What is data lifecycle management (DLCM)

Data lifecycle management (DLCM) is the process of managing data throughout its entire lifecycle—from creation to destruction.

This process ensures data security, compliance with regulations, and operational efficiency. Organizations can avoid storage inefficiencies, improve data protection, and meet regulatory requirements such as GDPR by responsibly managing data.

How DLCM works: Phases of the data lifecycle

There are five main phases in the data lifecycle, all of which are improved by DLCM:

1. Data creation and collection

Organizations collect data from multiple sources, including IoT devices and internal processes. Data cleaning may then be required to ensure usability and coherence.

2. Data storage

Efficient data storage is essential to reduce costs and enable disaster recovery. DLCM optimizes data storage systems by removing redundant data and backing up critical data.

3. Data usage

Data is most valuable when it drives decisions. During this phase, DLCM ensures sensitive information remains secure during analysis, processing, and sharing.

4. Archiving data

Once data becomes inactive, it is archived. Proper archiving reduces storage costs while making sure data can be retrieved for information compliance (such as FOI requests) or other business purposes.

5. Data destruction

When data has reached the end of its lifecycle, it must be destroyed securely. Failure to do so can result in data breaches or non-compliance with regulations like GDPR.

Why DLCM matters

With the exponential increase in data volume from sources such as Internet of Things (IoT) devices, the challenge of managing and securing data also rises. Meanwhile, the strengthening of data protection regulations, such as GDPR and CCPA, demands a rigorous approach to data handling.

A data lifecycle management (DLCM) strategy ensures your organization can efficiently manage large volumes of data, reduce risks associated with data breaches, and meet compliance obligations.

Distinction between DLCM and information lifecycle management (ILM)

Both DLCM and information lifecycle management (ILM) involve managing data. However, ILM focuses on enforcing data governance policies, while DLCM emphasizes the operational aspects of data handling and the practicalities of the process.

Key components of DLCM

• Data creation and collection: This is the initial phase, where data is generated from various sources such as business operations and IoT devices. Ensuring data accuracy and relevance is crucial during this stage
• Data cleaning: Depending on how well data has been sourced, it may require additional sorting and formatting, to ensure it is interpretable when required
• Data storage: Data must be stored securely and cost-effectively. DLCM involves implementing strategies that reduce storage costs and prevent data redundancy while ensuring proper backup for disaster recovery
• Data usage: At this stage, data is used to drive business decisions. Ensuring sensitive information such as payroll data remains secure during processing and sharing is critical
• Archiving data: As data becomes less frequently accessed, it is moved into archival storage. Setting good retention policies ensures long-term storage compliance and lowers the cost of keeping inactive data
• Data destruction: When data is no longer needed, secure destruction is necessary to comply with legal requirements and prevent unauthorized recovery

The importance of DLCM

There are three major benefits to instituting DLCM: compliance, procedural optimization, and cost reduction.

Data security and compliance

A solid DLCM strategy safeguards sensitive information and maintains compliance with data protection regulations, including GDPR. Implementing secure measures across all phases of data management reduces the risk of data breaches and non-compliance penalties.

Managing large volumes of data

As the volume of data increases, particularly from IoT devices, organizations need DLCM strategies to manage data efficiently. With a comprehensive DLCM approach, companies can streamline data management processes to easily organize and access essential data when needed.

Cost efficiency

One of the primary benefits of DLCM is cost efficiency. By managing data effectively, organizations can eliminate redundant, obsolete, or trivial (ROT) data. This will reduce storage costs and aid disaster recovery plans.

Key benefits of a DLCM Strategy

A good DLCM strategy conveys four additional benefits:

• Backup and disaster recovery: DLCM ensures proper data backup, making it easier to implement disaster recovery plans. Such backup potential protects your organization from data loss due to hardware failure or cyberattacks
• Data sharing and accessibility: A well-executed DLCM strategy improves data sharing across your organization. Better collaboration is enabled, while data remains secure and only accessible to authorized users
• Compliance with data protection regulations: Complying with regulations such as GDPR can be daunting. DLCM helps simplify compliance by ensuring sensitive information is managed appropriately. It also enables archiving according to legal standards, and secure data destruction when no longer required
• Managing different data types: DLCM helps companies manage various data types, including structured, unstructured, and IoT-generated data. All data is appropriately processed and stored according to its importance and sensitivity

Best practices for implementing DLCM

Here are five recommendations for properly implementing DLCM:

Data classification

Organizations should categorize data based on its sensitivity and importance. This defines what data must be stored long-term, what can be archived, and what should be destroyed.

Automating DLCM processes

Automation tools can streamline the management of large data volumes. Automated workflows reduce the manual effort required to manage data, and the time taken to retrieve it.

Disaster recovery and redundancy

A comprehensive DLCM strategy includes provisions for disaster recovery and redundancy. With the proper backup strategies, critical data is available to organizations during crises.

Data security and privacy

At every phase of the data lifecycle, strong security controls must be in place to protect sensitive data from unauthorized access or breaches.

Regular monitoring and auditing

Continuous monitoring and auditing ensure data management practices align with the organization’s DLCM strategy and comply with legal and regulatory standards.

Challenges with DLCM

There are significant challenges in implementing a DLCM approach. As data volume expands, organizations face challenges in storing, processing, and analyzing it. IoT data adds to the complexity of managing large volumes of data.

Organizations must also adhere to various global data protection regulations. Ensuring compliance with laws like GDPR can be difficult, particularly when handling sensitive information across multiple jurisdictions.

Striking a balance between reducing storage costs and ensuring adequate redundancy for disaster recovery can be tricky for some organizations. Ensuring sensitive data is protected throughout its lifecycle remains an ongoing challenge as well, particularly when faced with advanced cybersecurity threats.

The takeaway

Implementing an effective Data Lifecycle Management (DLCM) strategy is beneficial for any organization. It increases data security, ensures regulatory compliance, and marshals large volumes of data efficiently. A comprehensive DLCM approach can help reduce costs, ensure data accessibility, and protect sensitive information throughout its lifecycle.

Explore how Deel IT can support your organization in managing global workforce data with secure, efficient, and compliant data lifecycle management solutions. Request a demo today.