It's about mastering various domains. For example, an organization might want to master customer data residing within their IT landscape. This includes all master attributes related to customers, like name, email ID, phone number, address, and potential information like stores they visit. Ideally, if the organization also stores data related to those stores, all that information, files, and everything would be included. So, these master attributes would lie within the MDM system.

Here's where things get interesting. I'd bring this data from disparate sources. For example, accounting systems hold phone numbers, email addresses, and maybe even bank information (just an example). 

But another system, like the ER system, might have different information, like the customer's spouse. So, I'd likely get streams from both these systems, but there might be an additional attribute in the ERP system, like the spouse's name.

Now, looking at all these different attributes lying in different systems, one system might have my name as "Raja S.," while another might have it as "Raja Soni." So, the question becomes: are Raja S. and Raja Soni the same person? How do you identify them from these records?

They try to match these records based on phone numbers or any other common attribute between the two systems. Then, I would have a complete record in MDM, which is called the "Golden Record" - the single version of truth within the system.

Furthermore, MDM can also contain additional attributes that the ERP or accounting systems didn't have. So, imagine ten different applications or data sources feeding customer information. I can gather all of that information and create a single version of the truth for a particular customer within the MDM system.

Additionally, if I want my customers to update any information, I can provide a form where they can enrich their data. For example, they could potentially enter their Social Security number (although this wouldn't be common practice). This is just an example of how someone might want to collect this information. So, I can create a form and say, "Okay, can you directly feed this into the MDM system?" This becomes an enrichment opportunity as well.

With Informatica MDM, before you consume the data, you need to check what kind of data it is. There could be some systems where the first name is missing, or the last name is listed as "missing." 

This is where, before consuming or ingesting data into any MDM system, I can filter it out or rather do profiling using Informatica's data quality tool, which is a different tool called IDQ. I can profile the data, okay, and see the current state of the data from our system, any other database, or any source system. 

This is where I'll identify issues like missing phone numbers, incorrect cities, and other things.

So, when I see that the data is incorrect or incomplete (not just incorrect, but also incomplete), I can go back to the source system based on these profiling reports. I would say, "Source XYZ, you have missing data. Can you please ensure that you send it?" So, when I ingest data into the MDM system, I will only ingest it with certain rules. 

These rules define that only records with a first name, last name, city, phone number, and email address should get into MDM. If any of this is missing, I'm not going to let it get into the system.

I would ask the business to review those and then probably ask the system to correct them and then feed them again until the defined criteria are achieved. That's how I improve data quality using Informatica MDM.

Plus, I can also decide that once the data is in MDM, it can feed back to these source systems from where it was originally consuming the data. So, whatever is corrected gets looped back to these sources if they allow me to publish it to them. 

Then, this automatically becomes a cycle: data comes in, gets a data quality check, then enters MDM, and then can be fed back to the source systems if they accept it.

First and foremost, data profiling is a very important aspect, because it allows me to understand the state of the data from the different source systems and applications I'm going to pull into MDM. This is crucial, as it helps me understand the existing data landscape.

Next, Informatica MDM allows you to perform fuzzy matching. Like the example of Raja S and Raja Soni mentioned above. With fuzzy matching, I can define a threshold, and the system will let me know whether these two records are the same or not. 

This is where I think MDM shines - with its strong fuzzy matching algorithm. This is the essence of Informatica MDM. Based on these results, I can write our match conditions and then perform the corresponding data management activities.

When it comes to how data is governed - how accurate it is, what's missing, and what's not.

There are other Informatica tools involved: Informatica Enterprise Data Catalog (EDC) and Informatica Axon, which is specifically a governance tool. With these tools, users can understand data quality. 

Data quality, Informatica EDC, and Axon work together - they "talk" to each other. The moment Axon identifies that data is bad, incomplete, incorrect, or whatever, the governance tool allows you to monitor all of these things and feed them back into the organization.

For example, if someone within the organization is using the governance tool, which is connected to data quality, they might realize: "This particular source isn't giving me certain information, like city data. But I need city information for my XYZ data usage. So, I should focus on another data source or application where customer cities are available." Based on this, data governance can be implemented, and workflows can be established.

MDM also provides workflows. When records come in or if a customer wants to update a record directly in MDM, different personas can be defined. 

A workflow would then be triggered, and someone could review the data being fed through these forms or sources. They might reject or accept it based on predefined criteria. This is how data entering MDM is governed, ensuring everything is correct and meets organizational standards.

I feel the out-of-the-box APIs or the API management could be improved slightly from their current state. It could be more user-friendly.

In future releases, I would love to have more reports and dashboards available within Informatica MDM specifically for master data reporting. 

Currently, there aren't many reporting functionalities offered. While it's true that reporting isn't a core feature of any MDM system, they do have basic dashboard reports. I'd like to see them made more customizable and offer more options for creating reports.

I have been working with it for more than ten years. 

Stability-wise, it's also pretty decent and stable. So, I would rate the stability an eight out of ten. 

I would rate the scalability an eight out of ten. It's pretty good because mastering data across various domains like suppliers is crucial. Informatica is probably the best when it comes to multi-domain solutions.

There are around 500 end users. 

The quality of resources is good, and the time is acceptable. However, the initial quality of resources assigned to support tickets could be better.

Neutral

I'd rate Informatica higher. The biggest reason is the multi-domain capability. Not all vendors offer that flexibility. 

Additionally, Informatica is actively working on a clear, built-in AI engine for its tools. The SaaS version functions well, and they've introduced CLAIRE AI engine for on-premise versions. This engine learns from usage within your organization, further enhancing the experience.

The complexity of the setup depends. For example, it is different for the on-premise version. Now, Informatica has mostly shifted towards a SaaS model, which is essentially plug-and-play. You just need to log in and start using it, making it very simple. 

However, for the on-premise version, the setup process requires some expertise. It's not something just anyone can do. You need experts in place to handle the setup effectively.

Within the organization, businesses have benefited significantly. Tasks that used to take four to six weeks now only take three to four days.

Pricing can vary because Informatica doesn't have a standard price across the board. It depends more on the sales representatives in different regions. They essentially call the shots and decide the discount percentage for each customer.

So, it's quite flexible, like a bargain, in a way, but it depends on the salesperson.

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

I absolutely recommend it. If you're looking to implement a Master Data Management (MDM) solution, Informatica MDM is the most flexible tool available in the market. Compared to its competitors, it offers several advantages.

Firstly, it provides the option to move seamlessly between on-premise and SaaS versions. If you start with the on-premise version, you can easily transition to the SaaS model later, if needed. 

I use Informatica Data Quality to consolidate master data across our organization, ensuring consistent and high-quality data. Combining MDM and data quality features, we address issues like customer data inaccuracies. Additionally, we document business terms in our data catalog for a unified view across the company.

The profiling feature in Informatica Data Quality is incredibly effective for data governance. It helps identify data types and potential duplicates, streamlining the detection process. It also suggests matches with predefined fields in our catalog.

There is room for improvement in the Data Marketplace aspect. Specifically, we found some basic functionalities lacking, like transparent integration of quality indicators. Customizability and additional features in the Data Marketplace would be welcomed in future updates. 

I have been working with Informatica Data Quality for three years.

I would rate the stability of the solution as an eight out of ten.

Scalability with Informatica had some initial challenges, especially when ingesting metadata into the data catalog due to the large volume of source systems and data. While it eventually worked, it took considerable time. Overall, I would rate it a six out of ten for scalability at the moment.

Initially, a few hundred users were using Informatica, but now it is a few thousand. 

The technical support is good. I would rate them at a seven out of ten.

Neutral

Maintenance and troubleshooting are handled solely by the vendor.

Informatica's licensing cost is among the highest in the market. I would rate it as a five out of ten in terms of costliness. With Informatica, we have a single bundled agreement covering the entire solution based on total capacity rather than specific modules. 

Before choosing Informatica, we evaluated various vendors, including IBM and Microsoft. Initially, we considered a best-of-breed approach, but Informatica emerged as the preferred choice for three out of four key areas: MDM, data quality, and data marketplace. While there were some limitations in certain tools like the data marketplace and data catalog, we opted for Informatica's complete suite to avoid additional integration efforts and to capitalize on its strengths in critical areas.

The rule-based strategies feature in Informatica Data Quality has greatly benefited our data quality initiatives. With predefined rules in place, it provides a solid framework for assessing data quality. While data quality ultimately depends on source system updates, these rules give valuable insights and are heavily used alongside automatic profiling for effective data management.

Informatica Data Quality works within our IT setup for analyzing and reporting on data quality. It doesn't directly integrate with other tools, but it gives us clear insights. Data flows from sources to Informatica for analysis, and then to data stewards for updates, but there is no integration back to the original applications yet.

Navigating between modules within Informatica isn't always seamless. For instance, actions in the catalog might not be visible in the data marketplace.

Overall, I would rate Informatica Data Quality as an eight out of ten.

I mainly use it for data management.

It's for tool management, maintaining the golden record of customer status.

Data integration should be improved. Another area of improvement is customer applications, along with business 365 application case integration between applications.

I have been using this solution for three years now. I work with the latest update.

I would rate the stability a six out of ten. There is room for improvement in the stability.

I would rate the scalability of the solution an eight out of ten. There are currently nine end users in my team. There might be more people in the company. 

Recently, Informatica MDM upgraded, it transitioned from its traditional on-premise MDM offerings to a cloud-based platform called Informatica Intelligent Cloud Services (IICS). So, we are not planning to expand its further usage.

The customer support and service are helpful. 

Neutral

I would rate my experience with the initial setup an eight out of ten, where one is difficult, and ten is easy. 

It is very easy to set up. However, the deployment time depends on the configuration. It can take 10 to 15 minutes.

The pricing is reasonable.

The users should have more training on Informatica MDM, especially practical training. The vendor should provide some practical training.

Overall, I would rate the solution 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 works with our different customers to implement and install the solution.

The workflow in Informatica Axon is intelligent and good. Informatica Axon provides good data collection and good search criteria. In Informatica Axon, workflow and business glossary are good.

There are some limitations with Informatica Axon when one tries to connect or integrate it with Jira. For example, I can't delete any workflows after the integration process. There are issues with the integration capabilities of the tool with third-party solutions, specifically Jira.

I have experience with Informatica Axon for two to three years.

It is a very stable solution.

It is a scalable solution.

I recommend the solution to big companies because its functions are suitable for high-end companies.

The P1 support offered by the solution's technical support is very fast. If it is not P1 support, the support a user might get will be slow as it takes time. I rate the technical support a seven out of ten.

Neutral

For data governance, I work with Informatica Axon only. I prefer Informatica Axon for enterprise metadata management at an enterprise level, data quality, and integration. I only recommend Informatica Axon, mainly for data governance.

The product's initial setup phase is very easy.

For each of our company's customers, with an installation scope in place, it doesn't take much time. The product's implementation scope differs from the installation scope. I usually help our company's customers implement the tool.

The solution is deployed on an on-premises model.

Informatica Axon is a very good product with an easy implementation phase and a lot of information about the tool available online on the internet.

I rate the overall tool an eight out of ten.

We use Informatica Axon to make sure our data is in good shape across different apps. It helps us work with clients to set rules for data and keep things organized. For a bank, it makes sure customer info, like contact details, is correct and follows privacy rules. Axon also made it easy for our team to check and trust the data we were using. It is like a tool that brings everyone together and helps us find and use data better.

The most valuable feature of Informatica Axon has been the data marketplace. It has been a favorite because it not only boosts user engagement but also fosters collaboration. Implementing it was straightforward, and it seamlessly became a part of our organizational culture, making it easy for people to work together and share information.

One area I would like to see improvement in Informatica Axon is achieving feature parity between the on-premise and cloud versions. It would be great if the cloud version could match the full range of capabilities available on-premise. This would ensure a seamless experience and allow users to leverage all of Axon's features regardless of their deployment environment.

I have been using Informatica Axon for almost two years.

I would rate Informatica Axon at eight out of ten for stability. The main thing to improve is making the features and interface consistent between the on-premise and cloud versions. The cloud interface looks modern with DDGC, but the on-premise one is a bit outdated. Aligning them would be a big plus.

It is quite scalable. We had approximately 500 end users.

The standard support is good – they usually get back within the agreed time. If you have a higher-level support contract, like gold, silver, or platinum, you get a faster response, but the support team is generally effective and helpful.

Setting up Informatica Axon varies, but it generally depends on having a good grasp of data concepts. If you understand data well, the setup becomes more straightforward. Deploying and maintaining Informatica Axon depends on the use case, but I would say not too many people are needed. I would recommend at least two people per department or business unit to start with. It is good to have a mix, like an admin or engineer and a developer. One person could handle the technical side, while the other, who understands data and processes well, can provide expertise.

The licensing for Informatica Axon is expensive, but it provides value for the investment. With the new cloud platform, they have introduced a consumption-based license model, where you only pay for what you use. This change has made it more affordable and easier for users.

For those looking to start using Informatica Axon, my advice is to do thorough research, especially on available solutions, as integration with other software plays a big role. With the Informatica cloud solution, you have the flexibility to choose features that suit your needs. Starting with data quality is usually a good move before diving into more complex tasks. Consider exploring tools like robotics for repetitive or tedious tasks. Having someone experienced with data is a significant advantage, as these projects often have long cycles. Experienced individuals can guide you, help set realistic expectations, and emphasize the need for patience, as data governance projects take time to show results. Overall, I would rate the solution as an eight out of ten.

I use Informatica MDM to align data in my company.

The ability to aggregate and put together data from around fifty sources into one environment allows us to have a preview of everything in a single place, which is something we did not have previously in our company.

The most valuable feature I see in Informatica MDM stems from everything that touches the area of data governance.

I think everything related to the APIs and the manageability of the APIs in Informatica MDM are areas where improvements are required.

I have been using Informatica MDM for five years. I use the solution's latest version. I am a user of the solution.

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

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

Around 250 users of the solution exist in my company.

There is a need to use the solution in my company at least three times a week.

I rate the technical support an eight out of ten.

Positive

I have experience with other solutions. I switched to Informatica MDM from other solutions since it offers better scalability options and interoperability.

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

My company has deployed Informatica MDM with the services offered by our cloud partner.

Informatica MDM's deployment phase takes around a year to be completed.

Two people, who are data engineers specialized in Informatica MDM, are required for the deployment phase of the product.

Informatica MDM's deployment phase was carried out with the help of my company's in-house team and Informatica's partner.

I rate Informatica MDM's price a six on a scale of one to ten, where one is a low price, and ten is a high price.

Ideally, only one person is required to take care of the maintenance part of the product, but with the number of terminals where the solution is deployed, there may be a need for three or four people.

I recommend the solution to those who plan to use it.

I rate the overall solution an eight out of ten.

A wide range of solutions exist because data is primary, and my company looks over many overall data management solutions, from which Informatica Data Quality becomes one of our biggest priorities.

I cannot just go into details of the product's features randomly because if you look at a very wide range of overall requirements, be it Informatica or Talend or more data lake solutions like Snowflake. My company goes through an entire range of areas, making it difficult for me to just speak about the features.

Accuracy is one of the key areas a client looks at before using a solution. Considering internal data from legacy systems, it is quite difficult to know if Informatica Data Quality meets that high level of accuracy criteria. The aforementioned area can be considered for improvement in the solution.

I have been a consultant for Informatica Data Quality for two years in my company. I don't directly use the solution.

From a stability point of view, I haven't heard of any complaints about the solution from any of my company's clients who use it.

I don't go into the technical side of Informatica Data Quality much since I mostly work on the procurement side and market knowledge area related to the product. Scalability remains one of the requirements of the clients who buy the product, especially for future growth. My company caters to a mixture of clients, consisting of small, medium, and enterprise-sized businesses.

I do not go into the complete deployment areas of Informatica Data Quality.

The solution is deployed on a hybrid cloud.

Informatica Data Quality is a product that is worth the money.

I rate the product's pricing a seven on a scale of one to ten, where one is the lowest price and ten is the highest price.

I do look at a number of data quality tools, but Informatica, Talend, and Ataccama are a few of the top solutions I have come across.

My company deals with Informatica Data Quality since Informatica is a big vendor in the overall data management area.

I won't be able to speak on how I can recommend the solution to others since my suggestions will have to be based on the product's features and technical details. I wouldn't be able to point out anything about the product in detail, especially since I am not much of an end user.

Based on the feedback that I have received about the product from my company's customers, I rate the overall product a seven or eight out of ten.

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 it for various use cases, including data provisioning, data validation, continuous monitoring of data quality, and data standardization.

We have implemented both data profiling and data quality transformations for data validation. These are the two major components we rely on, with data profiling helping us understand the data's characteristics, and data quality transformations ensuring data validation.

Exploring the possibility of incorporating AI capabilities that can suggest additional rules would significantly streamline our data analysis process following data profiling. Many other tools offer this feature, enabling them to suggest rules, which can be generated with just one or two clicks.

I have been working with it for almost seven years.

Once it was implemented, we din not encounter any stability issues. I would rate it nine out of ten.

The scalability of the solution depends heavily on the design approach. Regardless of the tool used, the effectiveness of the data quality framework hinges on proper design. If the framework is not well-designed, it may not deliver the desired results. I would rate it eight out of ten.

We receive excellent support on a priority basis. I would rate it nine out of ten.

Positive

I would rate the installation and configuration process as moderately complex.

If it has been implemented effectively, I would say it is the best solution. When considering the use of the data governance package, combining Axon ADC and Informatica Data Quality together provides a comprehensive approach. I would rate it eight out of ten.