Importance of Data Management and Governance in Big Data Era

In the era of big data, data management and governance have become vital for any successful organization. With the exponential increase in the amount of data the world produces every day, the ability to organize and manage this data efficiently has become crucial.

What is data management and governance?
Data governance is a set of practices and policies aimed at ensuring the availability, quality, security and optimal use of data in an organization. Data governance is the framework that ensures the achievement of data management objectives by defining responsibilities, roles, processes, and technology necessary for this.

The importance of data management and governance
Improving data quality: Data management and governance contribute to ensuring the accuracy, validity and integrity of data, which enhances users’ confidence in it and improves the quality of decisions based on it.
Enhancing data security: Through protection and security policies and procedures, data governance helps maintain the confidentiality of sensitive data and protect it from leakage or hacking.
Maximizing the use of data: Data management enables an organization to make the most of its data by organizing it and making it available and understandable to authorized users.
Improved decision-making processes: Accurate and reliable data provided by data management and governance contribute to more effective and objective decision-making.
Regulatory Compliance: Data governance helps ensure that an organization complies with laws and regulations related to data protection and privacy.

Pillars of data management and governance
Data management and governance includes five main pillars:

Data Strategy: Establishing a clear vision of how data will be used to achieve the organization’s goals.
Policies and Procedures: Create standardized data management policies and procedures across the organization.
Infrastructure: Providing the technical infrastructure necessary to store, manage and distribute data efficiently.
Roles and Responsibilities: Define the different roles and responsibilities related to data management and governance.
Data Culture: Promoting a culture of dealing with data as a strategic asset at the organization level.
Steps to implement data management and governance
Defining data management goals: Establishing clear goals that are consistent with the organization’s strategy.
Establish a data governance structure: Establish a data governance committee and define responsibilities and powers.
Develop policies and procedures: Establish standard policies and procedures for data management across the organization.
Identifying data sources: revealing all data sources available within the organization.
Data classification: Classification of data according to the degree of sensitivity, importance, and risks associated with it.
Improving data quality: establishing mechanisms to ensure the validity, accuracy and integrity of data.
Infrastructure development: Developing the technical infrastructure necessary to store and manage data.
Promoting data culture: Spreading awareness and training employees on the importance of data management and governance.

Data management and governance has become an inevitable necessity in the era of big data. It enhances data quality and security and improves decision-making processes. This requires integrated efforts at the levels of strategy, policies, infrastructure and organizational culture. These practices will help organizations make the most of their data and achieve their goals more efficiently