From Big To Smart Data How Can Data Analytics Support Strategic Decisions To Gain Competitive Advantage
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From Big to Smart Data. How can Data Analytics support Strategic Decisions to gain Competitive Advantage?
Research Paper (postgraduate) from the year 2015 in the subject Business economics - Operations Research, grade: 1, University of Applied Sciences Essen, language: English, abstract: One of the biggest challenges currently and in the upcoming years is the amount of data generated worldwide, which will increase exponentially by factor 10. The challenge for business leaders in the era of Big Data will be to identify and to use the most relevant data for decision-making in the context of Strategic Management. This assignment analysis which relevance data analytics of Big respectively Smart Data nowadays has and how it can be utilized in enterprises to gain a higher degree of competitive advantage. Therefore a few selected examples and use cases are provided on the Corporate, Business and Functional level of Strategic Management. Business leaders are using data analytics to understand cost and revenue drivers, to evaluate risks and to predict trends to improve business performance and to foster innovation. Studies show, that Big Data will revolutionize business operations and change the way of doing business. Companies not dealing with Big Data will lose their competitive advantage. With a deeper understanding of customers’ behavior and demands through analysis of Big Data, companies can find new ways to approach existing and potential customers by improved or new products. Criticism related to this is the debate about data security and data privacy and the misuse of personal data.
Demystifying Big Data Analytics for Industries and Smart Societies
This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various industries and smart societies. What sets this book apart is its in-depth coverage of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems for precision agriculture. The book also delves into the use of big data analytics in healthcare, energy management, and agricultural development, among others. The authors have used clear and concise language, along with relevant examples and case studies, to help readers understand the complex concepts involved in big data analytics. Key Features: Comprehensive coverage of the fundamentals of big data analytics In-depth discussion of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems Practical examples and case studies to help readers understand complex concepts Coverage of the use of big data analytics in various industries, including healthcare, energy management, and agriculture Discussion of challenges and legal frameworks involved in big data analytics Clear and concise language that is easy to understand This book is a valuable resource for business owners, data analysts, students, and anyone interested in the field of big data analytics. It provides readers with the tools they need to leverage the power of big data and make informed decisions that can help their organizations succeed. Whether you are new to the field or an experienced practitioner, "Demystifying Big Data Analytics for Industries and Smart Societies" is must-read.
Enterprise Big Data Engineering, Analytics, and Management
The significance of big data can be observed in any decision-making process as it is often used for forecasting and predictive analytics. Additionally, big data can be used to build a holistic view of an enterprise through a collection and analysis of large data sets retrospectively. As the data deluge deepens, new methods for analyzing, comprehending, and making use of big data become necessary. Enterprise Big Data Engineering, Analytics, and Management presents novel methodologies and practical approaches to engineering, managing, and analyzing large-scale data sets with a focus on enterprise applications and implementation. Featuring essential big data concepts including data mining, artificial intelligence, and information extraction, this publication provides a platform for retargeting the current research available in the field. Data analysts, IT professionals, researchers, and graduate-level students will find the timely research presented in this publication essential to furthering their knowledge in the field.