Big Data Application Architecture Pattern Recipes provides an insight
into heterogeneous infrastructures, databases, and visualization and
analytics tools used for realizing the architectures of big data
solutions. Its problem-solution approach helps in selecting the right
architecture to solve the problem at hand. In the process of reading
through these problems, you will learn harness the power of new big data
opportunities which various enterprises use to attain real-time profits.
Big Data Application Architecture Pattern Recipes answers one of the
most critical questions of this time 'how do you select the best
end-to-end architecture to solve your big data problem?'.
The book deals with various mission critical problems encountered by
solution architects, consultants, and software architects while dealing
with the myriad options available for implementing a typical solution,
trying to extract insight from huge volumes of data in real-time and
across multiple relational and non-relational data types for clients
from industries like retail, telecommunication, banking, and insurance.
The patterns in this book provide the strong architectural foundation
required to launch your next big data application.
The architectures for realizing these opportunities are based on
relatively less expensive and heterogeneous infrastructures compared to
the traditional monolithic and hugely expensive options that exist
currently. This book describes and evaluates the benefits of
heterogeneity which brings with it multiple options of solving the same
problem, evaluation of trade-offs and validation of
'fitness-for-purpose' of the solution.
