Data lifecycle management, or DLM, helps companies manage the flow of business data. From creation to use, sharing, archiving, and deletion, this process follows the lifecycle of data. By accurately tracking data, companies have a foundation to protect sensitive information.
With this ability, companies get to apply security controls that keep their information out of the wrong hands. Because ‘lifecycle management” can have many definitions, DLM gets confused with other terms.
One such term is information lifecycle management. Although these two terms are often used interchangeably, some major differences exist.
Difference Between Information Lifecycle Management and Data Lifecycle Management
For its part, information lifecycle management takes a comprehensive approach to managing data. Not only does it handle the flow of data within information systems, but it also manages associated metadata. Management occurs from creation to destroying obsolete data.
On the other hand, enterprise data lifecycle management products manage general file attributes. These include the type, size, and age of data.
Descriptions of these processes represent another distinct difference between the two. In a nutshell, DLM refers to an automated policy-driven approach that takes data throughout its life.
However, there are nuances to the information lifecycle. While it also follows data life, the information lifecycle seeks to ensure that data is relevant and accurate.
Primary Goals of Data Lifecycle Management
Lifecycle management aims to secure and store all pieces of data, including file and database information.
Whether or not the data is useful, it gets stored in the database. At some point, the system applies logic and validation. When the data is no longer useful, the system either archives or purges it.
To achieve this organizing process, three main goals apply: confidentiality, availability, and integrity.
As the name implies, confidentiality protects information from third-party access. Additionally, this part of secure data lifecycle management prevents breaches.
Equally important to restricting access is ensuring the appropriate users can access data. Availability achieves this goal in the process by making data available whenever necessary.
One concern in the lifecycle process is whether stored data is accurate and useful. With this in mind, the management process must also check the integrity of data. Typically, this involves appropriately preserving and recording data.
Solutions for Data Lifecycle Management
While no specific standard exists. Each industry follows a general cycle of data life cycle management.
Phase One: Creation
During the data creation phase, either structured or unstructured data gets created. Generally, formats for data come as a PDF file, email, word processing document, database information, and images. Based on the company’s data security policy, security classifications occur.
Phase Two: Storage
After creating a data file, it gets stored. At this point, ensuring protection for the data with necessary security controls take place.
Phase Three: Security and Usage
Role-based security and data usage control user activity. For the most part, this involves viewing, processing, modifying, and saving data.
Phase Four: Sharing
Data sharing constantly occurs between employees and customers. Therefore, secure data lifecycle management should continuously monitor new instances of sensitive data stores.
Phase Five: Archive
With archival solutions, data lifecycle management ensures the protection and availability of inactive data. For each industry, retention-specific stipulations guide companies on how to remain compliant.
Phase Six: Destroy
At some point, the volume of archived data grows beyond storage capacity. While companies may want to keep data in perpetuity, doing so is not possible. When this happens, they must review storage cost and compliance issues. This includes securely deleting files to prevent leaks.
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