In today’s modern world, Big data analytics has become a fundamental part of our daily activities. Everything we do is linked to data security in one way or another. From companies using it to cure diseases, fight global warming and increase customer engagement all the way to predicting behaviors and building efficient business ecosystems, data is the key to digital innovation.
Synthetic data security, on the other hand, is a new concept that’s starting to win popularity across organizations and economies at large. In simple terms, it’s artificial data generated by AI technology. Its aim is to mimic the statistical patterns and properties of existing datasets, thus creating fresh new data security with identical features to the original one. In terms of value in a business context, synthetic data improves speed, and security and can help organizations scale faster.
Improved protection and security of sensitive information
Synthetic data eliminates the risk of compromising vital information in sensitive industries such as healthcare apps, manufacturing, retail, and others. This way, it makes sure both company and customer data are fully protected against external threats. Advanced privacy-preserving, encryption, and anonymization are just several of its fundamental capabilities. Via sophisticated algorithms, synthetic data can be used to safeguard the original data, minimizing the risk of exposure, alterations, or modifications by hackers and cybercriminals.
Amid the COVID-19 pandemic, the healthcare industry has been constantly struggling to protect patient information. To make sure everyone is safe and better seal records pertaining to infections, synthetic data can act as a bulletproof privacy barrier, preventing any sort of attempt to hamper the original data or breach any health system in an attempt to block access or steal information.
Speed and easier access to information
Companies across all industries are having issues getting access to their data as soon as it was collected. The longer it takes to extract the information, the more time it takes to generate value from it. With the help of synthetic data, organizations can streamline processes, eliminating privacy roadblocks and any additional security protocols that could slow down access to the data. Machine learning tech stacks, for example, can be easily implemented to deploy, train, and test AI-based solutions a lot faster.
However, original data can be challenging to collect. It may take months before enough data is gathered to train an AI. But with synthetic data, fast access to information via large datasets provides engineers with enough data to kick start the training of an AI-powered tool or platform. For businesses, it saves time and money, not to mention that it gives them an edge and a viable opportunity to stand above their market competitors.
Mass scaling & the opportunity to solve bigger problems
For any business to grow, scale, and have an impact, fast access to data matters just as much as security. Synthetic data can help with both pinpoints. On the one hand, it enables organizations to expand the data they can assess without bottlenecks or human error. Currently, companies operate on narrow data models that are limited in nature. With synthetic data, they can broaden their efforts, reaching vast data frameworks without going over budget.
Although original third-party data is accessible and ready to be purchased, for many organizations it’s an expensive endeavor they cannot afford. Also, it comes with a myriad of privacy concerns. Synthetic data is more conveniently-priced, just as reliable as original data, and Ultimately easier to use to increase return on investment.
Synthetic data security – a brand new data economy unfolded
From a business perspective, there’s an ongoing hunger to access as much data as possible. The downside is not every institution, government entity, startup, or company is willing to share information. Many are not willing to risk a data security breach whereas others simply don’t trust that the information will be used for a good cause. The good news is, that synthetic data could convince organizations to become more open about their data and the information they can share.
Simply put, it’s safer, faster, and more conveniently priced. Whether companies wish to buy or sell data, the potential of synthetic data goes beyond making a profit. The technology is still new, but it has been demonstrated to provide tremendous benefits in terms of protecting people’s identities, safekeeping critical information, and accelerating access speed.
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