Is Your Data Lifecycle Management (DLM) Effective?

Even if you’ve never heard of Data Lifecycle Management (DLM), you’re practicing it in one form or another. So, if you’re already doing it, why do you need a new name for it? Because just like any aspect of your business, it needs to be structured and have its own Policies & Procedures (P&P).

Your data is the life blood of your business, so it’s one of the most valuable assets you have. Managing this data throughout its lifecycle can be challenging. DLM refers to the set of Policies & Procedures that govern the handling, storage, and eventual disposal of data.

Like most businesses, you generate and store vast amounts of data. As this happens, the importance of effective DLM becomes more critical. Navigating the challenges of data lifecycle management requires a comprehensive approach. One that balances security, compliance, and operational efficiency.

Why is data lifecycle management important?

It’s very important, but let’s start with what it is and what it does: Data lifecycle management involves the governance of data. It starts from its creation to continues to its eventual disposal. The lifecycle includes several stages:

Data creation

Storage

Use

Sharing

Archiving

Deletion

Every stage of DLM presents its own set of challenges. Mismanagement at any stage can lead to cybersecurity risks as well as regulatory non-compliance and increased operational costs. Implementing a robust DLM strategy ensures proper data handling at every stage. This maximizes its value while minimizing risks.

There are three main reasons why effective DLM is crucial:

1) It helps ensure data security. As data moves through its lifecycle, it is exposed to various threats. These include unauthorized access, data breaches, and more. A well-implemented DLM strategy includes security measures that protect data at every stage.

2) DLM helps businesses follow regulatory requirements. Many industries are subject to strict data protection laws. Failure to comply can result in significant fines and reputational damage.

3) It improves operational efficiency. By managing data effectively, businesses can reduce storage costs as well as streamline operations and ensure that data is available when needed.
What is data lifecycle management?

Simply put, Data Lifecycle Management (DLM) is an approach to managing data throughout its lifecycle, from data entry to data destruction.

Let’s establish one thing first: Every aspect of maneuvering in any arena of the Cyber World is going to have challenges. DLM has several.

1) Volume and Variety

The sheer volume and variety of data your business generates constitutes one of the primary challenges of DLM. With the proliferation of digital devices and platforms, companies are collecting more data than ever before. It includes everything from structured databases to unstructured text, images, and videos.

How to Manage Large Volumes of Data

As you may guess, the massive volume of data presents an ongoing storage challenge. Businesses must invest in scalable storage solutions that can handle growth without compromising performance. As data volumes increase, the resources needed to manage and process this data also grow.

How to Best Manage Diverse Data Types

We generate and store many forms of data, and each type requires different handling and storage methods. Databases and other examples of highly structured data are easier to manage. Unstructured data, such as emails and social media posts, presents more challenges. A comprehensive DLM strategy must account for the different types of data as well as ensure proper data management for each type.

2) Data Cybersecurity and Privacy

Data protection is a critical aspect of DLM. As data moves through its lifecycle, it is vulnerable to a variety of security threats, including data breaches, unauthorized access, and cyberattacks. Ensuring data privacy and security is not only a best practice but often a legal need for maintaining regulatory compliance.

Enable Robust Security Measures

Businesses must enforce robust security measures to protect data throughout its lifecycle, including encryption, access controls, and regular security audits. Additionally, businesses should adopt a proactive approach to threat detection and response.

Ensure Compliance with Privacy Regulations

General and industry-specific regulatory agencies have imposed strict requirements on how businesses handle personal data. Compliance with these regulations is often non-negotiable. Businesses must ensure that their DLM strategies have provisions for data privacy. This includes obtaining consent for data collection and using data minimization practices as well as ensuring that data is securely deleted when no longer needed.

3) Maintain Data Quality and Integrity

For effective DLM, maintaining data quality and integrity is essential. Poor data quality can lead to several issues, including:

Inaccurate analyses

Poor business decisions

Wasted resources

Making sure that your data remains accurate and reliable throughout its lifecycle is a challenge that must be met.

Enact and Enforce Data Quality Controls

For the continuing health of your enterprise, you must enforce data quality controls at every stage of the data lifecycle. This includes validating data at the point of entry as well as regularly auditing data for accuracy, and correcting errors promptly.

Prevent Data Corruption

Data corruption happens at any stage of the data lifecycle, so steps must be taken to prevent it. Businesses should use reliable storage solutions as well as regularly back up data. Adopting error-checking and correction helps resolve issues before they impact data integrity.

4) Retaining and Deleting Data

Only you can decide how long to keep data and when to delete it, but it’s a critical aspect of DLM. Unnecessarily holding onto data for too long can increase storage costs as well as expose businesses to security risks. On the flip side, deleting data prematurely can lead to compliance issues. It can also mean the loss of valuable information.

Establish Data Retention Policies

Establishing clear data retention policies is a key component of DLM. These policies should outline how long to keep different types of data. Base them on legal, regulatory, and business requirements.

Data Deletion Security

The need for security doesn’t end when you decide it’s time to delete data. To prevent unauthorized access, use appropriate data destruction methods and ensure you delete all copies.

5) Accessibility and Availability

Your must be accessible when needed, and this can be another challenge of DLM. As data moves through its lifecycle, users may have archived it or moved it to different storage locations or perhaps deleted it altogether. Businesses must ensure that data remains accessible to authorized users throughout its lifecycle.

The Balance Accessibility with Cybersecurity

Enforcing access controls will maintain the balance of data accessibility and security by using MFA and role-based access.

Data Availability During Disruptions

Another factor of major importance is must data availability during disruptions like cyberattacks, natural disasters, or hardware failures. This highlights the critical need for a solid backup and disaster recovery  plan.