Big Data Orchestration from Logical to Physical Level

Master thesis is dedicated to the design of Big Data architecture solutions. Currently, the storage area and data analysis are faced with limitations of computational resources and the ability to scale existing solutions. Big Data approach enables to solve and remove existing restrictions. The most efficient way for removing these restrictions is to develop and implement the complex architectural solution. The aim of this work is to develop approaches and methods for dealing with complex Big Data architectural solutions. To achieve this goal several tasks were solved. Methods for designing Big Data architecture solutions were developed and described. Architectural frameworks required for designing Big Data solutions were developed and described. Implementation methodology and transformation steps of legacy conditions into Big Data solutions were developed and described in the master thesis. Several examples dealing with various company transformations based on solving Big Data problems were developed and described in master thesis. Keywords: Big Data, architecture, distributed file systems, framework, processing engine, data storage, model.