What are the four main processes of data management?
Posted: Sat Apr 19, 2025 9:33 am
Data management encompasses a whole set of tasks and procedures essential to ensuring the quality and integrity of the information collected. However, data management can be summarized in four main stages:
data collection : data is gathered from different sources regardless of location or format, whether the data is structured or unstructured.
data processing : all data is processed in order to be structured and analyzed to be able to extract useful information.
data validation : we ensure the accuracy and reliability of the data so that subsequent decisions are based on solid foundations.
Data access : Access is granted to the data stored in the system. This includes the methods, permissions, protocols, and data management technologies that allow authorized users to retrieve and use the desired information.
To start
What are the three india phone number lead types of data to manage?
The types of data to be managed can be classified into three categories:
Structured data : This data is organized according to predefined formats. This could be a date (DD/MM/YY), a purchase amount in euros, or an item reference. Structured data is very varied in both its source and format. However, they have in common that they can be easily arranged in a table for sorting, comparison, analysis, etc. This allows artificial intelligence (AI) algorithms to quickly detect anomalies or trends among all this data.
Unstructured data : Examples include images or videos from a social media post, or the free field in a customer feedback form. Unstructured data doesn't follow a predefined format and is therefore more complex to process. It's difficult to search for specific information in an audio file or video. However, unstructured data often represents 80% of a company's usable data. To transform their unstructured data into structured data, companies must first implement structuring, deduplication, and cleansing steps.
Semi-structured data : This is information that, although it does not follow a strictly organized format like structured data, nevertheless has a partial organization that allows it to be analyzed more flexibly while maintaining a certain structure. It generally uses tags or markers to define elements and attributes that can be used to partially organize it. For example, XML, JSON files, or emails are semi-structured data.
data collection : data is gathered from different sources regardless of location or format, whether the data is structured or unstructured.
data processing : all data is processed in order to be structured and analyzed to be able to extract useful information.
data validation : we ensure the accuracy and reliability of the data so that subsequent decisions are based on solid foundations.
Data access : Access is granted to the data stored in the system. This includes the methods, permissions, protocols, and data management technologies that allow authorized users to retrieve and use the desired information.
To start
What are the three india phone number lead types of data to manage?
The types of data to be managed can be classified into three categories:
Structured data : This data is organized according to predefined formats. This could be a date (DD/MM/YY), a purchase amount in euros, or an item reference. Structured data is very varied in both its source and format. However, they have in common that they can be easily arranged in a table for sorting, comparison, analysis, etc. This allows artificial intelligence (AI) algorithms to quickly detect anomalies or trends among all this data.
Unstructured data : Examples include images or videos from a social media post, or the free field in a customer feedback form. Unstructured data doesn't follow a predefined format and is therefore more complex to process. It's difficult to search for specific information in an audio file or video. However, unstructured data often represents 80% of a company's usable data. To transform their unstructured data into structured data, companies must first implement structuring, deduplication, and cleansing steps.
Semi-structured data : This is information that, although it does not follow a strictly organized format like structured data, nevertheless has a partial organization that allows it to be analyzed more flexibly while maintaining a certain structure. It generally uses tags or markers to define elements and attributes that can be used to partially organize it. For example, XML, JSON files, or emails are semi-structured data.