MDM Architecture - Deep Dive

Do you need details on Informatica Master Data Management Architecture? Would you also be curious to know what parts were involved? If so, you've come to the correct spot since we'll go into detail about the Informatica MDM Architecture in this post. Additionally, we will comprehend the upstream and downstream systems that are involved.

MDM Architecture Overview

<Check image>

Master Data Management, sometimes known as MDM, is a method for organising company data. We can attain uniformity, precision, and consistency in the company data by using a number of MDM methods. These mission-critical data can be used to improve process management and advance organisational objectives. We may effectively implement data governance practises with the aid of the MDM solution.

If we look at the big picture of MDM architecture, we can see, there are basically three layers. The first layer is the source systems, the second layer is MDM implementation and the third layer is consumption.

The source system layer includes operational systems which maintain 3rd party data. This layer may include multiple sources with different platforms such as Siebel, Oracle, SAP, Acxiom or D and B. The data from source systems will not be pushed to MDM layer directly. In order to push data from source system to MDM layer, we normally use ETL layer (Here ETL stands for Extract, Transport, and Load). This data push may happen in the batch mode or real-time mode or near real-time mode.

Once data is entered to MDM landing tables, first data cleansing will happen. Data standardization rules will be applied to enrich the business data. Cleansed and standardized data will be loaded into staging tables. To achieve data integrity constraints are enforced to the Base Object table while loading data from staging table to base object table. This is not the end of the process. Actual processing work will start after this. Even though the cleansed and standardized records are loaded in the MDM system, there will be duplicate and fuzzy records in the system. The next processes i.e. match process will identify such records based on the business criteria and rules developed during the data quality analysis phase. These duplicate records will be consolidated to make a golden copy of records. The golden copies of records may hold relations among them e.g. Manager and Employee relationships or Organization and Branch relationships etc. These relationships can also be maintained in the MDM system in the form of hierarchies.

The data stewardship will help to keep a golden copy of records in its consistency state and enforce controls on create and update processes through the user interface which comes with Informatica MDM product. e.g. Informatica Data Director or Customer 360 application.

Since the security of all these MDM capabilities, including data modelling, data quality, duplicate detection, record consolidation, preserving hierarchies, and workflow maintenance, cannot be compromised, MDM also includes role-based in-built security. We can, however, incorporate the company's current security measures, such as LDAP security for authentication, if necessary. However, in accordance with the role-based process, authorization of MDM components must take place in the MDM hub. One fantastic feature of Informatica MDM is that it uses metadata to keep MDM configurations up to date.

Encoding Enhancers created golden of records in the MDM hub. What we do with this data?

Thanks for asking that question, actually, after the successful implementation of MDM solution, the golden copies of records will be available to the consumer to consume. There could be a third party application which can consume data directly from MDM. However, in most of the cases, the data will be pushed from MDM to these consuming system through ETL layer as like data loading from source systems to MDM. It could be the batch mode, real-time or near real-time.

There are few other types of systems such as analytical or reporting systems which consumes data for different purposes. The analytical consuming systems such as Data warehouse, Data marts or Portal dashboard will use these golden records to analyze the data and comes better organization growth plans. On the other hand, reporting consuming systems such as business intelligence or corporate performance management will help to produce the report to achieve effectiveness in business processes and to achieve business goals.