This Focus Issue highlights recent advances in the study of complex systems, with a particular emphasis on data-driven research. Our editorial explores a diverse array of topics, including financial markets, electricity pricing, power grids, lasers, the Earth's climate, hydrology, neuronal assemblies and the brain, biomedicine, complex networks, real-world hypergraphs, animal behavior, and social media. This diversity underscores the broad applicability of complex systems research. Here, we summarize the 47 published works under this Focus Issue, which employ state-of-the-art or novel methodologies in machine learning, higher-order correlations, control theory, embeddings, information theory, symmetry analysis, extreme event modeling, time series analysis, fractal techniques, Markov chains, and persistent homology, to name a few. These methods have substantially enhanced our understanding of the intricate dynamics of complex systems. Furthermore, the published works demonstrate the potential of data-driven approaches to revolutionize the study of complex systems, paving the way for future research directions and breakthroughs at the intersection of complexity science and the digital era of data.