Regulating the use of big data in Africa

Large-scale data collection for strategic decision-making has been made possible by the rise of big data, which has already had a profound impact on the global economic environment. A distinct set of opportunities and difficulties arises from the adoption of big data analytics in Africa. The application of big data in African organizations has a significant influence on decision-making procedures and holds promise for the continent’s future use of this technology. A setback is associated with this potential. Big data collection and utilization are fraught with issues and worries. The worry of consumers over privacy is one of these.

In Europe and other developing continents of the world, great measures and regulations have been put in place to check these concerns and are being implemented to stem the abuse of this personal information.

So what about Africa? What are the concerns among consumers and business entities? And what regulations have been put in place?

This article talks extensively on why Big Data must be properly regulated in Africa as a matter of urgency.

What is big data 

Big data is structured or structured and a large amount of data collection. They keep growing over time at an astronomical rate. Most traditional data management systems are not able to store process or analyze them, because they are too vast and too large and are mostly too complicated by their volume and capacity.

The major drivers of this big data are the Internet of Things, artificial intelligence, and enhanced mobile connectivity, amongst others. With these, vast amounts of data are collected and retrieved from consumers of these technologies.

With this data, new solutions are being developed to help businesses collect, process and analyze them as quickly as possible to maximize their value.

These big data, when properly collected and analyzed, help businesses to make predictions and solve problems and also can make wise decisions with the help of technologies like predictive modelling, machine learning, and other strong analytical tools.

In Africa, the prospect of big data is great and promising. This is because it will help businesses to advance development, growth and innovation.

For example, the rate of internet penetration in Africa alone is about 28.2% as of 2019.

Problems arising from the use of big data 

Do you know that for companies in many sectors, big data has the potential to be a game changer for them? But like other tools, its usefulness sorely depends on how it is applied, and who has access to it. The truth is that big data has proven to be especially challenging in many ways. 

The concerns seem to be enormous, from personal security concerns to privacy and cybersecurity. Businesses and government entities need to set up regulations and acquire the skills to leverage big data and address these concerns.

Below are some of the challenges that come with big data.

1. Privacy and cybersecurity concerns 

The biggest danger associated with big data is security. Establishments that hold this big data from consumers are always a major target of cybercriminals, and these data breaches can be so harmful to their reputation, finances, and time. 

Similarly, gathering enormous volumes of data while maintaining user privacy standards is made challenging by privacy legislation such as the General Data Protection Regulation of the European Union. To ensure privacy and security, transparency is essential. To securely preserve your data and adhere to privacy regulations, you need to be aware of what you gather, where you store it, and how you utilize it. For security and privacy updates and to make sure that records are current, businesses need to develop a data map and conduct frequent audits.

Automation may be useful. Security experts can be notified of potentially suspicious activities by using artificial intelligence (AI) systems that can continuously analyze datasets and their linkages. Analogously, by contrasting data practices with relevant standards and pointing up places for improvement, AI and robotic process automation can automate compliance.

2. The quality of data

One more prevalent issue is data quality, which includes data correctness, relevance, and completeness. Though larger datasets are more likely to contain errors, duplication, incomplete information, and inaccuracies, they are nevertheless necessary for human decision-making and machine learning. Making poor decisions and losing money results from not fixing quality problems. Large data must be automatically cleaned up using technologies that detect and fix mistakes such as missing data, anomalies, duplication, and other issues before it can be analyzed. Determining the precise points at which data collecting and cleansing methods need to be modified and routinely monitoring these benchmarks would also be helpful.

3. Problem associated with storage of data

Big data can be difficult and also become too expensive to manage and store. Companies invested about twenty-two billion dollars in computer store infrastructures alone.

The fact is that this vast amount of data that is being generated every day at an astronomical rate cannot be stored using the traditional methods of storage because they are difficult and costly.

Here is what cloud storage comes in. With cloud storage, you pay only for what you use, and you’re able to scale up and down instantly. Also, cloud storage can handle big data efficiently, while reducing financial restrictions.

 Automatic data lifecycle management, deduplication, and compression can reduce the amount of storage required. Additionally, an automated system can facilitate faster access and make it easier to identify duplicate or out-of-date data.

How big data can be regulated in Africa 

In the years after the Cambridge Analytics scandal, there has been a wider and a strigen data control in Europe and America. Africa must learn from her neighbor and implement measures and legislation as to how these data are collected and used.

1. The European Union’s approach to big data

The EU has been at the forefront of establishing a comprehensive regulatory 

framework on data of both a personal and non-personal nature. Since 2014, the European Commission has developed several directives and laws to facilitate the development of a data-agile economy. Examples include the Regulation on the free flow of non-personal data, the Open 

Data Directive, the General Data Protection Regulation (GDPR)  and the Cybersecurity Act. The recently adopted EU Data Strategy takes on an interdisciplinary approach to the regulation of the data economy.

The strategy is chiefly rooted in the need to expand the responsible use, demand and development of digital products and services within the European Single Market for the period 2020 to 2025 and is backed by the intention to make the EU a leader in a data-driven society. Therefore, creating a single market for data will allow it to flow freely within the EU and across sectors for the benefit of businesses, researchers and public administrations.

As has been stated before, the GDPR principally applies to the processing of personal data. This extends to both an identified person as well as an identifiable natural person. If this is applied practically, it therefore means that the GDPR and by extension, data protection does not apply to anonymous information or information that does not relate to an identified or identifiable natural person.

The same can be said for personal data that has been so diluted or encrypted that it is rendered anonymous because the data subject is no longer identifiable. And Africa as a country, especially the African Union, can copy this model. 

2. The African Union approach 

The African Union (AU) in 2014 adopted the Convention on Cyber Security and Personal Data Protection at the Twenty-third Ordinary Session of the Assembly, held in Malabo, Equatorial Guinea (known as the Malabo Convention), which has only recently come into force in May 2023 following the last necessary ratification by Mauritania. This convention focuses on personal data and cybersecurity. 

The AU Commission has also formulated the Africa Data Policy Framework, which is informed, in part, by the Malabo Convention.  But Outside of this concerted effort, very little has been done in terms of a collective continental/regional legislative instrument on data protection with most countries opting to attempt protection individually.

As the continent moves to realize the promises of the AfCFTA, it will be important to have a measure of harmonization in regulatory frameworks so that inter-Africa trade is enhanced. Businesses and individual entrepreneurs trading in different countries across Africa would benefit if they had some assurance that similar principles of data protection and data governance models are aligned across the continent. 

Conclusion 

The Cambridge Analytics scandal has taught everyone the importance of setting regulations on how data must be collected and used. And like the EU, Africa, especially the AU, must work together as a body to implement rules and regulations regarding the use of these data. Africa must not be a free market where anything goes.