The DATALAB is a cross-disciplinary research lab at the Solvay Business School. It focuses on developing and adapting analytical tools and algorithms that retrieve valuable insights from data while taking into account the specific operational context, domain expertise and business requirements of the application at hand, an approach that differs from the typical statistical or IT perspective. The lab also exploits the connection between data analysis and the properties of complex systems, developing data analysis tools based on information theory, nonlinear dynamics, ergodic theory and statistical physics. The lab harnesses the power of Large Language Models to advance natural language understanding and scientific progress, applying them to domains ranging from the science of science to practical implementations. Its work also includes developing Explainable AI methods to uncover and address algorithmic bias, leveraging Graph Neural Networks to analyze structured data, and tackling the challenges of multitask learning with inspiration from physics and deep learning theory. The lab models biological systems using statistical physics, studies wealth inequality through computational approaches, and applies tools like ergodic theory and nonlinear dynamics to explore the evolution of complex systems, bridging theoretical innovation and real-world impact across science, business and society. The lab performs both fundamental and applied research, always in close collaboration with a wide network of academic and industrial partners.