For big companies, and insurance companies in particular, there are multiple opportunities. For example, data revealing driving styles are of interest to non-life insurance, and data concerning health and lifestyle are useful for life insurance. In both cases, knowing more about the person being insured allows better estimation of future risks. Storing this data requires a flexible and tailored architecture to allow parallel and dynamic processing of “voluminous”, “varied” data at “velocity” while evaluating its “veracity” in order to derive the great “value” of these new data flows. Big data, or megadata, is often presented in terms of these five Vs. This chapter describes current architecture models capable of real-time processing of high-volume and varied data, using parallel and distributed processing. As for all economic actors, insurers will of course face changes of organization, culture and competition. The chapter illustrates this development with a few examples in which big data plays a central role.