This new book focuses on the practical aspects to address Big Data scaling challenges, spanning from data integration to data analytics, including the emerging edge analytics. The dramatic increase in the processing power and the capacity of storage along with the rapid growth of cloud and the availability of Big Data offer unprecedented opportunities for scaling analytics and discovery.
Big Data’s rapid growth has definitely created radical shifts with new opportunities, leading organisations and companies to shift their activities towards more data-driven decisions with the help of machine learning (ML) techniques and artificial intelligence (AI). A shift from stand-alone traditional desktop computing to embrace a more comprehensive strategy such as Mesh App and Service Architecture (MASA) strategy banking on Big Data to allow more dynamic connection of people, processes, things and services that are supporting today’s increasingly intelligent (AI) digital ecosystems, according to Gartner (2017).
The book refers to the different techniques and tools used to address the ambiguity and uncertainty as well as scaling challenges that helped to transform, analyse, and reveal hidden patterns. The identified patterns were used, in turn, successfully in the discovery process. The tools are presented, in this book, within the perspective that these tools will lend themselves to also scale as the technologies and methodologies evolve.