  RooFit and RooStats, the toolkits for statistical modelling in ROOT, are used
in most searches and measurements at the Large Hadron Collider as well as at
$B$ factories. Larger datasets to be collected at e.g. the High-Luminosity LHC
will enable measurements with higher precision, but will require faster data
processing to keep fitting times stable. In this work, a simplification of
RooFit's interfaces and a redesign of its internal dataflow is presented.
Interfaces are being extended to look and feel more STL-like to be more
accessible both from C++ and Python to improve interoperability and ease of
use, while maintaining compatibility with old code. The redesign of the
dataflow improves cache locality and data loading, and can be used to process
batches of data with vectorised SIMD computations. This reduces the time for
computing unbinned likelihoods by a factor four to 16. This will allow to fit
larger datasets of the future in the same time or faster than today's fits.
