In recent years, quantum computing has moved from research labs to cloud platforms. But in this field it is important to separate hype from realistic expectations. In this article, we summarise where quantum computing stands today and what it could mean for the world of data.
Quantum computing in brief
Classical computers process information with bits that take the value 0 or 1. Quantum computers work with qubits, which take advantage of quantum properties such as superposition and entanglement. This opens the door to algorithms that, for certain types of problems, differ from classical methods and could be far more efficient.
Where are we today?
Today’s quantum processors are still sensitive to noise and have a limited number of qubits. Significant progress is being made in error correction, but applications that demonstrate a clear advantage over classical methods on real business problems are still limited. That is why the real value today lies in preparation and gaining experience.
Promising areas for the world of data
- Optimisation: Multi-variable problems such as route planning, warehouse and inventory distribution, and shift scheduling
- Simulation: Modelling molecular behaviour in fields such as chemistry and materials science
- Quantum machine learning: A long-term field that is still at the research stage
- Security: Because powerful quantum computers could threaten some of today’s encryption methods, the transition to post-quantum cryptography (PQC) standards has begun
What can companies do today?
- Identify complex optimisation problems that could be candidates for quantum
- Strengthen their data infrastructure; whatever technology is used, clean data is essential
- Run small experiments on quantum platforms accessible through the cloud
- Inventory their encryption and plan their readiness for post-quantum cryptography
The Future Quantum Data approach
Today we strengthen companies’ data infrastructure through data analytics, Power BI and data science projects. On the quantum programming side, we continue our optimisation-focused R&D and are preparing to announce our services in this area soon.