In today’s digital era, data is the lifeblood of businesses. Every day, companies generate vast amounts of data from various sources, including customer interactions, social media, and IoT devices. However, with the volume of data continuing to grow exponentially, managing it can be a challenge. Data retention and deletion policies are essential tools that businesses can use to manage their data effectively and unlock business value.
Data retention and deletion refer to the processes of storing data for a specific period and deleting it once it is no longer needed. Data retention ensures that businesses comply with legal and regulatory requirements, while data deletion reduces the risk of data breaches and improves data quality.
However, many businesses struggle to implement effective data retention and deletion policies, leading to the accumulation of obsolete, redundant, or trivial (ROT) data. And according to IDC, 60 percent of data stored by businesses is ROT.
Data retention can be costly for businesses. Storing data beyond its useful life increases storage costs, making it more expensive to manage data. According to IBM, the cost of storing one terabyte (TB) of data on-premises is $4,000 per year. With businesses generating vast amounts of data, these costs can quickly add up. Furthermore, retaining ROT data can lead to compliance and legal risks, including GDPR violations, which can result in hefty fines and reputational damage.
Deleting ROT data has several benefits for businesses. First, it reduces storage costs, allowing businesses to optimise their data storage resources. Second, it improves data quality, making it easier for businesses to make data-driven decisions. Third, it reduces the risks associated with data breaches and non-compliance, protecting businesses from reputational damage and financial losses.
To effectively manage data retention and deletion, businesses need to develop a data retention and deletion policy. This policy should outline the types of data that the company needs to retain and the duration of retention. The policy should also specify the process for deleting data once it reaches the end of its useful life. One way to orchestrate data retention and deletion is through the use of data lifecycle management (DLM) tools. DLM tools automate the process of managing data throughout its lifecycle, from creation to deletion. These tools can help businesses identify ROT data and automate the deletion process, thus reducing the risk of human error.
Another way to orchestrate data retention and deletion is through the use of data classification tools. Data classification tools analyse data and categorise it based on its sensitivity, importance, and other factors. This classification helps businesses prioritise data retention and deletion based on the value of the data.
Several businesses have implemented effective data retention and deletion policies. One example is Adobe Systems. Adobe has implemented a tiered retention policy that categorises data based on its value. The policy specifies different retention periods for each tier, with the lowest tier having the shortest retention period. The policy also includes a process for deleting data once it reaches the end of its useful life.
Implementing a data retention and deletion policy requires agencies to retain data only for as long as it is necessary to meet their business and legal requirements. The policy specifies who and why data must be deleted once it is no longer needed, reducing the risk of data breaches and compliance violations and procedures must set how it must be implemented to back-up existing policy documents.
Data retention and deletion policies are essential tools that businesses can use to manage their data effectively and unlock business value. Data retention and deletion policies help businesses reduce storage costs, improve data quality, and reduce the risks associated with data breaches and it is important for businesses to employ these procedures to manage ROTS in businesses.
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