High-resolution structural information is needed in order to unveil the underlying mechanistic of biomolecular function. Due to the technical limitations or the nature of the underlying complexes, acquiring atomic resolution information is difficult for many challenging systems, while, often, low-resolution biochemical or biophysical data can still be obtained. To make best use of all the available information and shed light on these challenging systems, integrative computational tools are required that can judiciously combine and accurately translate sparse experimental data into structural information. In this review we discuss the current state of integrative approaches, the challenges they are confronting and the advances made regarding those challenges. Recent developments are underpinned by noteworthy application examples taken from the literature. Within this context, we also position our data-driven docking approach, HADDOCK that can integrate a variety of information sources to drive the modeling of biomolecular complexes. Only a synergistic combination of experiment and modeling will allow us to tackle the challenges of adding the structural dimension to interactomes, shed "atomic" light onto molecular processes and understand the underlying mechanistic of biomolecular function. The current state of integrative approaches indicates that they are poised to take those challenges.