Fundamental pillars of data governance for effective management
Posted: Wed Jan 22, 2025 7:10 am
Ensuring data security and confidentiality is crucial for business continuity. Learn the fundamental pillars of data governance.
Sep 5, 2022
Data is now the primary input for organizations and its role is becoming more critical as privacy regulations and compliance standards emerge. But there are also greater requirements for accuracy in analysis to optimize operations and decision-making.
What is data governance and why is its proper vnpay database relevant in organizations? What are the essential factors for implementing it effectively?
30% of total company time is spent on tasks without added value due to poor data quality and availability.
Source: McKinsey
What is data governance?
Data governance is the process of managing the availability, integrity, and security of data in enterprise systems based on internal standards and policies. Effective data governance ensures consistent, reliable data and proper use of data .
Otherwise, inconsistencies between different systems in a company may not be resolved, which complicates the integration and centralization of information and can lead to errors in precision in analysis and lack of corrections. The ultimate goal is to generate the highest possible performance from data, detecting critical opportunities to take advantage of the available information assets and avoid the risks of their exposure.
Data the power to be extraordinary
The data governance framework and its fundamental pillars
Defining the structure of a data governance program requires a framework of rules and processes for collecting, storing, and using information. This facilitates the optimization and scaling of operations, democratization of data access, and ensuring that data is used by different users according to established standards. It also ensures that data is reliably transformed and delivered across all of the organization's cloud and on-premise deployments and analytics.
There are four key factors to carrying out a data governance program:
Human resources: People define the technology requirements, procedures, and drive data governance outcomes. Having their commitment and knowledge of their responsibilities, along with the necessary skills, is critical to aligning their work with that of the organization and its standards.
Processes: These allow people to confirm that data is formally managed across the enterprise, ensuring that critical operations are based on reliable data. For this reason, appropriate rule and objective definitions and modernized processes are necessary to achieve the expected results.
Contributors: These are the IT business experts, business leaders and administrators, analysts and systems architects who execute the processes and provide the framework within which to perform operational tasks.
Technology: Includes the platforms, tools, and expertise needed to enable a robust data governance process. Data profiling, lineage, and metadata tools are critical to automating and scaling data governance processes and accelerating time to value.
Sep 5, 2022
Data is now the primary input for organizations and its role is becoming more critical as privacy regulations and compliance standards emerge. But there are also greater requirements for accuracy in analysis to optimize operations and decision-making.
What is data governance and why is its proper vnpay database relevant in organizations? What are the essential factors for implementing it effectively?
30% of total company time is spent on tasks without added value due to poor data quality and availability.
Source: McKinsey
What is data governance?
Data governance is the process of managing the availability, integrity, and security of data in enterprise systems based on internal standards and policies. Effective data governance ensures consistent, reliable data and proper use of data .
Otherwise, inconsistencies between different systems in a company may not be resolved, which complicates the integration and centralization of information and can lead to errors in precision in analysis and lack of corrections. The ultimate goal is to generate the highest possible performance from data, detecting critical opportunities to take advantage of the available information assets and avoid the risks of their exposure.
Data the power to be extraordinary
The data governance framework and its fundamental pillars
Defining the structure of a data governance program requires a framework of rules and processes for collecting, storing, and using information. This facilitates the optimization and scaling of operations, democratization of data access, and ensuring that data is used by different users according to established standards. It also ensures that data is reliably transformed and delivered across all of the organization's cloud and on-premise deployments and analytics.
There are four key factors to carrying out a data governance program:
Human resources: People define the technology requirements, procedures, and drive data governance outcomes. Having their commitment and knowledge of their responsibilities, along with the necessary skills, is critical to aligning their work with that of the organization and its standards.
Processes: These allow people to confirm that data is formally managed across the enterprise, ensuring that critical operations are based on reliable data. For this reason, appropriate rule and objective definitions and modernized processes are necessary to achieve the expected results.
Contributors: These are the IT business experts, business leaders and administrators, analysts and systems architects who execute the processes and provide the framework within which to perform operational tasks.
Technology: Includes the platforms, tools, and expertise needed to enable a robust data governance process. Data profiling, lineage, and metadata tools are critical to automating and scaling data governance processes and accelerating time to value.