Bring data-driven expectations and trusted data closer with Data Government
Posted: Tue Jan 21, 2025 4:46 am
Discover why achieving reliable data with Data Government is the first step to closing the gap with your business's data-driven expectations.
Becoming a data-driven company is today an imperative to obtain competitive advantages and respond to the demands of clients and consumers. The generation of reliable and quality data in a secure environment is an unavoidable requirement to achieve this: What is the role of data governance in this task? How important is it to organizations and how do they perceive the state of information?
HubSpot BLOG
74 % of organizations believe that active use of data by senior management roles is critical to building data trust.
Source: IDC
3 keys to data governance for successful businesses
Data governance consists of generating a framework or overseas chinese in canada data that supports the management of data used by organizations in the execution of operations. It is composed of standards and policies that ensure the reliability, usefulness and security of data .
Good governance is a fundamental requirement to meet the key objectives and demands of organizations, from cost optimization, offering an excellent customer experience and expanding revenue. Among the main actions that can be carried out to meet these goals are:
Align data governance with business outcomes : Business strategy and business priorities are the foundation that guides data governance efforts. If data governance revolves around data governance as an end in itself without considering the broader framework of business priorities and objectives, the results obtained will not be as desired.
Business value and the goals to be achieved must be placed at the center of the data governance plan by establishing clear and precise business metrics.
Implement trust-based data governance : The information circulating in organizations does not have the same level of privacy or importance. For this reason, it is important to establish a plan based on the different data sources and their degree of reliability for better decision-making.
Foster cultural change and collaboration : Data governance strategies should focus on the interactions of those who process and use data on a daily basis, fostering innovation and knowledge sharing.
A starting point is to understand the perception that different sectors of the organization have about the importance of data and the weak points that need to be corrected.
Data management and governance for data-first companies
Reliable data: a requirement for data-driven decision making
Intelligent data management is expected within companies, but this is not what usually happens. According to a study by IDC , having a solid knowledge of the lineage, quality and location of information are the most valued issues, but at the same time, performance and daily operations do not meet these expectations due to poor management in locating and identifying the best data.
Organizations must bridge the gap between data-driven expectations and the availability of quality information by building trust in data, ensuring transparency, and seeking to reduce the gap between data producers and consumers to achieve the best results.
Becoming a data-driven company is today an imperative to obtain competitive advantages and respond to the demands of clients and consumers. The generation of reliable and quality data in a secure environment is an unavoidable requirement to achieve this: What is the role of data governance in this task? How important is it to organizations and how do they perceive the state of information?
HubSpot BLOG
74 % of organizations believe that active use of data by senior management roles is critical to building data trust.
Source: IDC
3 keys to data governance for successful businesses
Data governance consists of generating a framework or overseas chinese in canada data that supports the management of data used by organizations in the execution of operations. It is composed of standards and policies that ensure the reliability, usefulness and security of data .
Good governance is a fundamental requirement to meet the key objectives and demands of organizations, from cost optimization, offering an excellent customer experience and expanding revenue. Among the main actions that can be carried out to meet these goals are:
Align data governance with business outcomes : Business strategy and business priorities are the foundation that guides data governance efforts. If data governance revolves around data governance as an end in itself without considering the broader framework of business priorities and objectives, the results obtained will not be as desired.
Business value and the goals to be achieved must be placed at the center of the data governance plan by establishing clear and precise business metrics.
Implement trust-based data governance : The information circulating in organizations does not have the same level of privacy or importance. For this reason, it is important to establish a plan based on the different data sources and their degree of reliability for better decision-making.
Foster cultural change and collaboration : Data governance strategies should focus on the interactions of those who process and use data on a daily basis, fostering innovation and knowledge sharing.
A starting point is to understand the perception that different sectors of the organization have about the importance of data and the weak points that need to be corrected.
Data management and governance for data-first companies
Reliable data: a requirement for data-driven decision making
Intelligent data management is expected within companies, but this is not what usually happens. According to a study by IDC , having a solid knowledge of the lineage, quality and location of information are the most valued issues, but at the same time, performance and daily operations do not meet these expectations due to poor management in locating and identifying the best data.
Organizations must bridge the gap between data-driven expectations and the availability of quality information by building trust in data, ensuring transparency, and seeking to reduce the gap between data producers and consumers to achieve the best results.