Step 4: Data integration
Data integration includes the process of capturing, consolidating, and integrating data from various internal and external sources into the MDM system.
Here are the steps that are performed in this process:
Identification of the data sources
Identify all relevant data sources, both internal and external, to be integrated into the MDM system. These can be ERP systems, CRM systems, legacy systems, external databases, cloud services or other systems relevant to your business.
Data extraction
Develop a strategy and tools to extract the data from the identified sources. This may include accessing databases, using APIs (Application Programming Interfaces), or using file exports. Ensure that the extracted data meets data quality and integrity requirements.
Data cleansing and transformation
Clean and transform extracted data to identify and correct inconsistencies, duplicates, errors, and incomplete information. Perform data cleansing activities to improve the quality of the data. This may include standardizing data formats, removing redundancies, and aligning data with the MDM system data model.
Data loading
Load the cleansed and transformed data into the MDM system. In the process, the data must be structured and formatted according to the defined data model of the MDM system. Data loading can be manual or automated, depending on the size and complexity of the data volumes.
Data reconciliation and duplicate cleansing
Identify and clean up duplicate or redundant records that originate from the different data sources. Use algorithms and matching techniques to identify and merge similar records. This contributes to data consistency and data integrity in the MDM system.
Data integration with other systems
Ensure that the MDM system is seamlessly integrated with other systems in your IT landscape. This includes synchronizing data between the MDM system and other systems such as ERP, CRM, or e-commerce platforms. Develop appropriate interfaces and data flow mechanisms to enable smooth data integration.
Data validation and quality assurance
Check integrated data for completeness, accuracy, and data quality. Perform extensive testing and validation to ensure that integrated data meets defined quality standards.
Data integration is a critical step in implementing an MDM system because it ensures that high-quality data from multiple sources flows into the MDM system and can be used as a single source of truth.
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