If there’s a popular theme in the world of technology, it’s got to be data – and the numbers prove it all. In 2020, about 2.5 quintillion bytes of data were created each day. For context, that would be about 10 million Blu-ray discs. When stacked against each other, that would be the combined height of two Eiffel towers!
What the Future Holds for Data
Data is used everywhere. Organizations can use it to make critical business decisions while individuals can also utilize it to learn more about themselves. The widespread applications of data are only bound to grow from here. Yet the question remains – in what specific ways?
In this article, we’ll explore the defining trends that define the future of data. As this field continues to grow, we’ll explore the impact of data on technologies, social dynamics, and more.
Artificial Intelligence
Together with data, artificial intelligence (AI) is also one of the biggest buzzwords in the tech world today. The growth of artificial intelligence relies on the availability and quality of data. Machines learn from historical data to predict potential outcomes, recognize patterns, and make decisions without explicit programming.
As the AI race continues, many models will become more dependent on data. After all, the success of an AI model does not solely rely on its architecture or algorithms, but rather on the quality and diversity of data that it processes. Only those who know how to harness the power of data effectively can succeed in this fast-growing field.
Quantum Computing
Traditional computers are powerful, yes, but quantum computers are on a whole different level. Unlike classical computers that use bits to represent information such as 0s and 1s, quantum computers use quantum bits or qubits.
These qubits exist in multiple states simultaneously, allowing quantum computers to perform complex calculations significantly faster than traditional computers. Because of the sheer power they have to revolutionize data analysis, we’ll find more breakthroughs in areas such as machine learning, optimization, and pattern recognition.
Data Privacy and Security
As data continues to be used by both individuals and organizations, many concerns are raised about data privacy. The constant flow of information, whether it be personal information or corporate data, does fuel innovation, but the concerns on data handling, usage, and storage must be addressed.
The increased reliance on data will lead to individuals sharing less and less of their personal information online, due to the severe risks that come with doing so. As a result, more individuals are demanding increased transparency and control over how their data is collected and used.
We can expect organizations to beef up their cybersecurity to prevent data breaches from occurring, such as migrating their data to cloud storage. The consequences of a data breach often involve financial loss, reputational harm, and the compromise of individuals’ personal information.
Data Regulations
Like with most technological advancements, regulations must exist to protect data – whether it be through handling, storage, or usage. In 2018, we saw the enactment of the General Data Protection Regulation by the European Union (EU)
Organizations must now obtain explicit consent for data processing, disclose how data is used, and provide mechanisms for data subjects to access, rectify, or delete their information. This framework is applied not only to the European Union as this regulation has set the standard for other regions and countries.
There have been concerns, particularly about the use of data in AI models. Earlier, we mentioned that data is used to train these models. However, there are concerns about data privacy. If personal information is used, for example, can cyber attackers gain access to this data?
Because artificial intelligence is quite novel, the regulations surrounding the use of data in AI have been unclear. In the near future, we can expect more clarity on the proper use of data in artificial intelligence.
Augmented Reality and Virtual Reality
Other innovations that are expected to grow in the coming years are augmented reality (AR) and virtual reality (VR). Both AR and VR depend on sensors to provide an immersive experience.
Additionally, these technologies generate a large amount of data. For example, VR records data in a virtual environment, which is often high-resolution data. This can cause some challenges with storage and handling.
Thus, data scientists must step in and design efficient strategies for data management – this can become particularly challenging when handling large amounts of data, as you do with AR and VR.
Just like with other technologies, there are also potential issues relating to data privacy, specifically in AR and VR technologies that deal with personal information and other confidential data.
Final Thoughts
The future is indeed bright as we transition to a more data-driven world. Because it is now a valuable commodity, data has led the way to more innovations in the fields of artificial intelligence and AR/VR.
However, as we continue to increasingly rely on data, it becomes a challenge to deal with data privacy and the regulations surrounding it. Despite that, the potential benefits of a data-driven world are immense.
The evolution of data must be approached with transparency and ethical considerations, so we can ensure a bright future ahead – one that prioritizes technological advancements while also protecting individuals and organizations alike.
