Data Integrity is a critical component of Data lifecycle management. Its
importance increases even more in a complex and dynamic landscape. Actions like
unauthorized access, unauthorized modifications, data manipulations, audit
tampering, data backdating, data falsification, phishing and spoofing are no
longer restricted to rogue individuals but in fact also prevalent in systematic
organizations and states as well. Therefore, data security requires strong data
integrity measures and associated technical controls in place. Without proper
customized framework in place, organizations are prone to high risk of
financial, reputational, revenue losses, bankruptcies, and legal penalties
which we shall discuss further throughout this paper. We will also explore some
of the improvised and innovative techniques in product development to better
tackle the challenges and requirements of data security and integrity.
References
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[2]
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