Data Privacy & Security in the Age of the Cloud

Data privacy and security are big topics in the technology landscape. In the age of big data where many individuals use online storage systems such as Dropbox, consumers are beginning to question the safety and confidentiality of their personal information.

With IT Governance reporting a staggering 8 billion data breaches in 2023, it comes as no surprise that there’s growing apprehension about who has access to data, how it is being used and whether it is adequately protected from unauthorised access or breaches.

By 2025, it is estimated that 463 exabytes of data will be created each day, equivalent to 212,765,957 DVDs. Let’s explore what this means for businesses.

Big data refers to large and complex data sets that cannot be easily managed or analysed using traditional data processing techniques or software. These data sets typically contain massive volumes of structured, semi-structured and unstructured data.

In regards to big data privacy, this refers to the protection of sensitive and personal information within the context of big data analytics and processing. This includes the policies, procedures and technologies implemented to ensure that individual's data rights and privacy are respected, even as large volumes of data are collected.

Given the magnitude of developments in the tech sector, the safety of big data is often a common worry. If gathered and stored incorrectly, big data has the potential to pose some serious dangers. This can include data breaches, data loss, data corruption and regulatory non-compliance.

Improper backup and recovery procedures can result in data loss. For example, if big data systems are not appropriately backed up or replicated, hardware failures, software bugs or human errors can lead to irreversible data loss.

Components such as hard drives, solid-state drives (SSDs), and servers can malfunction unexpectedly, resulting in data loss if not adequately backed up. Similarly, software bugs, glitches and corruption within big data systems can also pose significant risks to data integrity.

Data integrity is the accuracy and quality of the data.

If a software update introduces unforeseen errors or if the system encounters software-related issues, it may lead to data corruption or loss. Without reliable backup or recovery mechanisms, organisations may struggle to recover lost or corrupted data, potentially disrupting business operations and compromising decision-making processes.

Data corruption can occur due to various reasons, such as hardware malfunctions, software bugs or network issues.

If big data is stored incorrectly without proper data integrity or checks, corrupt data can propagate throughout the system. This leads to inaccurate analytics, decision-making and potentially severe financial losses.

Moreover, network issues such as packet loss or data transmission errors can corrupt data as it travels between different components of the system. These factors collectively pose significant risks to the integrity of big data storage environments.

As a result, the financial implications of data corruption can be severe. Organisations may incur direct costs associated with data recovery efforts, system repairs and potential legal liabilities.

When assessing the effectiveness and safety of your data strategy, it’s essential to ask yourself the following questions.

1. How is sensitive data encrypted and protected from unauthorised access or breaches?
2. Are robust backup and recovery procedures in place to ensure data availability and integrity in case of system failures or disasters?
3. Does the data strategy adhere to regulatory requirements and industry standards relevant to the organisation's operations and data handling practices?
4. Are there mechanisms in place to monitor data access, track changes and conduct audits to identify potential security breaches or compliance violations?

A growing number of organisations rely on big data to drive insights and innovation. However, the vast amount of data brings significant risks to privacy and security.

Cyber threats, data breaches and regulatory requirements emphasise the need for organisations to develop a clear strategy. A robust big data privacy and security strategy is crucial for safeguarding data, maintaining trust, and complying with regulations.

Conduct regular audits and compliance checks

The first step of any strategy involves conducting regular audits and compliance checks. This allows organisations to assess the effectiveness of big data privacy and security controls.

These audits and checks serve as a critical evaluation of mechanisms, ensuring the company is adhering to its regulatory compliance and assessing how effective these measures are. Similarly, during these checks, any vulnerabilities within systems can be exposed.

Develop employee training and awareness

A company can have a robust big data privacy and security strategy, but if employees are not up to date with regular regulations, it will seize its purpose. As a result, employee training and awareness are vital components of developing a robust big data privacy and security strategy.

By educating employees on data handling best practices, compliance requirements and risk mitigation strategies, organisations can reduce the likelihood of data breaches and non-compliance with regulations such as GDPR and HIPAA.

Equipping employees with the knowledge and skills to respond effectively to security incidents ensures swift and appropriate action when necessary. This ultimately reduces the risks of any security incidents and maintains the integrity of the organisation's data handling practices.

Understand regulatory compliance

Data compliance standards vary across industries and regions; however, they focus on common principles. For example:

• Data accuracy
• Tracking data storage
• Protecting sensitive information
• Providing transparency over individual data rights

The existing data compliance regulations include the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA). By understanding these regulations, organisations can implement appropriate measures to safeguard data, mitigate risks and prevent unauthorised access or breaches.

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