The extensive use of Big Data has now become common in plethora of technologies and
industries. From massive data bases to business intelligence and datamining
applications; from search engines to recommendation systems; advancing the state of
the art of voice recognition, translation and more. The design, analysis and
engineering of Big Data algorithms has multiple flavors, including massive
parallelism, streaming algorithms, sketches and synopses, cloud technologies, and
more. We will discuss some of these aspects, and reflect on their evolution and on
the interplay between the theory and practice of Big Data algorithmics.