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Data Governance Vs. Data Management: What’s the Difference?

Zoha Shakoor

Content Strategist

April 4th, 2024

The difference and relationship between data governance vs. data management can be confusing, even though both are essential for data strategy. This blog takes a close look at the roles that data governance and data management play in leveraging data as a strategic asset, and how they contribute to enhance data-driven decision-making and operational excellence. 

What is Data Governance?

Data governance includes the frameworks, policies, standards, and processes that guide how data is collected, stored, accessed, utilized, and disseminated within an organization. Its primary goal is to certify data’s trustworthiness, security, compliance, and alignment with the business objectives and values.  

Data governance involves establishing clear data ownership, accountability, and decision-making authority regarding data-related matters. Data governance serves as a foundational element of data management, focusing on overseeing the operational lifecycle of data as it flows through an organization. 

What is Data Management?

Data management is the process of setting up, applying, and managing frameworks, rules, and methods to address all the data lifecycle requirements of an organization.  This process ensures that data, treated as an asset, is managed with care to support complex analysis and reporting.  

Data management includes various tasks and projects focusing on establishing policies and standards for data quality and security. 

Data Governance Vs. Data Management: Differences

While data governance and data management are essential components of an organization’s data strategy, they serve different purposes, have distinct scopes, and achieve separate outcomes. These two concepts can be differentiated in terms of process, people, and technology.  

Process 

Data governance focuses on establishing the “how” of decision-making around data use. Its processes involve: 

  • Setting up data quality checks to ensure data reliability. 
  • Defining data access policies to control who can view and use data. 
  • Ensuring compliance with various regulations to mitigate legal risks. 
  • Creating and maintaining a business glossary to standardize data terminology. 

Data management, in contrast, is about implementing the “how” of using data within the established framework of governance. Its processes include: 

  • Performing data transformations to keep data in consistent formats.
  • Storing data in appropriate repositories like warehouses or lakes.
  • Exploring data to address both operational and analytical needs.

People

Data governance involves a mix of business and IT stakeholders, including business managers, domain data owners, and other non-technical roles. This group focuses on setting the rules and policies for data use and protection without delving into technical specifics. 

Data management requires technical expertise to implement the governance framework practically. Roles such as data engineers, architects, and database administrators work on the technical execution, from data storage setups to access rights and controls. 

Technology 

Data governance tools document and enforce data rules and policies across an organization. They include solutions for managing data dictionaries, glossaries, and catalogs, helping to ensure everyone operates from a common understanding of data assets. 

Data management tools are designed for the operational aspects of data handling, including storage, processing, and exploration. These tools facilitate the technical work of managing data flows, maintaining databases, and analyzing data. 

How Data Governance & Data Management Work Together 

Data governance and data management are complementary practices, working together to fulfill an organization’s data strategy. Their collaboration ensures data is managed efficiently and aligns with company policies and objectives, thus maximizing its value.  

Improving Data Quality for Decision-Making and Operations 

Data governance involves creating a comprehensive system that catalogs and defines every piece of data, detailing its purpose, usage, and origin. It provides a structured framework that focuses on data quality and involves accessibility, privacy, and ensuring data is effectively managed across its lifecycle. 

Data management, on the other hand, is about systematically organizing and integrating data from various sources into cohesive storage solutions, enhancing seamless operation and accessibility. This process supports the execution of data governance policies by applying data quality checks, cleansing, and profiling to maintain the integrity and usability of data. 

Enhancing Data Security and Privacy 

Data governance sets the standards for legal compliance with data regulations and provides training for business units on handling data securely and legally. It outlines clear policies on who has the right to access which data, in what situations, and with which protective measures in place, serving as a strategic guide for implementing security and privacy safeguards. 

Data management, on the other hand, puts these guidelines into action. It involves specific steps like automating data encryption and setting up access controls, ensuring that data handling across the organization aligns with the governance framework. This ensures that sensitive data is only accessible to those who need it, under strict conditions, safeguarding privacy and compliance. 

Integrating Data for Shared Business Operations 

Data governance ensures that data integration efforts align with company policies, facilitating smooth collaboration between teams through tools like data catalogs and business glossaries. 

Data management is responsible for the technical side, implementing ETL processes and data pipelines as guided by governance policies to enable efficient data sharing and integration. 

Benefits of Integrating Data Governance & Data Management  

Integrating data governance and data management into a unified strategy offers various benefits to organizations, converting data into a powerful tool for decision-making and operational improvement. Below are five key advantages of this integrated approach: 

1. Streamlined Regulatory Compliance

Integrating data governance and data management streamlines compliance with industry-specific regulations. By establishing clear guidelines for data usage and storage, organizations can more easily demonstrate compliance, reducing the risk of penalties and enhancing trust with stakeholders. 

2. Optimized Data Utilization

A unified strategy improves the organization’s ability to use data effectively. Tailored data management processes, informed by governance policies, ensure data is consistent and aligned with specific business objectives, leading to more targeted and impactful data analysis. 

For example, a retail chain would use integrated data strategies to precisely target customer segments, improving marketing campaign responses by aligning offers with customer preferences. 

3. Accelerated Innovation

When organizations harmonize data governance and management practices, they can accelerate their innovation cycles. Having reliable, well-governed data at their fingertips allows teams to quickly prototype, test, and refine new ideas, driving faster time-to-market for new products or services. 

4. Reduced Data Management Costs

Efficient data governance and management practices reduce the overall costs associated with data storage, processing, and cleanup. By eliminating redundancies and streamlining data workflows, organizations can achieve significant savings, reallocating resources to strategic initiatives. 

For instance, an educational institution could streamline its data management by integrating governance principles, which leads to the elimination of duplicate databases and automates data quality checks. 

5. Strengthened Data Security

A cohesive approach enhances data security, combining governance policies that define data access controls with management practices that implement these controls in practical terms. This dual layer of protection ensures sensitive data is safeguarded against unauthorized access and potential breaches.  

Investing in the Right Tools for Data Governance & Data Management  

Tools and software are essential for managing and governing data. They automate and integrate processes, streamlining the establishment and enforcement of data governance policies across an organization. The impact of tools and software on data governance and management extends significantly beyond simplification, offering efficiency and effectiveness. According to a study by the International Data Corporation (IDC), organizations that use automated tools for data governance and management can see up to a 65% reduction in time spent on data-related tasks.  

This automation enables companies to focus more on strategic initiatives rather than routine data maintenance, ensuring that data governance policies are applied consistently and comprehensively across the board. By integrating these processes, organizations facilitate a more cohesive data strategy, allowing for seamless policy enforcement and streamlined data handling that align with their objectives and compliance requirements.  

  • Consistency

 A tool must have the feature of automating data quality checks. The technology can systematically scan through vast datasets, identifying and correcting errors without human intervention. This saves considerable time and enhances data accuracy, a fundamental aspect of good governance and management. 

  • Integration Capabilities

The software should also combine different data sources into one organized data warehouse.  Such a tool enables organizations to consolidate their information assets, making it easier to manage, analyze, and utilize data in line with governance standards. This integration is essential for maintaining a single source of truth, important for informed decision-making and strategic planning. 

  • Efficiency and Scalability

These tools provide scalability, allowing data governance and data management practices to evolve with the organization. As data volumes grow and business needs change, a scalable software solution can adapt, ensuring that governance and management efforts remain efficient and responsive. 

Final Words 

To improve a company’s data, having a good link between data governance and management is key. It is essential to recognize that aligning data governance and data management successfully is important for turning data into a key asset for any organization. This alignment streamlines compliance, data security, and drives businesses towards operational excellence and innovation. As we move into the age of big data, having a unified approach to data governance and data management is becoming increasingly important. 

Astera offers intuitive solutions designed to simplify the complexity of data operations, for those seeking to streamline their data governance and data management processes. With its user-friendly interface and powerful automation capabilities, Astera facilitates the seamless integration of data governance policies and data management practices. Experience how Astera can transform your data governance and management initiatives by signing up for a 14-day free trial. 

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