Characteristics necessary for good quality information
Posted: Tue Jan 21, 2025 10:13 am
Discover the basic concepts that help define the concept of information quality and take note of some examples of the different attributes of data quality.
Remembering basic concepts is often useful, and this is especially interesting when it comes to data quality . This is probably one of the main aspects that every company should consider before starting any data analytics project.
At first glance, the concept may seem obvious. To have good information quality, data must meet certain criteria that are recognized by everyone, such as accuracy, timeliness, relevance and comprehensibility . However, there are slightly different definitions for each person. So what is quality information?
Every year, 25-30 % of data becomes inaccurate , leading to less rich people database sales and marketing campaigns.
Source: Webincare
What are the attributes of information quality?
Below are the key attributes that must be present to speak of good information quality. There are 8 of them and they are usually written in such a way that the first letter of each concept in English forms the acronym ACCURATE .
Accurate: In practice, data used for different purposes requires different levels of accuracy. Problems related to inaccuracy occur constantly in business intelligence systems. It is a well-known information quality problem, ranging from system design to implementation and maintenance.
Complete: Incomplete information can lead to poor decision-making. The problem is that complete information for one person may be incomplete for another, so it is necessary to reach an agreement on the needs of each user so that everyone has the required data.
Compatible: The quality of information also consists of how well it can be combined with other information. This often occurs when the information involves several systems working together, in a data integration, for example. In these cases, it is important to have an appropriate information architecture with a dynamic structure that can grow with the needs of the client.
Remembering basic concepts is often useful, and this is especially interesting when it comes to data quality . This is probably one of the main aspects that every company should consider before starting any data analytics project.
At first glance, the concept may seem obvious. To have good information quality, data must meet certain criteria that are recognized by everyone, such as accuracy, timeliness, relevance and comprehensibility . However, there are slightly different definitions for each person. So what is quality information?
Every year, 25-30 % of data becomes inaccurate , leading to less rich people database sales and marketing campaigns.
Source: Webincare
What are the attributes of information quality?
Below are the key attributes that must be present to speak of good information quality. There are 8 of them and they are usually written in such a way that the first letter of each concept in English forms the acronym ACCURATE .
Accurate: In practice, data used for different purposes requires different levels of accuracy. Problems related to inaccuracy occur constantly in business intelligence systems. It is a well-known information quality problem, ranging from system design to implementation and maintenance.
Complete: Incomplete information can lead to poor decision-making. The problem is that complete information for one person may be incomplete for another, so it is necessary to reach an agreement on the needs of each user so that everyone has the required data.
Compatible: The quality of information also consists of how well it can be combined with other information. This often occurs when the information involves several systems working together, in a data integration, for example. In these cases, it is important to have an appropriate information architecture with a dynamic structure that can grow with the needs of the client.