achieve and maintain data quality

Obtaining the quality of the data is a great achievement, undoubtedly, but this does not mean that we have reached a definitive goal, much less that we can enjoy it sine die. Conversely, Its guarantee of validity is closely related to the processes that are carried out throughout the data quality flow, which means it is a constant procedure.

The implementation of the quality processes itself is carried out in a scalable way, which means that it is going to expand to other areas of the corporation gradually, among other supports, with the collaboration of a person in charge of the quality of the information. The figure"Figure" is a term that is used in various contexts, From art to anatomy. In the artistic field, refers to the representation of human or animal forms in sculptures and paintings. In anatomy, designates the shape and structure of the body. What's more, in mathematics, "figure" it is related to geometric shapes. Its versatility makes it a fundamental concept in multiple disciplines.... of the appointment manager, that coordinates the procedure with a double vision, technical and functional.

At the same time, the quality of the data is the result of the efforts of different professionals working together (quality developer, business analyst or executives), without forgetting that they must also have the staff involvement design, streamline quality processes and, in conclusion, guarantee its realization.

Expand scalability: objective of the data quality project

By implementing data quality processes to new departments of the company, scalability expansion is achieved, In the first instance, implication of the parts of the organization that are not yet linked to the project.

Simply, it is about involving human resources from different areas, making them participate in the Achieved achievements in other departments and advantage derived from it, whether economical or time-saving, Let's say.

Staff participation is a key asset to achieve our goal: put into practice the quality processes suitable for our company medium and long term, as well as its maintenance thanks, Inter alia, to good practices.

In reality, the concept of scalability is key to understanding the dynamics of data quality processes, that start from a niche department to finally distribute the improvements to the rest of the departments, based on three main items:

• The need to make staff aware of the new areas.

• The relevance of providing them with tools to assume it.

• Coordination carried out by the data administrator.

This is how scalability expands, through these three fundamental items, and always in parallel with a permanent update of the projects implemented. As a final consequence, a unique ecosystem will be obtained that will have achieved the data federation through seamless integration thanks to quality apps, as ETL processes or other online applications.

The need for constant updating

Once the quality procedure has been implemented throughout the company, indeed, its maintenance will be a permanent objective, even though the initial effort will be the most important. This is exactly why, so as not to spoil it, maintaining data quality is vital.

It should not be surprising that the very concept of information quality depends on its use, In other words, of their ability to meet needs. Therefore, By maintaining that quality we are not only verifying the compliance with the rulessince they are also configured new rules correction based on established rules.

We bear in mind that quality processes are processes of constant improvement that impact data and processes, ultimately looking for a optimal operating efficiency. Finally, achieving and maintaining data quality will be synonymous with ensuring the good state of the data to maximize its use.

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