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Data Management Overview

What is Data Management?

Data management refers to the process of organizing, storing, protecting, and maintaining data throughout its lifecycle.

Companies need physical and Logical Data Management because they serve different but equally important purposes in managing data. However, often Logical Data Management is an overlooked and underused data management style. Logical Data Management can add tremendous productivity and agility gains to existing data management practices. Here is a quick overview of these two data management styles.

Data Management Overview

What are the Different Types of Data Management?

Data management practices can be broadly categorized into two styles. For best results, these practices should work together.

Physical Data Management

Physical data management is the process of implementing and maintaining the physical storage, access, and processing of data in a database management system or other data storage technology. It involves implementing the logical data model in a specific database technology and defining the physical characteristics of the data storage and access.

We are all familiar with relational, NoSQL, and Data Warehouse management systems, etc. All of these are examples of physical data management.

physical data management

Logical Data Management

Logical data management is a process of organizing and managing data based on its logical relationships, meaning, and context. It focuses on defining data elements, their relationships, and their attributes in an understandable and meaningful way to both business and technical users.

The goal of logical data management is to create a conceptual model of the data that all stakeholders can easily understand and maintain. This includes defining data entities, their attributes, and the relationships between them, as well as defining business rules and data quality standards. The result of Logical Data Management is a logical data model, which is a high-level view of the data that does not depend on any specific technology or implementation.

Logical data management is critical for ensuring that data is well-organized, understandable, and meaningful, essential for effective data governance, integration, and analytics.

While physical data architecture has been the predominant architecture used for decades, logical data management is increasing in popularity, for its agile nature. One of the hottest topics in the data management space is data fabric, which enables augmented data integration and sharing across heterogeneous data sources. This concept of heterogeneous data sources means you are establishing a logical data access layer atop these various data sources. Likewise, another very popular data management pattern today is data mesh, which is inherently a logical data architecture. It is built on a distributed data platform, and data access is gained through domain-based data products, which are located in an abstraction layer of underlying data sources. The consumers of data products do not necessarily see – or even know anything about – the underlying data sources. These links will provide you with more detail about data fabric and data mesh.

Logical Data Management
Data Management Overview

Comparing and Contrasting the Different Types of Data Management


Logical data management is concerned with the high-level organization and classification of data, while physical data management is concerned with the physical storage and management of data.


Logical data management focuses on the meaning and relationships of data, while physical data management focuses on the technical aspects of data storage and retrieval.


Logical data management is often more abstract than physical data management. It deals with data models, structures, and relationships, while physical data management deals with data storage technologies, data compression, and data security.

Data independence

Logical data management aims to provide data independence from the underlying physical data storage, allowing data to be manipulated and viewed in different ways without affecting the physical storage. In contrast, physical data management is closely tied to specific storage technology.


Logical data management is typically performed by data architects, data modelers, and business analysts, while physical data management is typically performed by database administrators, storage administrators, and system administrators.

Data Management Overview

What Core Technology Will You Need to Adopt and Implement Logical Data Management?

Data Virtualization

Data virtualization implements logical data architecture and management that integrates all enterprise data siloed across disparate systems, manages unified data for centralized security and governance, and delivers it to business users in real time.

To learn more about data virtualization, visit the link below.


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