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This volume collects the contributions presented at the conference “Data-driven Decision Making” organized by the Italian Association for Applied Statistics, held in Genoa from 12 to 14 September 2022. The papers cover a broad range of topics, with a common thread: the use of statistical methods to support decision-making both in public administrations and in private companies.
This book aims to explain Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focused on specific issues. It explores the concepts of database technology, machine learning, knowledge-based system, high performance computing, information retrieval, finding patterns hidden in large datasets and data visualization. Also, it presents various paradigms including pattern mining, clustering, classification, and data analysis. Overall aim is to provide technical solutions in the field of data analytics and data mining. Features: Covers descriptive statistics with respect to predictive analytics and business analytics. Discusses different data analytics platforms for real-time applications. Explain SMART business models. Includes algorithms in data sciences alongwith automated methods and models. Explores varied challenges encountered by researchers and businesses in the realm of real-time analytics. This book aims at researchers and graduate students in data analytics, data sciences, data mining, and signal processing.
Making decisions is an inevitable activity in life, whether at a personal level or at an institutional level. Everyone is faced with situations where a decision has to be made. There are two ways of treating such situations. One way is to consider the situation to be posing a challenge, where one is more worried about consequences of making a wrong decision. The other, obviously, is to consider the situation to be offering an opportunity, where one is interested in maximizing the benefits by making the right decision.
In today's competitive market, a manager must be able to look at data, understand it, analyze it, and then interpret it to design a smart business strategy. Big data is also a valuable source of information on how customers interact with firms through various mediums such as social media platforms, online reviews, and many more. The applications and uses of business analytics are numerous and must be further studied to ensure they are utilized appropriately. Data-Driven Approaches for Effective Managerial Decision Making investigates management concepts and applications using data analytics and outlines future research directions. The book also addresses contemporary advancements and innovations in the field of management. Covering key topics such as big data, business intelligence, and artificial intelligence, this reference work is ideal for managers, business owners, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.
This book delves into contemporary business analytics techniques across sectors for critical decision-making. It combines data, mathematical and statistical models, and information technology to present alternatives for decision evaluation. Offering systematic mechanisms, it explores business contexts, factors, and relationships to foster competitiveness. Beyond managerial perspectives, it includes contributions from professionals, academics, and scholars worldwide, delivering comprehensive knowledge and skills through diverse viewpoints, cases, and applications of analytical tools. As an international business science reference, it targets professionals, academics, researchers, doctoral scholars, postgraduate students, and research organizations seeking a nuanced understanding of modern business analytics.
In the ever-evolving landscape of business, the power of data-driven decision making has become paramount. In the compelling book, "DATA-DRIVEN DECISION MAKING: Leveraging Analytics for Smarter Business Choices," Datawhiz takes you on a captivating journey into the world of data and analytics, unraveling the secrets to making informed choices that propel success. Discover how to navigate the complex realm of data and leverage cutting-edge analytics techniques to gain a competitive edge. Through expert guidance and real-world examples, Datawhiz illuminates the path to unlocking hidden insights and making data-driven decisions that revolutionize your business trajectory. With an emphasis on SEO optimization, this book ensures discoverability with critical keywords and targeted content, making it a must-read resource for individuals and organizations seeking to excel in data-driven decision making. From data quality assurance to predictive analytics, Datawhiz provides a comprehensive guide to mastering the art and science of data analysis. Unleash the power of data to gain deep customer insights, optimize operational efficiency, and drive revenue growth. Whether you're a business leader, entrepreneur, or aspiring data analyst, this book equips you with the tools and knowledge to harness the full potential of analytics and make smarter choices that propel your success. Don't miss your chance to embark on this thrilling journey into the world of data-driven decision making. With Datawhiz's engaging storytelling, practical strategies, and actionable advice, you'll transform raw data into actionable insights that fuel your business's growth. Embrace the era of data-driven success and seize opportunities that others overlook. Get your copy of "DATA-DRIVEN DECISION MAKING: Leveraging Analytics for Smarter Business Choices" today and unlock a world of possibilities in the data-driven era. Empower yourself with the knowledge, skills, and confidence to make data-driven decisions that propel your business to new heights.
This book presents a framework for developing an analytics strategy that includes a range of activities, from problem definition and data collection to data warehousing, analysis, and decision making. The authors examine best practices in team analytics strategies such as player evaluation, game strategy, and training and performance. They also explore the way in which organizations can use analytics to drive additional revenue and operate more efficiently. The authors provide keys to building and organizing a decision intelligence analytics that delivers insights into all parts of an organization. The book examines the criteria and tools for evaluating and selecting decision intelligence analytics technologies and the applicability of strategies for fostering a culture that prioritizes data-driven decision making. Each chapter is carefully segmented to enable the reader to gain knowledge in business intelligence, decision making and artificial intelligence in a strategic management context.
Data plays a vital role in different parts of our lives. In the world of big data, and policy determined by a variety of statistical artifacts, discussions around the ethics of data gathering, manipulation and presentation are increasingly important. Ethics in Statistics aims to make a significant contribution to that debate. The processes of gathering data through sampling, summarising of the findings, and extending results to a population, need to be checked via an ethical prospective, as well as a statistical one. Statistical learning without ethics can be harmful for mankind. This edited collection brings together contributors in the field of data science, data analytics and statistics, to share their thoughts about the role of ethics in different aspects of statistical learning.