What is a data domain? Meaning & examples

Matthew Cawsey | March 21, 2022 | 4 minute read

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What is a data domain? Meaning & examples

Master Data Management Blog by Stibo Systems logo
| 4 minute read
March 21 2022
What is a Data Domain? Meaning & Examples ➤
7:40

Master data management (MDM) is a comprehensive approach to managing an organization's critical data assets. At the core of master data management are data domains, which are specific categories of data that are critical to an organization's operations.

Data domains can include customer data, product data, supplier data, location master data and more. Each domain requires unique management and governance to ensure data accuracy, consistency and completeness across the enterprise, guided by principles of data modeling and metadata management.

In this blog post, we will dive deeper into the concept of data domains within master data management, explore some of the most common data domains and discuss the benefits of managing multiple data domains with multi-domain master data management like those offered by IBM, Microsoft and other SaaS platforms, which ensure scalability and data integration across systems.

what-is-a-data-domain

Data domain definition

In data management, a data domain refers to a set of values or attributes that share a common meaning or purpose, often seen as a logical grouping of data within a data lake or data warehouse.

It can be thought of as a category or a group of related data elements that are characterized by the same set of attributes or characteristics. For example, in a customer database, which can be part of a CRM system, some common data domains might include customer name, address, phone number and email address.

Each of these data domains has its own set of rules and constraints that govern the format, type and length of the data that can be stored within it.

Data domains are important for data governance and data quality management because they provide a framework for understanding and managing the data that an organization collects and uses. By defining and enforcing rules and standards for each data domain, organizations can ensure that their data is accurate, consistent and meaningful.

Templates and a business glossary can further aid in standardizing data across domains.

What are examples of data domains?

Master data management typically includes several data domains. Here are some examples of the different data domains that can be managed through multidomain master data management:

    • Customer data: This includes data related to customers, such as contact information, demographics, preferences and purchase history.
    • Product data: This includes data related to products or services offered by an organization, such as descriptions, pricing, attributes and specifications.
    • Supplier data: This includes data related to suppliers or vendors, such as contact information, contract terms and performance metrics.
    • Employee data: This includes data related to employees, such as job titles, roles, performance and compensation.
    • Location data: This includes data related to geographic locations, such as addresses, coordinates and boundary data.
    • Asset data: This includes data related to physical assets, such as equipment, vehicles and real estate.
    • Financial data: This includes data related to financial transactions, account balances, invoices and payment processing.
    • Reference data: This includes data related to codes, classifications and other standardized reference information used across different domains.

These are just a few examples of the many data domains that can be managed through multidomain master data management. The specific data domains that an organization manages will depend on its industry, business model and data needs.

What is multidomain master data management?

Multidomain master data management is an approach to data management that allows organizations to manage multiple data domains simultaneously within a single, integrated system.

A data domain is a specific category of data, such as customer data, supplier data, product data or location data. In multidomain master data management, these different data domains are brought together into a single, unified view of the organization's data.

The goal of multidomain master data management is to provide a comprehensive and accurate view of an organization's data, while also ensuring that data is consistent and standardized across different domains.

This approach helps organizations to avoid the silos that can arise when data is managed separately for each domain, which can lead to inconsistencies, redundancies and errors.

Multidomain master data management typically involves the use of specialized software and tools to manage data across multiple domains. These tools often include data governance and data quality management features, which help organizations to define and enforce standards for their data.

The tools may also include data integration features, which allow data to be shared and synchronized across different applications and systems.

What are the benefits of managing multiple data domains with multidomain master data management?

Managing multiple data domains with multidomain master data management offers several benefits, including:

1. Improved data quality

Multidomain master data management provides a single source of truth for data, allowing organizations to ensure that data is accurate, complete and consistent across different domains. This helps to improve data quality and reduce errors and inconsistencies.

2. Enhanced decision-making

By providing a comprehensive view of an organization's data, multidomain master data management enables better decision-making. Organizations can analyze data across different domains to identify trends, patterns and insights that can inform strategic decision-making.

3. Increased efficiency

Multidomain master data management reduces the need for manual data entry and data processing across different systems, resulting in increased efficiency and productivity. Data can be managed centrally and shared across different applications and systems, reducing redundancies and improving data processing times.

4. Better customer experiences

Multidomain master data management enables organizations to better understand their customers and personalize their interactions. By managing customer data across different domains, organizations can gain a more complete view of each customer and tailor their experiences accordingly, enhancing social media and other marketing channels.

5. Improved compliance

Multidomain master data management enables organizations to ensure compliance with regulatory requirements and industry standards. By managing data across different domains in a consistent and standardized manner, organizations can reduce the risk of non-compliance and associated penalties.

Overall, multidomain master data management enables organizations to achieve better data governance and management, resulting in improved business performance, customer experiences and regulatory compliance.

Introducing data mesh and data products

A data mesh approach complements multidomain master data management by decentralizing data ownership and treating data as products.

This concept transforms data management from a centralized model to a distributed one where data products are built and consumed by different business units within an organization.

Each data product, managed by a data steward, supports specific use cases and business processes, enhancing data intelligence and promoting a culture of shared responsibility.

 


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Master Data Management Blog by Stibo Systems logo

Driving growth for customers with trusted, rich, complete, curated data, Matt has over 20 years of experience in enterprise software with the world’s leading data management companies and is a qualified marketer within pragmatic product marketing. He is a highly experienced professional in customer information management, enterprise data quality, multidomain master data management and data governance & compliance.

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