Consolidates customer data from disparate sources like accounting, ER systems, and more and establishes clear guidelines for data quality and consistency within the organizationFirst 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.
