The fact that ransomware and cyberattacks have become increasingly prevalent is common knowledge, and this has raised greater awareness of the need for effective data protection. However, ransomware and other data breaches are not the only concern for businesses. Protecting data is essential, but managing it is equally important. This is not only to prevent data from falling into the wrong hands, but to ensure that organisations are compliant with a growing body of legislation, and to enable them to fully leverage the value of data for analytics and to drive business insight.
Data is sensitive
One does not have to look hard to find examples of high-profile data breaches, both in South Africa and across the globe. One of the most publicised breaches in recent years occurred in late May 2020, when credit bureau TransUnion discovered that an unauthorised third party had gained access to its systems and had downloaded a large amount of personal data.
This breach exposed the confidential data of over a million South Africans, with information including ID numbers, financial details, and phone numbers leaked into the public domain. A comprehensive cybersecurity strategy must include data protection, to prevent this sort of attack from causing the extent of damage that it did, as the consequences can be significant.
From loss of customer trust and damage to reputation, to compliance fines and the financial impact of recovering from a breach, no business can afford to be the victim of such an attack. However, the goal should not be just data protection in isolation, but data management as a holistic concept. This is key to effectively safeguarding information, while ensuring it can also be leveraged for business value.
Data is valuable
When it comes to data, the lifeblood of the digital organisation, several important factors need to be considered as part of an overall data management strategy. Data that is not available for analysis is not adding business value, and poor quality data can lead to inaccurate insights, bad decisions and wasted resources, while data that is not governed is a compliance risk. Furthermore, data that is siloed can prevent organisations from having a complete and accurate picture of information across various platforms and applications throughout the enterprise; and data that is not managed effectively throughout its lifecycle can result in faulty insight, increased risk and inflated storage costs, among other business challenges.
An effective data management strategy should therefore include data quality to ensure that data is accurate, complete and consistent; data governance to ensure that policies, procedures and standards are established around data; and data integration, to create a unified view of information. Data management should also incorporate data lifecycle management, from creation to deletion, including archiving data, preserving data for historical purposes, and securely disposing of data that is no longer needed.
Data needs to be managed holistically
While data protection is an essential part of data management, it is just one aspect of the broader data management discipline. Data needs to be collected, processed, stored and analysed in a way that is secure, efficient and compliant, not only to protect against ransomware and data breaches, but to ensure that the value of data can be leveraged to its greatest extent.
However, using multiple point solutions to achieve this adds a layer of cost and complexity that can erode the benefits. A single, holistic data management strategy ensures consistency across data management processes to reduce errors and improve the accuracy and reliability of the data. In addition, a comprehensive solution that integrates with other systems and tools can help streamline data management processes and eliminate the need for multiple tools. A single provider also reduces the costs associated with managing multiple systems and tools, offers improved service and support, and delivers enhanced security through an integrated, comprehensive data management process. This can help reduce the risk of data breaches and other security threats, while enhancing all other elements of data management as a whole.
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