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Tackling Data Retention in Data Life Cycle Management!


Tackling Data Retention in Data Life Cycle Management!
Tackling Data Retention in Data Life Cycle Management!

The laws & regulations state how long data can be saved, when it must be deleted, & regulations that state if any specific information must be saved for a minimum period. Across all industries, organizations need to maintain compliance with different retention regulations that vary by industry, country, or even by state for different categories of information.

It is more difficult for the organizations operating multi-nationally, to abide by various country regulations. At any given time, retention laws may be added or amended, so Chief Data Officers (CDOs) need to stay updated with retention laws to adjust & execute new policies for their company. CDOs are responsible for owning data lifecycle management with data governance priorities.

As organizations are working with roles that may have conflicting priorities about data lifecycle management, it is important to have consistent, documented policies about when data will be retained & when data must be deleted.

Technology solutions are available to automate the complex task of applying data retention policies. Organizations first need to discover & classify information to know the data & relevant policies to apply data retention. Advanced artificial intelligence (AI) solutions help automate discovery & classification to identify & match the data to the relevant policy.

As organizations have vast amounts of data, applying technology solutions to assist with lifecycle management is a recommended best practice to maintain a data retention program. Automating data discovery & applying policy tracking is more efficient & accurate than with manual effort.

Data retention prevails across all parts of the business for different initiatives & priorities. By successfully incorporating the business-centric data retention programs, organizations are assured to gain benefits


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