Businesses grow and increasingly handle more and more data. The trend is upward and, as we can imagine, it is increasingly complex to deal with the data, analyze it, process it and even store it.

Data lifecycle management is the information management process that follows the data from the moment it is created and stored for the first time, until the moment it is archived or destroyed when it is no longer useful. It is a concept analogous to the software lifecycle, which deals with it in all phases of its development, from initial conception and design, to future updates and patches.

What are the phases of data lifecycle management?

Data lifecycle management is typically divided into three distinct stages that span data throughout its life. These three stages are to create, keep and withdraw, and they are explained like this. First, we have the creation and acquisition of the data.

Then we have to consider the retention and protection of these, and then we have to look at their withdrawal. Within these "categories" there are other small phases such as data collection, data protection and data destruction when necessary. Let's see it in detail:

Data acquisition and creation. This first stage refers to when data is created or transferred to the system, which involves creating files, classifying them for easy retrieval, and determining access controls.

Data retention and protection. Once the data is acquired, it must be stored and preserved. It is about guaranteeing data redundancy through backup, security by using protection solutions such as encryption and physical security of the server. In addition to accuracy, continually validating and auditing files to ensure the accuracy of the data.

Data withdrawal in that you have to get rid of them when they are not useful. This implies either archiving the data or its destruction because it is not operational.

Benefits of data lifecycle management

Companies that apply data lifecycle management and follow good management of the information generate in their daily operations, have many immediate advantages, such as:

- A satisfactory data lifecycle management strategy allows businesses to meet their requirements and goals. It guarantees a good data protection infrastructure, which helps your security in case of risk or emergency. This applies to both internal information and customer data the company works with.

- The extraction and maintenance of information throughout the data lifecycle allows you to always have up-to-date values.

- Availability for all users of clean, useful and accurate data. This increases the agility and efficiency of business processes.

Best practices for applying data lifecycle management
Here are some of the most important things to keep in mind when establishing a data lifecycle management policy:

- Create and define the types of data for each type of file.

- Use a consistent naming scheme that applies to all data in your organization. By ensuring that everything is properly named, the data is easier to manage and access.

- Save the new data through a backup plan, which guarantees redundancy and protects us from possible data loss due to accidents, disasters or ransomware.

- Consider implementing a file sharing and synchronization service.

- Archiving your data is recommended if it is rarely used, or if it simply needs to be retained to comply with regulations.

- You need to clear the space by destroying the data when it reaches the end of its useful life. A proper destruction or removal policy is critical to ensure that nothing that needs to be archived for later reference is accidentally removed.

Businesses increasingly need more space in which to store information and it is essential that it is secure for the most critical data.