The Economics of Data, Analytics, and Digital Transformation

Author: Bill Schmarzo
Publisher: Packt Publishing Ltd
ISBN: 1800569130
Category : Computers
Languages : en
Pages : 261

Book Description
Build a continuously learning and adapting organization that can extract increasing levels of business, customer and operational value from the amalgamation of data and advanced analytics such as AI and Machine Learning Key Features Master the Big Data Business Model Maturity Index methodology to transition to a value-driven organizational mindset Acquire implementable knowledge on digital transformation through 8 practical laws Explore the economics behind digital assets (data and analytics) that appreciate in value when constructed and deployed correctly Book Description In today's digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization's data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise. The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company's operations through AI and machine learning. By the end of the book, you will have the tools and techniques to drive your organization's digital transformation. Here are a few words from Dr. Kirk Borne, Data Scientist and Executive Advisor at Booz Allen Hamilton, about the book: "Data analytics should first and foremost be about action and value. Consequently, the great value of this book is that it seeks to be actionable. It offers a dynamic progression of purpose-driven ignition points that you can act upon." What you will learn Train your organization to transition from being data-driven to being value-driven Navigate and master the big data business model maturity index Learn a methodology for determining the economic value of your data and analytics Understand how AI and machine learning can create analytics assets that appreciate in value the more that they are used Become aware of digital transformation misconceptions and pitfalls Create empowered and dynamic teams that fuel your organization's digital transformation Who this book is for This book is designed to benefit everyone from students who aspire to study the economic fundamentals behind data and digital transformation to established business leaders and professionals who want to learn how to leverage data and analytics to accelerate their business careers.

Data Analysis for Business, Economics, and Policy

Author: Gábor Békés
Publisher: Cambridge University Press
ISBN: 1108483011
Category : Business & Economics
Languages : en
Pages : 741

Book Description
A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

Big Data

Author: Bill Schmarzo
Publisher: John Wiley & Sons
ISBN: 1118740009
Category : Business & Economics
Languages : en
Pages : 245

Book Description
Leverage big data to add value to your business Social media analytics, web-tracking, and other technologies help companies acquire and handle massive amounts of data to better understand their customers, products, competition, and markets. Armed with the insights from big data, companies can improve customer experience and products, add value, and increase return on investment. The tricky part for busy IT professionals and executives is how to get this done, and that's where this practical book comes in. Big Data: Understanding How Data Powers Big Business is a complete how-to guide to leveraging big data to drive business value. Full of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved, as well as how to find areas of the organization that can take full advantage of big data. Shows how to decompose current business strategies in order to link big data initiatives to the organization’s value creation processes Explores different value creation processes and models Explains issues surrounding operationalizing big data, including organizational structures, education challenges, and new big data-related roles Provides methodology worksheets and exercises so readers can apply techniques Includes real-world examples from a variety of organizations leveraging big data Big Data: Understanding How Data Powers Big Business is written by one of Big Data's preeminent experts, William Schmarzo. Don't miss his invaluable insights and advice.

Big Data MBA

Author: Bill Schmarzo
Publisher: John Wiley & Sons
ISBN: 1119238846
Category : Computers
Languages : en
Pages : 314

Book Description
Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions your business is trying to make, the hypotheses you need to test, and the predictions you need to produce. Business stakeholders no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity. Understand where and how to leverage big data Integrate analytics into everyday operations Structure your organization to drive analytic insights Optimize processes, uncover opportunities, and stand out from the rest Help business stakeholders to “think like a data scientist” Understand appropriate business application of different analytic techniques If you want data to transform your business, you need to know how to put it to use. Big Data MBA shows you how to implement big data and analytics to make better decisions.

Digitalization, Digital Transformation and Sustainability in the Global Economy

Author: Tim A. Herberger
Publisher: Springer Nature
ISBN: 303077340X
Category : Business & Economics
Languages : en
Pages : 185

Book Description
This book highlights the opportunities and risks of digitalization and digital transformation for our global economy at both the micro and macro level. Experts from various fields, presenting both scientific and practice-oriented perspectives, identify and critically analyse areas of tension and development potential in connection with new business models and sustainability efforts in our society. It is divided into four parts, the first of which highlights new technological advances in areas such as blockchain, cryptocurrencies and fintechs, and discusses the challenges they pose for public regulation. The second part illustrates digitalization’s effects on and potential advantages for public welfare, focusing on key areas such as education, health and smart cities. The third part focuses on challenges for corporate and public management, particularly for leadership and Corporate Social Responsibility, while the fourth part discusses new dimensions for analysis based on big data. The contributions gathered here are partly an outcome of the International Conference on Digitalization, Digital Transformation and Sustainability held in Budapest in October 2020 and generously supported by the Hanns Seidel Foundation.

Digital Transformation of the Economy: Challenges, Trends and New Opportunities

Author: Svetlana Ashmarina
Publisher: Springer
ISBN: 3030113671
Category : Technology & Engineering
Languages : en
Pages : 721

Book Description
This book gathers the best contributions from the conference “Digital Transformation of the Economy: Challenges, Trends and New Opportunities”, which took place in Samara, Russian Federation, on May 29–31, 2018. Organized by Samara State University of Economics (Samara), Russia, the conference was devoted to issues of the digital economy.Presenting international research on the impact of digitalization on economic development, it includes topics such as the transformation of the institutional environment under the influence of informatization, the comparative analysis of the digitalization development in different countries, and modeling the dependence of the rate of change in the economy on the level of the digitalization penetration into various spheres of human activity. It also covers business-process transformation in the context of digitalization and changes in the structure of employment and personnel training for the digital economy. Lastly, it addresses the issue of ensuring information security and dealing with information risks for both individual enterprises and national economies as a whole. The book appeals to both students and researchers whose interests include the development of the digital economy, as well as to managers and professionals who integrate digital solutions into real-world business practice.

Data Science for Economics and Finance

Author: Sergio Consoli
Publisher: Springer Nature
ISBN: 3030668916
Category : Application software
Languages : en
Pages : 357

Book Description
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Big Data

Author: Viktor Mayer-Schönberger
Publisher: Houghton Mifflin Harcourt
ISBN: 0544002695
Category : Business & Economics
Languages : en
Pages : 257

Book Description
A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.

Digital Transformation and Innovative Services for Business and Learning

Author: Sandhu, Kamaljeet
Publisher: IGI Global
ISBN: 179985177X
Category : Business & Economics
Languages : en
Pages : 282

Book Description
In a world dependent on digital technologies, business corporations continually try to stay ahead of their competitors by adopting the most updated technology into their business processes. Many companies are adopting digital transformation models, data analytics, big data, data empowerment, and data sharing as key strategies and as service disruptors for information delivery and record management. Higher education institutions have adopted digital service innovation as a core to driving their business processes. Such services are key to ensuring efficiency and improving organizational performance. Digital Transformation and Innovative Services for Business and Learning is a collection of innovative research on the latest digital services and their role in supporting the digital transformation of businesses and education. While highlighting topics including brand equality, digital banking, and generational workforce, this book is ideally designed for managers, executives, IT consultants, industry professionals, academicians, researchers, and students.

Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions

Author: Matt Taddy
Publisher: McGraw Hill Professional
ISBN: 1260452786
Category : Business & Economics
Languages : en
Pages : 350

Book Description
Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling Understand how use ML tools in real world business problems, where causation matters more that correlation Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.