From Creation to Deletion: How Data Life Cycle Management Protects Your Success

Are you overwhelmed by the size and complexity of your data storage? Are you worried about the damage that could be caused by essential files that your team did not adequately dispose? Data management is one of the most critical processes to build into your workflow, but it can be challenging to handle on your own.

Data life cycle management doesn’t have to be stressful. Like any strategy, formulating your approach requires understanding what your goals are for your data strategy. We want to help break this down into more manageable steps. If you are an SMB in Northeast Pennsylvania, come to the area’s leading experts in data management strategy! Call us today and discuss how we can help you improve your processes.

What Is Data Lifecycle Management?

Data Lifecycle Management (DLM) is the approach to how data is created, processed, and deleted in your system. Understanding how your data moves through tasks will give you a more thoughtful approach to the data structure, enhancing data security, hygiene, and availability.

A good DLM strategy views your data management with priorities of protecting data and preparing for the worst-case scenarios of disaster recovery and data theft. Having this approach to data management systematized is suitable for your business in multiple ways. So, what does data lifecycle management look like?

The Lifecycle of Data

From the moment data is created to when and if it ever gets deleted, it must be protected at every step. Let’s take a detailed look at each point of the data lifecycle.

Data Creation

The data creation step is critical to your business and should be carefully structured for future steps in the data lifetime. Gathering and processing data within your system is often part of the same step. From data mining to data collection, ensuring ethical and structured processes will simplify future data management steps.

De-personalization, as you collect data, is an essential step. Ensuring data integrity as you gather and process raw data is the first thing to consider in your data management strategy.

Data Storage

When storing data, you have many regulatory and governmental considerations to make. Data governance policies will provide you with better regulation practices, improving your data security and data privacy practices as you are more conscious of how your data access will be monitored.

Data Sharing and Usage

Two coworkers examine a data structure on their desktop as they discuss their strategy

How you utilize your organization’s data might be second nature, but having a new perspective and approach can revitalize and enhance your approach. A thoughtful data strategy enables your business plan by providing a higher-level approach to your business data, pushing you towards becoming an efficient data-driven organization.

Bring your data analysts and IT providers to discuss how to structure a unified data strategy across the business more efficiently. Their data literacy is a strategic asset to your data lifecycle management as they generate business value from this data.

Archival and Data Protection

When your data has been used for immediate business objectives, it is often ignored as your workers move on. However, archiving in a data warehouse will provide a few benefits. Some data is critical to maintaining firm business continuity – tracking the work done for a client ensures no wasted time re-doing the same projects.

Your data life cycle management strategy should specify how long you store and maintain data. Tracking archived data should include deleting excess copies from the system to prevent loss and excess storage costs.

Deletion and Removal

Data is not permanent and shouldn’t be treated as such. But assuming that clicking ‘delete data’ is the end of the file would be a mistake. Many systems have automatic archives or backups that should be monitored and regularly purged of data that has outlived its use. This doesn’t just minimize storage costs. It also likely keeps you compliant with necessary consumer protection regulations.

How Will Data Lifecycle Management Benefit My Business?

You don’t want to make broad changes to your workflow without a good reason. Data lifecycle management has multiple benefits to consider, including:

  • Enhancing Your Process: Data is the fuel of most modern businesses. DLM pushes employees to be more considerate and thoughtful about interacting with sensitive data. This strategy also provides more points to check for data corruption and think about data strategies and processing.
  • Lowering Costs: Messy data management can cost valuable time. Consider how many work hours are wasted on data deletion, recovery, and searching for the file you need. Additionally, more efficient data management simplifies your data curation and backup processes.
  • Making Data More Usable: A fully actuated DLM strategy can utilize metadata and data policies to ensure that a team can share data more easily when needed and that access is restricted when it isn’t.
  • Adhering to Regulations: Every industry has its own data management regulations and rules. A proper DLM strategy can ensure that every step of your business process complies with regulations as strict as HIPAA. This compliance enhances customer trust and data security in one fell swoop!

Structuring your data processing workflow around DLM will enhance your business in many ways. This more thoughtful approach will help you manage data more effectively, which is critical in our data-driven culture. Having these meaningful insights into how you use data is also essential for future-proofing your business continuity and making informed decisions regarding AI and machine learning tools.

See Your Data Lifecycle Management with New Eyes!

Data moves through businesses alongside the work that involves it. It is born or adopted by clients and employees. Data lives within your system and moves around within it. Then, it is either archived for future use or deleted to keep your system clean. This complicated process can be a lot to deal with, but a simple data strategy framework will save you the headache of handling the nitty-gritty.

At InnoTek, we take data science and data architecture seriously. Implementing a successful data life cycle management strategy is not easy, but there are steps you can take to get a firmer handle on it. Let us help you simplify and enhance your approach to a more effective data strategy—we’re just one phone call away.

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