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Data-Centric Business and Applications: Towards Software Development (Volume 4) (Lecture Notes on Data Engineering and Communications Technologies #40)
by Aneta Poniszewska-Marańda Natalia Kryvinska Stanisław Jarząbek Lech MadeyskiThis book explores various aspects of software creation and development as well as data and information processing. It covers relevant topics such as business analysis, business rules, requirements engineering, software development processes, software defect prediction, information management systems, and knowledge management solutions. Lastly, the book presents lessons learned in information and data management processes and procedures.
Data Classification: Algorithms and Applications (Chapman And Hall/crc Data Mining And Knowledge Discovery Ser. #35)
by Charu C. AggarwalComprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlyi
Data Clustering: Algorithms and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series #31)
by Charu C. Aggarwal Chandan K. ReddyResearch on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains.The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.
Data Clustering in C++: An Object-Oriented Approach
by Guojun GanData clustering is a highly interdisciplinary field, the goal of which is to divide a set of objects into homogeneous groups such that objects in the same group are similar and objects in different groups are quite distinct. Thousands of theoretical papers and a number of books on data clustering have been published over the past 50 years. However, few books exist to teach people how to implement data clustering algorithms. This book was written for anyone who wants to implement or improve their data clustering algorithms. Using object-oriented design and programming techniques, Data Clustering in C++ exploits the commonalities of all data clustering algorithms to create a flexible set of reusable classes that simplifies the implementation of any data clustering algorithm. Readers can follow the development of the base data clustering classes and several popular data clustering algorithms. Additional topics such as data pre-processing, data visualization, cluster visualization, and cluster interpretation are briefly covered.This book is divided into three parts-- Data Clustering and C++ Preliminaries: A review of basic concepts of data clustering, the unified modeling language, object-oriented programming in C++, and design patterns A C++ Data Clustering Framework: The development of data clustering base classes Data Clustering Algorithms: The implementation of several popular data clustering algorithms A key to learning a clustering algorithm is to implement and experiment the clustering algorithm. Complete listings of classes, examples, unit test cases, and GNU configuration files are included in the appendices of this book as well as in the downloadable resources. The only requirements to compile the code are a modern C++ compiler and the Boost C++ libraries.
Data Collection: Planning for and Collecting All Types of Data
by Cathy A. Stawarski Patricia Pulliam PhillipsData Collection Data Collection is the second of six books in the Measurement and Evaluation Series from Pfeiffer. The proven ROI Methodology--developed by the ROI Institute--provides a practical system for evaluation planning, data collection, data analysis, and reporting. All six books in the series offer the latest tools, most current research, and practical advice for measuring ROI in a variety of settings. Data Collection offers an effective process for collecting data that is essential to the implementation of the ROI Methodology. The authors outline the techniques, processes, and critical issues involved in successful data collection. The book examines the various methods of data collection, including questionnaires, interviews, focus groups, observation, action plans, performance contracts, and monitoring records. Written for evaluators, facilitators, analysts, designers, coordinators, and managers, Data Collection is a valuable guide for collecting data that are adequate in quantity and quality to produce a complete and credible analysis.
Data Collection in Fragile States: Innovations from Africa and Beyond
by Johannes Hoogeveen Utz Pape‘This open access book addresses an urgent issue on which little organized information exists. It reflects experience in Africa but is highly relevant to other fragile states as well.’ —Constantine Michalopoulos, John Hopkins University, USA and former Director of Economic Policy and Co-ordination at the World BankFragile countries face a triple data challenge. Up-to-date information is needed to deal with rapidly changing circumstances and to design adequate responses. Yet, fragile countries are among the most data deprived, while collecting new information in such circumstances is very challenging. This open access book presents innovations in data collection developed with decision makers in fragile countries in mind. Looking at innovations in Africa from mobile phone surveys monitoring the Ebola crisis, to tracking displaced people in Mali, this collection highlights the challenges in data collection researchers face and how they can be overcome.
Data Conscience: Algorithmic Siege on our Humanity
by Brandeis Hill MarshallDATA CONSCIENCE ALGORITHMIC S1EGE ON OUR HUM4N1TY EXPLORE HOW D4TA STRUCTURES C4N HELP OR H1NDER SOC1AL EQU1TY Data has enjoyed ‘bystander’ status as we’ve attempted to digitize responsibility and morality in tech. In fact, data’s importance should earn it a spot at the center of our thinking and strategy around building a better, more ethical world. It’s use—and misuse—lies at the heart of many of the racist, gendered, classist, and otherwise oppressive practices of modern tech. In Data Conscience: Algorithmic Siege on our Humanity, computer science and data inclusivity thought leader Dr. Brandeis Hill Marshall delivers a call to action for rebel tech leaders, who acknowledge and are prepared to address the current limitations of software development. In the book, Dr. Brandeis Hill Marshall discusses how the philosophy of “move fast and break things” is, itself, broken, and requires change. You’ll learn about the ways that discrimination rears its ugly head in the digital data space and how to address them with several known algorithms, including social network analysis, and linear regression A can’t-miss resource for junior-level to senior-level software developers who have gotten their hands dirty with at least a handful of significant software development projects, Data Conscience also provides readers with: Discussions of the importance of transparency Explorations of computational thinking in practice Strategies for encouraging accountability in tech Ways to avoid double-edged data visualization Schemes for governing data structures with law and algorithms
Data Conversion: Calculating the Monetary Benefits
by Patricia Pulliam Phillips Holly BurkettThis book tackles the third major challenge and the second most difficult step in the ROI methodology: converting data to monetary values. When a particular project or program is connected to a business measure, the next logical question is: what is the monetary value of that impact? For ROI analysis, it is at this critical point where the monetary benefits are developed to compare to the costs of the program to calculate the ROI. Includes: the importance of converting data to monetary value; preliminary issues; standard values: the standard values: where to find them; using internal experts, using external databases; linking with other measures; using estimates; when to abandon conversion efforts and leave data as intangible, analyzing the intangibles; and reporting the intangibles.
Data Crush: How the Information Tidal Wave Is Driving New Business Opportunities
by Christopher SurdakThe Internet used to be a tool for telling your customers about your business. Now its real value lies in what it tells you about them. Every move your customers make online can be tracked, catalogued, and analyzed to better understand their preferences and predict their future behavior. And with mobile technology like smartphones, customers are online almost every second of every day. The companies that succeed going forward will be those that learn to leverage this torrent of information--without being drowned by it. Balancing examples from giants like Amazon, Home Depot, and Ford with newer players like Rovio, Groupon, and scores of niche-market winners, Data Crush examines the forces behind the explosive growth in data and reveals how the most innovative companies are responding to this challenge. The book clarifies the key drivers: the proliferation of "big data" generated by a never-ending range of online activities (and the mobility that enables much of it); the seemingly infinite array of digital commerce and entertainment pathways; and the rising growth of Cloud computing. These and other factors combine to create an overwhelming universe of valuable information--all constantly updated in real time with billions of mouse clicks each day. It's daunting, but with this onslaught of information comes tremendous opportunity--and Data Crush will help you make sense of it all.
Data Culture: Develop An Effective Data-Driven Organization
by Dr Shorful IslamOrganizations often start their data journey by either procuring the technology or hiring the people. However, without an effective data-driven culture in place, they can struggle to derive value from their investments.Data Culture explores how data leaders can develop and nurture a data-driven culture tailored to their organization's needs. It outlines the types of data leadership and teams needed and the key building blocks for success, such as team recruitment, building and training, leadership, process, behavioural change management, developing, sustaining and measuring a data culture, company values and everyday decision making. It also explores the nuances of how different types of data cultures work with different types of companies, what to avoid and the differences between building a data culture from scratch and changing an existing data culture from within.With this hands-on guide, senior data leader Shorful Islam takes readers through how to successfully establish or change a data culture, sharing his expertise in behavioural change psychology and two decades of experience in fostering data culture in organizations. Supported throughout by real-world examples and cases, this will be an essential read for all data leaders and anyone involved in developing a data-driven organizational culture.
Data Cultures in Higher Education: Emergent Practices and the Challenge Ahead (Higher Education Dynamics #59)
by Juliana E. Raffaghelli Albert SangràThis collection focuses on the role of higher education institutions concerning datafication as a complex phenomenon. It explores how the universities can develop data literac(ies) shaping tomorrow skills and “formae mentis” to face the most deleterious effects of datafication, but also to engage in creative and constructive ways with data. Notably, the book spots data practices within the two most relevant sides of academics’ professional practice, namely, research and teaching. Hence, the collection seeks to reflect on faculty’s professional learning about data infrastructures and practices.The book draws on a range of studies covering the higher education response to the several facets of data in society, from data surveillance and the algorithmic control of human behaviour to empowerment through the use of open data. The research reported ranges from literature overviews to multi-case and in-depth case studies illustrating institutional and educational responses to different problems connected to data. The ultimate intention is to provide conceptual bases and practical examples relating to universities’ faculty development policies to overcome data practices and discourses' fragmentation and contradictions: in a nutshell, to build “fair data cultures” in higher education.
Data Curious: Applying Agile Analytics for Better Business Decisions
by Carl Allchin Sarah NabelsiData has been a missing part of most academic curriculums for a long time, and we're all being affected. During challenging times, creating a data-informed culture can help you pivot quickly or prevent expensive missteps. Developing a data curious organization will take advantage of the burgeoning data resources available as a result of increasing digitalization.With this book, authors Carl Allchin and Sarah Nabelsi show today's business professionals how to become data empowered. These tech-savvy business professionals will learn data literacy fundamentals—from understanding the possibilities to asking the right questions. You'll discover how to make the right technology choices and avoid pitfalls that could put your career and company at risk.Discover what an agile, empowered, data-driven organization should look likeExamine how to use data in new ways to help your business come to lifeLearn key terms and concepts around data management and analyticsUnderstand the differences between spreadsheet analysis and a data analytics pipelineGet advice for working with data scientists and explore ways to mitigate the IT department's concerns
Data Democratization with Domo: Bring together every component of your business to make better data-driven decisions using Domo
by Jeff BurtenshawOvercome data challenges at record speed and cloud-scale that optimize businesses by transforming raw data into dashboards and apps which democratize data consumption, supercharging results with the cloud-based solution, DomoKey FeaturesAcquire data and automate data pipelines quickly for any data volume, variety, and velocityPresent relevant stories in dashboards and custom apps that drive favorable outcomes using DomoShare information securely and govern content including Domo content embedded in other toolsBook DescriptionDomo is a power-packed business intelligence (BI) platform that empowers organizations to track, analyze, and activate data in record time at cloud scale and performance. Data Democratization with Domo begins with an overview of the Domo ecosystem. You'll learn how to get data into the cloud with Domo data connectors and Workbench; profile datasets; use Magic ETL to transform data; work with in-memory data sculpting tools (Data Views and Beast Modes); create, edit, and link card visualizations; and create card drill paths using Domo Analyzer. Next, you'll discover options to distribute content with real-time updates using Domo Embed and digital wallboards. As you advance, you'll understand how to use alerts and webhooks to drive automated actions. You'll also build and deploy a custom app to the Domo Appstore and find out how to code Python apps, use Jupyter Notebooks, and insert R custom models. Furthermore, you'll learn how to use Auto ML to automatically evaluate dozens of models for the best fit using SageMaker and produce a predictive model as well as use Python and the Domo Command Line Interface tool to extend Domo. Finally, you'll learn how to govern and secure the entire Domo platform. By the end of this book, you'll have gained the skills you need to become a successful Domo master.What you will learnUnderstand the Domo cloud data warehouse architecture and platformAcquire data with Connectors, Workbench, and Federated QueriesSculpt data using no-code Magic ETL, Data Views, and Beast ModesProfile data with the Data Dictionary, Data Profile, and Usage toolsUse a storytelling pattern to create dashboards with Domo StoriesCreate, share, and monitor custom alerts activated using webhooksCreate custom Domo apps, use the Domo CLI, and code with the Python APIAutomate model operations with Python programming and R scriptingWho this book is forThis book is for BI developers, ETL developers, and Domo users looking for a comprehensive, end-to-end guide to exploring Domo features for BI. Chief data officers, data strategists, architects, and BI managers interested in a new paradigm for integrated cloud data storage, data transformation, storytelling, content distribution, custom app development, governance, and security will find this book useful. Business analysts seeking new ways to tell relevant stories to shape business performance will also benefit from this book. A basic understanding of Domo will be helpful.
The Data Detective: Ten Easy Rules to Make Sense of Statistics
by Tim HarfordFrom &“one of the great (greatest?) contemporary popular writers on economics&” (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics.Today we think statistics are the enemy, numbers used to mislead and confuse us. That&’s a mistake, Tim Harford says in The Data Detective. We shouldn&’t be suspicious of statistics—we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often &“the only way of grasping much of what is going on around us.&” If we can toss aside our fears and learn to approach them clearly—understanding how our own preconceptions lead us astray—statistics can point to ways we can live better and work smarter.As &“perhaps the best popular economics writer in the world&” (New Statesman), Tim Harford is an expert at taking complicated ideas and untangling them for millions of readers. In The Data Detective, he uses new research in science and psychology to set out ten strategies for using statistics to erase our biases and replace them with new ideas that use virtues like patience, curiosity, and good sense to better understand ourselves and the world. As a result, The Data Detective is a big-idea book about statistics and human behavior that is fresh, unexpected, and insightful.
Data Driven: An Introduction to Management Consulting in the 21st Century (Management for Professionals)
by Jeremy David CuruksuThis book is a “scientific” introduction to management consulting that covers elementary and more advanced concepts, such as strategy and client-relationship. It discusses the emerging role of information technologies in consulting activities and introduces the essential tools in data science, assuming no technical background. Drawing on extensive literature reviews with more than 200 peer reviewed articles, reports, books and surveys referenced, this book has at least four objectives: to be scientific, modern, complete and concise. An interactive version of some sections (industry snapshots, method toolbox) is freely accessible at econsultingdata.com.
Data Driven
by Jenny DearbornA "how-to" guide to boosting sales through predictive andprescriptive analytics Data Driven is a uniquely practical guide to increasingsales success, using the power of data analytics. Written by one ofthe world's leading authorities on the topic, this book shows youhow to transform the corporate sales function by leveraging bigdata into better decision-making, more informed strategy, andincreased effectiveness throughout the organization. Engaging andinformative, this book tells the story of a newly hired sales chiefunder intense pressure to deliver higher performance from her team,and how data analytics becomes the ultimate driver behind the salesfunction turnaround. Each chapter features insightful commentaryand practical notes on the points the story raises, and one entirechapter is devoted solely to laying out the Prescriptive ActionModel step-by-step giving you the actionable guidance you need toput it into action in your own organization.Predictive and prescriptive analytics is poised to changecorporate sales, and companies that fail to adapt to the newrealities and adopt the new practices will be left behind. Thisbook explains why the Prescriptive Action Model is the keycorporate sales weapon of the 21st Century, and how you canimplement this dynamic new resource to bring value to yourbusiness.Exploit one of the last remaining sources of competitiveadvantageRe-engineer the sales function to optimize success ratesImplement a more effective analytics model to drive efficientchangeBoost operational effectiveness and decision making with bigdataThere are fewer competitive edges to gain than ever before. Theonly thing that's left is to execute business with maximumefficiency and make the smartest business decisions possible.Predictive analytics is the essential method behind this newstandard, and Data Driven is the practical guide tocomplete, efficient implementation.
Data Driven: Truckers, Technology, and the New Workplace Surveillance
by Karen LevyA behind-the-scenes look at how digital surveillance is affecting the trucking way of lifeLong-haul truckers are the backbone of the American economy, transporting goods under grueling conditions and immense economic pressure. Truckers have long valued the day-to-day independence of their work, sharing a strong occupational identity rooted in a tradition of autonomy. Yet these workers increasingly find themselves under many watchful eyes. Data Driven examines how digital surveillance is upending life and work on the open road, and raises crucial questions about the role of data collection in broader systems of social control.Karen Levy takes readers inside a world few ever see, painting a bracing portrait of one of the last great American frontiers. Federal regulations now require truckers to buy and install digital monitors that capture data about their locations and behaviors. Intended to address the pervasive problem of trucker fatigue by regulating the number of hours driven each day, these devices support additional surveillance by trucking firms and other companies. Traveling from industry trade shows to law offices and truck-stop bars, Levy reveals how these invasive technologies are reconfiguring industry relationships and providing new tools for managerial and legal control—and how truckers are challenging and resisting them.Data Driven contributes to an emerging conversation about how technology affects our work, institutions, and personal lives, and helps to guide our thinking about how to protect public interests and safeguard human dignity in the digital age.
Data Driven
by Dj Patil Hilary MasonSucceeding with data isn’t just a matter of putting Hadoop in your machine room, or hiring some physicists with crazy math skills. It requires you to develop a data culture that involves people throughout the organization. In this O’Reilly report, DJ Patil and Hilary Mason outline the steps you need to take if your company is to be truly data-driven—including the questions you should ask and the methods you should adopt.You’ll not only learn examples of how Google, LinkedIn, and Facebook use their data, but also how Walmart, UPS, and other organizations took advantage of this resource long before the advent of Big Data. No matter how you approach it, building a data culture is the key to success in the 21st century.You’ll explore:Data scientist skills—and why every company needs a SpockHow the benefits of giving company-wide access to data outweigh the costsWhy data-driven organizations use the scientific method to explore and solve data problemsKey questions to help you develop a research-specific process for tackling important issuesWhat to consider when assembling your data teamDeveloping processes to keep your data team (and company) engagedChoosing technologies that are powerful, support teamwork, and easy to use and learn
Data Driven
by Thomas C. RedmanYour company's data has the potential to add enormous value to every facet of the organization -- from marketing and new product development to strategy to financial management. Yet if your company is like most, it's not using its data to create strategic advantage. Data sits around unused -- or incorrect data fouls up operations and decision making.In Data Driven, Thomas Redman, the "Data Doc," shows how to leverage and deploy data to sharpen your company's competitive edge and enhance its profitability. The author reveals:· The special properties that make data such a powerful asset· The hidden costs of flawed, outdated, or otherwise poor-quality data· How to improve data quality for competitive advantage· Strategies for exploiting your data to make better business decisions· The many ways to bring data to market· Ideas for dealing with political struggles over data and concerns about privacy rightsYour company's data is a key business asset, and you need to manage it aggressively and professionally. Whether you're a top executive, an aspiring leader, or a product-line manager, this eye-opening book provides the tools and thinking you need to do that.
Data-Driven Alexa Skills: Voice Access to Rich Data Sources for Enterprise Applications
by Simon A. KingabyDesign and build innovative, custom, data-driven Alexa skills for home or business. Working through several projects, this book teaches you how to build Alexa skills and integrate them with online APIs. If you have basic Python skills, this book will show you how to build data-driven Alexa skills. You will learn to use data to give your Alexa skills dynamic intelligence, in-depth knowledge, and the ability to remember. Data-Driven Alexa Skills takes a step-by-step approach to skill development. You will begin by configuring simple skills in the Alexa Skill Builder Console. Then you will develop advanced custom skills that use several Alexa Skill Development Kit features to integrate with lambda functions, Amazon Web Services (AWS), and Internet data feeds. These advanced skills enable you to link user accounts, query and store data using a NoSQL database, and access real estate listings and stock prices via web APIs.What You Will LearnSet up and configure your development environment properly the first timeBuild Alexa skills quickly and efficiently using Agile tools and techniquesCreate a variety of data-driven Alexa skills for home and businessAccess data from web applications and Internet data sources via their APIsTest with unit-testing frameworks throughout the development life cycleManage and query your data using the DynamoDb NoSQL database enginesWho This Book Is ForDevelopers who wish to go beyond Hello World and build complex, data-driven applications on Amazon's Alexa platform; developers who want to learn how to use Lambda functions, the Alexa Skills SDK, Alexa Presentation Language, and Alexa Conversations; developers interested in integrating with public APIs such as real estate listings and stock market prices. Readers will need to have basic Python skills.
Data-driven Analytics for Sustainable Buildings and Cities: From Theory to Application (Sustainable Development Goals Series)
by Xingxing ZhangThis book explores the interdisciplinary and transdisciplinary fields of energy systems, occupant behavior, thermal comfort, air quality and economic modelling across levels of building, communities and cities, through various data analytical approaches. It highlights the complex interplay of heating/cooling, ventilation and power systems in different processes, such as design, renovation and operation, for buildings, communities and cities. Methods from classical statistics, machine learning and artificial intelligence are applied into analyses for different building/urban components and systems. Knowledge from this book assists to accelerate sustainability of the society, which would contribute to a prospective improvement through data analysis in the liveability of both built and urban environment. This book targets a broad readership with specific experience and knowledge in data analysis, energy system, built environment and urban planning. As such, it appeals to researchers, graduate students, data scientists, engineers, consultants, urban scientists, investors and policymakers, with interests in energy flexibility, building/city resilience and climate neutrality.
Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers (Chapman & Hall/CRC Big Data Series)
by Chengliang Yang Chris Delcher Elizabeth Shenkman Sanjay RankaHealth care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem. Key Features: Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codes Provides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizers Presents descriptive data driven methods for the high utilizer population Identifies a best-fitting linear and tree-based regression model to account for patients’ acute and chronic condition loads and demographic characteristics
Data-Driven Company: Moderne und integrierte Ansätze, um datengetrieben zu werden
by Sven-Erik WillrichDaten werden für Unternehmen immer wichtiger. Gleichzeitig mangelt es an Best Practices und Leitfäden, wie klassische mit modernen Ansätzen wie Data Mesh oder Data Fabric zu einem anwendbaren Framework integriert werden können. Hierzu werden die Themen Organisationsdesign, Datenstrategie / -management und Enterprise Architecture auf theoretische und pragmatische Weise verbunden. Das Buch präsentiert Ziele, ein Data Operating Model sowie datenstrategische Ansätze für eine Data-Driven Company. Hervorzuheben sind dabei die zahlreichen Abbildungen aus diesem Buch, die die komplexen Zusammenhänge anschaulich machen und das Lesen unterstützen. Zielgruppe Mit diesen Inhalten richtet sich das Buch an Führungskräfte, Experten, Berater und weitere Personen, die einen Bezug zur IT und Daten haben beziehungsweise diesen entwickeln möchten. Durch den niedrigschwelligen Einstieg und gleichzeitigen Tiefgang in die ausgewählten Themen adressiert es sowohl Einsteiger als auch erfahrene Datenexperten. Autor Dr. Sven-Erik Willrich ist ein erfahrener Experte im Bereich IT und Datenmanagement. Mit seinem Hintergrund in Wirtschaftsinformatik und langjähriger Beratungserfahrung bringt er sowohl theoretisches Wissen als auch praxisorientierte Lösungsansätze ein. Als Dozent und Redner im Bereich Digitalisierung teilt er regelmäßig seine Expertise.
Data-Driven Customer Engagement: Mastering MarTech Strategies for Success
by Ralf StraussEmbark on a journey through the rapidly evolving landscape of Marketing Technology (MarTech) with this comprehensive guide. From understanding the strategic imperatives driving MarTech adoption to navigating the intricacies of data-driven customer interaction, this book provides invaluable insights and practical strategies. Explore topics ranging from budget allocation and market potential to data readiness and GDPR compliance, gaining a deep understanding of key concepts and best practices. Whether you're grappling with the complexities of AI integration or seeking to optimize measurement and KPIs, this book equips you with the knowledge and tools needed to thrive in today's digital marketing environment. With decades of industry experience, Ralf Strauss offers in this book a roadmap for success, empowering marketers to navigate the challenges and seize the opportunities presented by MarTech innovation.
Data-Driven Customer Experience Transformation: Optimize Your Omnichannel Approach
by null Mohamed ZakiWe are living in an experience-driven economy, where the customer's experience is paramount and even beloved brands risk losing market share due to a single negative customer experience.In our technology-led, omnichannel environment, one of the biggest risks for brands is a lack of consistency in their customer experience across digital, physical and social channels. Data-driven Customer Experience Transformation provides insights and frameworks for creating delightful customer experiences across all three channels, by leveraging data and the latest technologies. Using cutting-edge research from the Cambridge Service Alliance, at the University of Cambridge, this book explores the importance of omnichannel customer-centricity across all sectors and takes you on a journey from setting your strategy, through designing and managing your customer experiences in real-time. It explores how AI can be used to identify opportunities and predict engagement, as well as how to use data to understand customer loyalty, forge stronger customer relationships and drive growth.By combining academic rigour with real-world examples from leading companies such as Microsoft, KFC and Emirates Airline, this book is the ultimate guide to designing and implementing an exceptional data-driven customer experience across all channels, whether you work in B2B, B2C or public services.