Informatica Intelligent Data Management Cloud (IDMC) Reviews

The most valuable features are:

• Data synchronization tasks
• Mapping designer tasks
• Scheduling

We are using this for integration of on-premise Oracle EBS, Navision and cloud applications, such as Salesforce, BigMachines, etc.

Error reporting and debugging need improvement.

They need to improve on the upgrade testing process from their end so that it does not cause any issue to existing functionality/setup.

I have been using this solution for 36 months.

Sometimes after upgrades, it gives some trouble for already working tasks. We need to report bugs to get a solution from Informatica.

We have not had scalability issues.

I rate support 8/10.

We did not have a previous solution.

Setup was straightforward and easy to work with.

I am not involved in pricing and licensing.

We looked at Dell Boomi.

Informatica Cloud is easy for development and maintenance. It really works fast and is scalable.

It allows you to build your own rules to identify the golden records as part of master data management.

It helped my client, a technology company, to identify a unique customer and remove the redundant customer information. For example, a customer might be linked with a product to the organization directly, indirectly or as a retailer. Informatica MDM helped us realize our goal of maintaining a distinct (golden) record in our database for better decision making and reporting purposes.

I've been using it for 15 months.

In general, it is good. We used to face some Java application problems, approximately two issues a month.

As the data keeps growing, we have to clear temporary storage space. Otherwise, we encountered issues in starting the batch jobs.

3.5/5.

3.5/5.

I worked as a vendor for one of my clients. As I heard recently, the contract is still on, so I think we are doing pretty well.

I used this product almost 18 months ago. Informatica is one of the renowned names in Enterprise Information Management and there has been some changes for their MDM product. I would suggest you check their recent upgrades and take an informed decision.

Our primary use case of this solution is to improve issues of security, quality and accuracy. 
We are partners of Informatica and I'm an architect. 

In terms of Data Quality, the feature most valuable to me is that the solution is applicable for both technical and business users. I like that instead of using on-premises processing power, you can now use your on-cloud platform processing power to process the data and get a faster turnaround time. From a product perspective, everything is well done. 

I think improvements can be made regarding the ability of the product to leverage the power of big data. It would also help if we could get the software as a services product so that we feed in the requirements and it's a more customized solution. I think that would increase the adoption by customers. 

I've been using this solution for three years. 

Informatica is a very stable product, I haven't had any issues with it. 

It's a very scalable solution and it has all the other big data components. 

We have a business partnership with Informatica and they are very responsive. 

I've had a lot of experience with this solution so I don't have any issues with implementation. Perhaps someone from a different background or different circumstance, may face challenges but it is user friendly so it shouldn't be a problem. Implementation generally takes about six months depending on the dimensions required. This solution cannot be implemented in a day or a week.

The pricing of this solution is definitely at the higher end and they don't provide the option of a trial version. If you look at Talend, for example, they provide a free version, so the cost of IBM and Informatica is a little high. 

The cost of the product is high, but feature wise, it provides a whole lot of features that can easily solve your problems. I would recommend this product. 

I would rate this solution an eight out of 10.

We are using the product data for building maintenance and item creation, then putting all the structures in for our new e-Catalog launch. It has been performing well.

• Its key capability is in data maintenance.
• We can maintain all the organizational data in a single software. 
• It is nice to learn. 
• We can see all our information on a single screen.

It is good for centralized data.

We cannot sell the product directly with an additional layer.

It would be more stable if we could merge all the products into a single software.

I haven't used the technical support.

I wasn't involved in the initial setup.

We were looking to market this solution, which is how we ended up using it.

Our primary use case of this solution is for data integration; integrating cloud warehouse or cloud layout. Cloud Data Integration offers capabilities that didn't exist in the on-prem version. I'm the company product manager.

The mass ingestion functionality and the elasticity of the solution are great. It enables you to leverage the elasticity capability that the cloud provides. You can build a process, scale-up and leverage all the elasticity and the automatic provision the cloud has. What took 10 hours to do in the on-prem version, takes less than an hour in the cloud. It's a huge difference. The solution is designed for a cloud-native approach with native components and connectors for all the cloud-ready solutions we need nowadays.

I think the price modeling could be improved. Currently, the IPU consumption is defined on a monthly basis and if you don't use all the IPUs available in a particular month, they are lost. A more flexible pricing model is something Informatica should look at. 

The solution is scalable. 

The technical support is good, we raise the tickets in the Informatica Support Portal. 

The solution is great once you have a clear roadmap of migration to the cloud. In the cloud migration journey, it's important to be clear of the entire process.

I rate this solution nine out of 10. 

We provide services mostly to banks. 

I am currently working at a bank where they are using Data Masking and Data Transformation at the same time. They are an old core banking system, which is COBOL, and it's unstructured data. We are using Data Transformation to transform and structure the data into a relational format.

We use the test data management to create test data from the relational data. To create the test data, we mask using different techniques for the discovery. After that, we re-transform the relational data into unstructured data to be fed into the core banking system.

The most valuable feature is data discovery. This is the most exciting feature for all of the banks.

I have encountered some issues using the substitution, which is one of the techniques of data masking. I used the substitution and software. I had issues in both when using the field, and specifying the field. Each one will have the same data for the same person, and they will have realistic data each time. This issue was raised with technical support and it was flagged as an issue that had no solution. They have indicated that it is a bug that would be resolved in the next release.

In the next release, I would l like to see the bug with the substitution resolved.

I have two years of experience with Informatica Data Masking.

This solution is stable and we have not had any issues.

Informatica Data Masking is scalable.

The technical support is good, although sometimes they don't respond quickly. Overall, they are good.

I raised the case where I was having some issues with the substitution, and it took two months. Finally, the answer was that they have no solution for this, but said they will flag it as a bug to be resolved for the next release.

As I was not able to stop the project because of the bug, I created a workaround using PowerCenter to make it work. The data was not unique. I used PowerCenter and added an ID to all of the columns, then I concatenated the ID with the columns. As an example of why this was complete is if my name is Donna, it will show as Donna123. That way, any other person named Dana in the same database or table would show as Donna246 and they would no longer be the same. With this, I would then offer a substitute.

Previously, we did not use another solution.

The initial setup is straightforward.

The length of deployment depends on the solution. For example, I find security was very easy, but the data integration was more complex. This is because it has many features and you can do many things. Setting up the data quality was also very easy.

We have deployed both on-premises and on the cloud. Mostly, I work in Lebanon and some  Arab countries also. There have been some issues with the Cloud, so they prefer on-premises software. We implemented some iPaas on the Cloud for Data integration.

It's good as a solution.

I would rate this solution a nine out of ten.

I have received feedback from certain teams and there is a steep learning curve to use this solution.

In a future release, there should be better integration with other governance tools.

I have been using Informatica Cloud Data Integration for approximately three years. We have been using it consistently for one year in a large project.

The solution is reliable.

Informatica Cloud Data Integration has a strong enterprise customer base and this is one of the main reasons why we choose to work with them. The solution is scalable.

We use other similar products similar to Informatica Cloud Data Integration.

The initial setup is not easy.

The implementation would be best to be done by experts.

Our customers sometimes are able to negotiate a much better price for Informatica Cloud Data Integration based on their relationship with the vendor.

I rate Informatica Cloud Data Integration a seven out of ten.

To cleanse and create standardization third-party data by implementing business rules and Address Doctor.

• Manually checks on applying business rules, 
• The tool helps to implement business rules.
• It helps to get quick results as well.

Address Doctor. This is the best feature to gives an accurate combination of the information provided with a level of returned threshold value.

To implement the new workflow with simple steps and a quick visualization with a 360 view of the data.