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Data Mapping: a key function of every data driven organisation

Updated: Apr 11, 2023

Data is a valuable asset for any organization, as it can provide insights into operations, customers, and markets. However, data needs to be properly managed and maintained to ensure its accuracy and reliability. Data mapping, data cataloging, and data stewardship are three key processes in the data management lifecycle that help organizations ensure that data is properly managed and utilized.

Data Mapping: from data collection to analysis and indexation

Data mapping is the process of identifying the relationships between data elements from different sources. It is a critical step in data integration, as it ensures that data from different sources can be properly combined and analyzed. Data mapping involves analyzing data structures, identifying data elements, and determining how they relate to each other.

For example, suppose an organization has customer data in one system and sales data in another. Data mapping would involve identifying common data elements, such as customer ID, and mapping them between the two systems. This would enable the organization to analyze sales data by customer, providing insights into customer behavior and preferences.

Data Cataloging for better data inventories

Data cataloging is the process of creating a comprehensive inventory of an organization's data assets. It involves identifying data sources, documenting data schemas, and capturing metadata such as data definitions, data quality rules, and data lineage information. The resulting data catalog provides a central location for users to discover, understand, and access data assets.

Data cataloging is important because it enables organizations to effectively manage and utilize their data assets. A well-designed data catalog can improve data discovery, enable more efficient data integration, and provide better visibility into data quality issues.

Data Stewardship

Data stewardship is the process of managing data assets throughout their lifecycle, from creation to deletion. It involves defining data policies and procedures, monitoring data quality, and ensuring that data is properly secured and managed. Data stewards are responsible for ensuring that data assets are properly utilized and that data-related risks are identified and mitigated.

Data stewardship is important because it ensures that data assets are properly managed and protected. Effective data stewardship can improve data quality, reduce data-related risks, and increase user confidence in data assets.

Master data mapping for better ROI

Data mapping, data cataloging, and data stewardship are all critical processes in the data management lifecycle. They help organizations ensure that their data assets are properly managed, utilized, and protected. By investing in these processes, organizations can improve data quality, enable more effective data integration, and provide better visibility into their data assets.

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