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BIG DATA STRATEGIES FOR AGILE BUSINESS
Título:
BIG DATA STRATEGIES FOR AGILE BUSINESS
Subtítulo:
Autor:
UNHELKAR, B
Editorial:
CRC PRESS
Año de edición:
2017
Materia
INFORMATICA EMPRESARIAL
ISBN:
978-1-4987-2438-8
Páginas:
503
81,50 €

 

Sinopsis

Features
Offers a business view of Big Data and its analytics
Showcases the importance of Big Data technologies (Hadoop/Mapreduce) in the context of business decision making
Demonstrates the interrelationship between social, mobile, analytics, and cloud (the SMAC stack) and its relevance to Big Data strategies
Provides a practitioner's view on Big Data strategies that would be helpful to consultants as well as in-house decision makers
Imparts an understanding of the concepts of Big Data strategies and Agile Business through examples and case studies
Summary
Agile is a set of values, principles, techniques, and frameworks for the adaptable, incremental, and efficient delivery of work. Big Data is a rapidly growing field that encompasses crucial aspects of data such as its volume, velocity, variety, and veracity. This book outlines a strategic approach to Big Data that will render a business Agile. It discusses the important competencies required to streamline and focus on the analytics and presents a roadmap for implementing such analytics in business.



Table of Contents
Introduction to Big Data and Agile Business

Big Data Framework for Agile Business (BDFAB)

Data Science - Analytics, Context and Strategies
Business Process Modeling (BPM); Agile Practices; Big Data Adoption Process

Enterprise Architecture (EA) and the Big Data Technical Eco-System

Social Mobile (SoMo), Presentation and User Experience in Big Data

Cloud-Based Big Data Strategies; Sustainability; Analytics-as-a-Service (AaaS)
Big Data, Semantic Web and Collaborative Business Process Engineering (CBPE)

NoSQL Databases and Big Data Strategies

Quality& Service Assurance, Testing and Governance-Risk-Compliance (GRC) Within Big Data

Big Data People and Communities

Functioning Agile Organization with Big Data Adoption

Big Data and Banking: A-Bank Case Study

Big Data and Health

Big Data and Education

Appendices