Data ethics in business: From collection to compliance

We live in a data-driven world where businesses are often rendered ineffective when they lack or have insufficient data. This is because enterprises leverage vast amounts of information to make predictive and future forecasts. Data ethics in business refers to the responsible handling of data throughout its lifecycle. That is, from data collection and management to the use of data, ensuring respect for privacy, fairness, and legal compliance.

Why Data Ethics Matters More Than Ever

Due to the importance that data holds in the world today, it is being compared to the significance that oil offers in the industrial economy, hence the common phrase “data is the new oil.” This analogy typically captures the crucial reality that data drives the digital economy in the same way that oil drove the industrial period.

Legislation such as the General Data Protection Regulation (GDPR) in the European Union, the UK’s Data Protection Act, and the California Consumer Privacy Act (CCPA) in the United States are all important steps toward regulating how data is used. These laws make it clear that ethical data practices are not optional and are, in fact, legally mandated. Still, the law often lags behind technology.

More than avoiding fines from regulatory bodies, ethical data use is about building trust. An organisation that respects its customer data would earn loyalty and credibility.

Core Principles of Ethical Data Practices

For businesses to thrive, data management should be anchored on certain ethical principles. The principle of ‘Transparency’ builds trust and enables informed consent by the data subject, that is, the individual whose personal data is collected, held, or processed. By upholding this principle, data subjects have the right to know what data are collected, why the data are collected, who will have access to their data, and for what purpose.

Secondly, the data subject should have the capacity to give their consent to the data collected and also to withdraw consent on who can access their data. This principle is referred to as Consent and Control.

Thirdly, Privacy and Confidentiality must be upheld to protect personal data against any form of misuse or unauthorised access. As a result, organisations must adopt encryption of data in their custody and ensure their protection from unauthorised persons (or groups).

In addition, businesses must review their algorithms and data for bias and discriminatory outcomes. To actualise this, organisations make data-driven decisions to ensure equal treatment and prevent discrimination in automated processes and predictive analytics. Lastly, organisations must demonstrate accountability by adopting strong governance frameworks, maintaining transparency, and taking full responsibility for their data practices to uphold ethical standards and public trust.

Ethical Use and Distribution of Data

Ethically, data should be collected from data subjects with consent and without coercion, and this should also extend to the responsible use of the data and how they are shared. In other words, data must be used in accordance with the original purpose, and if, for any reason, they are to be shared, the consent of the data subject must be sought.

Barriers to Ethical Data Implementation

Even with the best intentions, businesses sometimes struggle to keep ethics at the forefront. One of the barriers to ethical data implementation is the pace at which technology advances, which sometimes overshadows what the existing regulations or ethics frameworks can adapt.

Another lies in the fact that data ethics may be impeded due to the different jurisdictions where the data is domiciled or needs to be transferred. For instance, what is considered ethical or legal in one country may be seen differently in another. A typical example is the GDPR concept, as it is seen in the UK and the European Union. Additionally, businesses may be tempted to compromise on ethical practices in their pursuit of gaining market share, and improper profiling of embedded systems, such as AI systems, could lead to data bias.

Therefore, in addition to meeting regulatory and compliance requirements, businesses must build courage, clarity, and a strong commitment to doing what is right.

Building Ethical Data Culture

Businesses must move beyond compliance checklists and embrace ethics as a shared value. To start with, organisations must secure leadership buy-in to champion data ethics and establish strong policies and governance frameworks. Secondly, cross-department collaboration—bringing together legal, IT, marketing, HR, and compliance teams—is essential to embed ethics across all data processes, supported by regular ethics reviews and open dialogue to address concerns.

Lastly, continuous improvement should be prioritised by aligning ethical standards with technological and societal changes and embedding ongoing learning and adaptation into data governance to ensure long-term ethical resilience. 

Conclusion

In a digitally driven world, for businesses to build their reputation and the trust of their customers and users, they must stay ethical through how their data are managed, that is, collected, utilised, shared, and disposed of. This approach would foster trust, protect reputations, and ensure compliance with regulatory bodies responsible for the ethical use of data.

Today, businesses are not only being held accountable by regulatory bodies but also by an increasingly awareness and empowered public; therefore, ensuring data ethics is in place is a significant metric to ensure such organisations thrive.

About the author

Nathaniel Akande is a Cybersecurity Analyst with over 8 years of experience in threat intelligence, incident response, vulnerability management, risk compliance, and Quality assurance analyst in the Software Development Life Cycle process. He holds a Master’s Degree in Cybersecurity and is a PECB Certified ISO/IEC 27001 Lead Implementer. Adept at implementing data governance, identity and access management, and aligning operations with standards like GDPR, ISO 27001, and NIST. He is known for strong analytical skills, technical acumen, and a proactive approach to security operations and compliance.