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Simplifying Data Management in the Age of AI

Why remove obsolete data? Read on to explore.

 


In today's fast-paced business environment, the use of data has become of great importance for innovation and growth. However, alongside this opportunity comes the responsibility of managing data effectively to avoid legal issues and security breaches. With the rise of artificial intelligence (AI), businesses are facing a data explosion, which presents both challenges and opportunities.

According to Forrester, unstructured data is expected to double by 2024, largely driven by AI applications. Despite this growth, the cost of data breaches and privacy violations is also on the rise. Recent incidents, such as hacks targeting sensitive medical and government databases, highlight the escalating threat landscape. IBM's research reveals that the average total cost of a data breach reached $4.45 million in 2023, a significant increase from previous years.

To address these challenges, organisations must develop effective data retention and deletion strategies. Deleting obsolete data is crucial not only for compliance with data protection laws but also for reducing storage costs and minimising the risk of breaches. This involves identifying redundant or outdated data and determining the best approach for its removal.

Legal requirements play a significant role in dictating data retention policies. Regulations stipulate that personal data should only be retained for as long as necessary, driving organisations to establish retention periods tailored to different types of data. By deleting obsolete data, businesses can reduce legal liability and mitigate the risk of fines for privacy law violations.

Creating a comprehensive data map is essential for understanding the organization's data landscape. This map outlines the sources, types, and locations of data, providing insights into data processing activities and purposes. Armed with this information, organisations can assess the value of specific data and the regulatory restrictions that apply to it.

Determining how long to retain data requires careful consideration of legal obligations and business needs. Automating the deletion process can improve efficiency and reliability, while techniques such as deidentification or anonymization can help protect sensitive information.

Collaboration between legal, privacy, security, and business teams is critical in developing and implementing data retention and deletion policies. Rushing the process or overlooking stakeholder input can lead to unintended consequences. Therefore, the institutions must take a strategic and informed approach to data management.

All in all, effective data management is essential for organisations seeking to harness the power of data in the age of AI. By prioritising data deletion and implementing robust retention policies, businesses can mitigate risks, comply with regulations, and safeguard their digital commodities.


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