K
Kathleen Martin
Guest
Many leaders would be surprised to discover that their organization is lacking in data maturity. They might see that they have data professionals on staff and that different data resources are being used, and they could think that the organization is getting a lot of value from the data being collected, but this is not always the case. This is why a data maturity assessment can be so important.
In a basic sense, data maturity is a measure of an organization's ability to use data, along with how well the organization leverages those capabilities. When an organization is data mature, it means that it can deploy its data resources to achieve a range of goals. In many cases, this not only means making data-driven decisions but also making data resources more accessible throughout the organization.
What Is A Data Maturity Assessment?
A data maturity assessment (DMA) is a framework for determining how data mature an organization is. There are different models for performing a DMA, but most of them will define different stages of data maturity to represent an organization's data capabilities and the effectiveness with which the organization deploys those capabilities.
In essence, a DMA is like an audit of an organization's data resources, data governance practices and the processes that go into the use of data at the organization. The purpose is to define the data maturity of the organization while also developing plans to advance that data maturity.
Identifying a lack of data maturity is the first step in making an organization more data-driven. But what are some of the issues that might come up during a data maturity assessment?
Unclear Goals Or Vision
One of the most common issues uncovered during a DMA is the lack of a data strategy or a strategy that does not have clear goals. Data should be seen as a guiding force in the organization, but you need to have goals and a clear vision of where you want the data to take you.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/04/12/data-maturity-finding-a-path-to-a-data-driven-future/?sh=14cc369a7d16
In a basic sense, data maturity is a measure of an organization's ability to use data, along with how well the organization leverages those capabilities. When an organization is data mature, it means that it can deploy its data resources to achieve a range of goals. In many cases, this not only means making data-driven decisions but also making data resources more accessible throughout the organization.
What Is A Data Maturity Assessment?
A data maturity assessment (DMA) is a framework for determining how data mature an organization is. There are different models for performing a DMA, but most of them will define different stages of data maturity to represent an organization's data capabilities and the effectiveness with which the organization deploys those capabilities.
In essence, a DMA is like an audit of an organization's data resources, data governance practices and the processes that go into the use of data at the organization. The purpose is to define the data maturity of the organization while also developing plans to advance that data maturity.
Identifying a lack of data maturity is the first step in making an organization more data-driven. But what are some of the issues that might come up during a data maturity assessment?
Unclear Goals Or Vision
One of the most common issues uncovered during a DMA is the lack of a data strategy or a strategy that does not have clear goals. Data should be seen as a guiding force in the organization, but you need to have goals and a clear vision of where you want the data to take you.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/04/12/data-maturity-finding-a-path-to-a-data-driven-future/?sh=14cc369a7d16
