Data management and data processing are two processes that occur in many industries, but each has a very different purpose. Professionals who deal with this on a daily basis often use confusing terminology, making it sometimes difficult to understand and keep it all apart.

When you understand the purpose of different processes, the distinction between data management and data processing immediately becomes much clearer. Let's take a look at how these two concepts work in practice.

What is data management?

Data management involves collecting, preparing and storing data. We can describe these steps as data acquisition, data cleaning, data preservation and data documentation. In the data acquisition phase, you collect data from various sources. For effective data management, it is essential to know where the data came from.

Data cleansing is the process of removing or adjusting imperfect or incomplete data. This can help you reduce errors in the data and make it easier to use.

Data retention, with the linked data retention, refers to how long you keep data. Retention periods vary depending on the industry and type of data you collect.

Data documentation refers to creating metadata about the data. Metadata helps make the data easier to understand and use more effectively.

Data processing

Data processing is the conversion of raw data into useful information. Data must be processed and analyzed to be useful and can be reused in something more meaningful.

This could include calculating sales figures, analyzing customer data or understanding energy consumption. Although data management is a part of data processing, data management is not processing.

Data processing can also be referred to as "data analytics," which is a process that extracts useful information from data. This is often done using computer systems and software. Data analytics is, or can and should be, an important part at any organization. It enables companies to understand their customers and sales, improve marketing strategies and product development, and make better business decisions.

Data storage and data management

Another term sometimes confused with data management is data warehousing. Data warehousing is a form of data management. Data warehousing is the process of collecting, cleaning, organizing and storing large amounts of information from multiple sources to make it easily accessible when needed. This data can come from a single database or from multiple sources. Data warehousing is often used to store information about customers, products and equipment.


Data cleansing and enrichment

Data cleansing and data enrichment are important parts of data management. Data cleansing and data enrichment are important parts of data management. Data cleansing is the process of identifying and removing errors or incomplete information from data. Data enrichment is the process of adding missing information to data. Both processes are important parts of data management.


Data management and data processing are important parts of many industries. Data management involves the collection, preparation and storage of data. Data processing is the conversion of raw data into usable information. The two terms are often confused with each other because of their similar names. However, their purpose is quite different. It is important that you understand the difference because this will help you better understand the work of data managers and data processors.

Author: Tom Van den Eynden
Web Architect | Coordinator
Tom Van den Eynden

More insights

Cross-platform applicaties with React Native

Never before has developing native mobile applications been as accessible as it is today. At Codana, we do this by using the React Native, an open-source framework developed by Meta.

Author: Jinse Camps
Architect | Analyst
Jinse Camps

Laracon EU 2024

A fantastic learning experience to inspire and be inspired together with a lot of other Laravel passionate people! Something we couldn't miss and very much connect with the community. What a top event! Who will we see next editions? ­čś«

Author: Noah Gillard
PHP / Laravel Developer
Noah Gillard AI generated Face
laracon codana persoon

An efficient tourism data management system

A TDMS or Tourist Data Management System, is simply a platform that retrieves data from various sources, processes it internally either automatically or not, and offers this data back to external platforms.

Author: Tom Van den Eynden
Web Architect | Coordinator
Tom Van den Eynden

Tourism Data Management Systems

In dit artikel verkennen we wat een TDMS is, waarom het essentieel is voor de toerisme-industrie, en hoe technologie├źn zoals Laravel en ElasticSearch het verschil kunnen maken. 

Author: Tom Van den Eynden
Web Architect | Coordinator
Tom Van den Eynden

Test Driven Development - application to a project

TDD, or in full Test Driven Development, is an approach to development where we start from writing tests.

Author: Sarah Jehin
PHP developer
Sarah Jehin

Securing Laravel 101

In this blog post, we're gonna take a closer look at some common Laravel security mistakes.

Author: Robbe Reygel
PHP developer