

The scalability is impressive. Implementing something is easy, and there's no need to wait for licenses or other potential roadblocks. It is a highly efficient and smooth process, which makes it even more appealing.

The main reason for the switch was the cost. IBM solutions are quite expensive, and migrating to the cloud platform is complicated. Another significant expense comes from the database, as IBM typically recommends DB2 when implementing DataStage, and using Db2 can be costly. The company considered moving to a more versatile platform that supports different databases and cloud providers. With IBM, there are limitations, and the cloud strategy is more rigid, which influenced the decision to explore other platforms.

Deployment is straightforward. I have experience implementing the platform for various customers here in Brazil, where I live, and I can confirm that it's quite easy to implement. It takes around six months to deploy.

Data has been migrated from IBM DataStage to Informatica Cloud. In this process, we worked with NextPath MSA, which generated new metadata based on the iDMC platform. After this, the company produced the data, and here at the bank, we are validating the conversion from this process. In some cases, adjustments or parameterization were needed with Informatica to refine the processes. The company is responsible for translating the code and generating the required information for each project. We migrate this to the development environment, then to the test environment for validation, and finally to production, where about sixty percent of the projects are implemented for data integration. The entire process, from creation to production, has taken approximately six months.

We are reviewing all components and executions, and overall, the migration process has been a success, with only minor adjustments. It’s interesting to see how the company has successfully converted the original metadata to the new metadata, showcasing its expertise in the process. We have 40-50 professionals involved. We have different levels of specialists across various areas involved in this project. For example, we have experts with extensive knowledge of IBM DataStage, others with experience in IBM CA, and some professionals specializing in databases. Each group brings expertise and experience with these solutions, contributing significantly to the project's success.

They do have additional costs in terms of usage.

The bank acquired the platform and utilized almost all its services except MDM. We use APIs, messaging, data governance, and data integration for the enterprise. The platform's full range of services is involved. The combination of data integration with application integration is precious to us. It allows us to acquire information through APIs, treat this information via data integration, and generate files or intermediary databases for future consumption by messaging systems. This type of usage is efficient and straightforward to implement. The implementation and usage are simple and effective for our needs.

In our daily operations, we receive data from external and internal systems for Kuzena and generate information in real-time for various departments within the bank, such as the risk and human resources departments. The platform’s ability to efficiently deliver this information is precious.

When a platform provides data from external systems and other sources, combined with HEP implementation and fast integration, the platform ensures high data quality and the ability to deliver information efficiently. This simplicity allows all departments in the bank to adopt and explore this type of usage easily.

I know of other companies using Informatica Cloud, like Ferrero in Chicago. They used Informatica Cloud for three years but migrated to SAP CPI this year. While I know why they made the switch, it's hard to justify it fully. For context, Ferrara produces candies and is owned by Ferrero Rocher in Italy. The IT team in Italy used SAP CPI for data integration, closing their operations with Informatica products. It's surprising, especially because Ferrero had given us positive feedback about Informatica Cloud regarding usage, implementation, and cost.

Its open platform allows it to connect with everything you need, making it very versatile and efficient for various integrations.

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

The solution was part of building our data warehouses, where we needed a tool for bulk data migration that didn't require mappings when migrating from a source to a target.

The product's most valuable feature is the replication tasks. It allows the creation of identical tasks that can be applied across multiple tables, ranging from 100 to even 1,000 tables.

The product interface could be improved to be more intuitive. It requires navigating through several steps to access mappings and pre-created metrics. Enhancing it to provide a more streamlined structure or dashboard would allow quicker access to maps and other essential features.

We used Informatica Cloud Data Integration for six months.

The product was stable. I rate the stability a ten.

We had 30 Informatica Cloud Data Integration users in our organization. I rate the scalability an eight.

The solution didn't require much setup, and since it was browser-based, it was fairly easy to use. I rate the process a ten out of ten.

The product was pretty easy to use. The connections to other platforms worked fine.

I recommend it to others and rate it a seven.

We've 300-400 data quality rules and different kinds of rules for completeness, conformity, and timeliness. We're using Informatica to implement those rules in Cloud Data Quality.

Informatica has CDI. So, if you find some issues, you can always integrate your CDI and then fix your data.

The reusability factors are nice. The Cloud Data Quality is much better. A major flaw in the previous version was integration with the catalog, which is now seamless.

I have been using Informatica Cloud Data Quality as a partner for three months.

I rate the solution's stability a nine out of ten.

We want to keep costs down, so we are not getting enough resources.

It is suitable for enterprise level.

I rate the solution's scalability as nine out of ten.

Support response time could be better.

I use Collibra Data Quality. I switched to Informatica because Collibra cannot integrate. Colibra Cloud Data Quality is a very basic tool. There is no integration capability. If you have problem records, there is no fix to remediate them using the same tool. With Informatica, you can integrate with CDI and then create a remediation plan.

The initial setup was straightforward, and we were able to start configuring the rules quickly, etc.

It took about half a day to deploy since we are also learning.

There are different tiers based on consumption, but there is no flexible option. The catalog grows slowly over time. It would have been nice to use a flexible feature at the beginning and then transition to a model where you have a fixed set of units that you consume and pay for. If you exceed those units, you move to the next tier. We were expecting a flexible pricing structure, which we did not get.

We would have preferred a pay-as-you-go model. Although pay-as-you-go is slightly more expensive, we know our consumption will not be high initially.

It is easy to integrate cloud data quality with IT workflow. We haven't faced many challenges. It is fairly straightforward.

I recommend the solution.

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

I use the solution in my company and have worked with two tools from Informatica, both on on-premises and cloud models. I have experience with Informatica Axon, and I have used the cloud services under Informatica CDGC.

The use case of the tool is basically in the banking sector. It is used to optimize certain areas of a project. In Europe, we have a GDPR implementation. In the Middle East, there is the Central Bank of the UAE and UAE data protection law. Implementing data protection laws and ensuring that all the policies are enforced for financial security is my use case. I have to make sure the bank or financial institution meets the requirements of the Central Bank of the UAE. Data quality is another use case where my company handles corporate and retail customer data, and protecting their information is known as PII. The tool ensures that the system holds the PII data properly.

For data lineage, we look for things at a transformation level and how the data is transforming and managing the ETL mapping. Every tool gives this information about how the data goes, but our company is interested in knowing how the data is transforming and the transformation logic between the two data sources.

There are some tool limitations. Some connectors do not scan the metadata properly. If I want to scan the metadata from the data lineage or the Python code, such areas can get tedious in the tool. To manage such areas, one needs to have a lot of coding knowledge, and you need to know how to apply the code, and only then can you get it fixed. There is no user-friendly enterprise.

There are certain shortcomings even if we opt for subscription-based technical support.

I have been using Informatica Axon for four years. I work as a consultant.

It is a stable solution. Once it is implemented, we will handle everything for the business. Stability-wise, I rate the solution an eight out of ten.

It is a highly scalable solution. Scalability-wise, I rate the solution an eight out of ten.

The tool is meant for enterprise-sized businesses.

I rate the technical support a six out of ten.

I have experience with Informatica Data Governance.

If one is difficult and ten is easy, I rate the product's initial setup phase an eight out of ten.

The solution is deployed on the cloud, specifically if you have cloud-based virtual machines. If there are compliance issues, and you need to hold the metadata only on-premises models, you can do that, too.

The solution can be deployed in a few days.

It is an expensive solution. I would say it is the most expensive solution in the market.

For the features of the software, the price is justifiable.

Speaking about how the tool enhances data governance tasks, I would say that we have three types of users, consisting of the consumer, who are normally a business user, then we have a developer and finally the admin. Our company onboards the user, and then the user can collaborate, comment, ask questions, give ratings to their assets, publish the data to the marketplace and go for downloads.

One needs to resolve the problem that stems from the fact that different people can have different understandings of the concepts associated with the tool. A database administrator may see an area as a table, but for a business, it may be a person. The tool gives you a common understanding of the business concept. The tool also provides lineage data and how the business data is performing. It provides an interface between organizational policies, the different processes governed by a certain policy, and the different systems governed by which policy. The tool gives you a 360-degree holistic view of the data.

The cloud version of Informatica Axon utilized the AI for the classification purposes, data domain and automatic data tagging. In my company, we use the tool's AI capabilities.

I will recommend the tool to others.

I rate the tool an eight out of ten.