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| forrester wave data management for analytics: Secure Data Management Willem Jonker, Milan Petković, 2014-05-14 This book constitutes the refereed proceedings of the 10th VLDB Workshop on Secure Data Management held in Trento, Italy, on August 30, 2013. The 15 revised full papers and one keynote paper presented were carefully reviewed and selected from various submissions. The papers are organized in technical papers and 10 vision papers which address key challenges in secure data management and indicate interesting research questions. |
| forrester wave data management for analytics: Digital Marketing Analytics Chuck Hemann, Ken Burbary, 2018-04-23 Distill Maximum Value from Your Digital Data! Do It Now! Why hasn’t all that data delivered a whopping competitive advantage? Because you’ve barely begun to use it, that’s why! Good news: neither have your competitors. It’s hard! But digital marketing analytics is 100% doable, it offers colossal opportunities, and all of the data is accessible to you. Chuck Hemann and Ken Burbary will help you chop the problem down to size, solve every piece of the puzzle, and integrate a virtually frictionless system for moving from data to decision, action to results! Scope it out, pick your tools, learn to listen, get the metrics right, and then distill your digital data for maximum value for everything from R&D to customer service to social media marketing! Prioritize—because you can’t measure and analyze everything Use analysis to craft experiences that profoundly reflect each customer’s needs, expectations, and behaviors Measure real digital media ROI: sales, leads, and customer satisfaction Track the performance of all paid, earned, and owned digital channels Leverage digital data way beyond PR and marketing: for strategic planning, product development, and HR Start optimizing digital content in real time Implement advanced tools, processes, and algorithms for accurately measuring influence Make the most of surveys, focus groups, and offline research synergies Focus new marketing investments where they’ll deliver the most value • Identify and understand your most important audiences across the digital ecosystem “Chuck and Ken lead marketers clearly and efficiently through the minefield of digital marketing measurement. And they do so with a lightness of touch and absence of jargon so rare in this overhyped, much-misunderstood ecosystem.” — Sam Knowles, Founder & MD of Insight Agents; author of Narrative by Numbers: How to Tell Powerful & Purposeful Stories with Data |
| forrester wave data management for analytics: Analytics and Data Science Amit V. Deokar, Ashish Gupta, Lakshmi S. Iyer, Mary C. Jones, 2017-10-05 This book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data. The chapters examine the role of analytics and data science to create, spread, develop and utilize analytics applications for practice. Selected chapters provide a good balance between discussing research advances and pedagogical tools in key topic areas in analytics and data science in a systematic manner. This book also focuses on several business applications of these emerging technologies in decision making, i.e., business analytics. The chapters in Analytics and Data Science: Advances in Research and Pedagogy are written by leading academics and practitioners that participated at the Business Analytics Congress 2015. Applications of analytics and data science technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination of the impact of these technologies and applications on business and society. As organizations in various sectors formulate their IT strategies and investments, it is imperative to understand how various analytics and data science approaches contribute to the improvements in organizational information processing and decision making. Recent advances in computational capacities coupled by improvements in areas such as data warehousing, big data, analytics, semantics, predictive and descriptive analytics, visualization, and real-time analytics have particularly strong implications on the growth of analytics and data science. |
| forrester wave data management for analytics: Modern Data Strategy Mike Fleckenstein, Lorraine Fellows, 2018-02-12 This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others. It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy. This provides the user with a good understanding of what a data strategy is and its limits. Critical to a data strategy is the incorporation of one or more data management domains. Chapters on key data management domains—data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy. The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues. This book is intended for business users who work with data, who need to manage one or more aspects of the organization’s data, and who want to foster an integrated approach for how enterprise data is managed. This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management. |
| forrester wave data management for analytics: Unstructured Data Analytics Jean Paul Isson, 2018-03-02 Turn unstructured data into valuable business insight Unstructured Data Analytics provides an accessible, non-technical introduction to the analysis of unstructured data. Written by global experts in the analytics space, this book presents unstructured data analysis (UDA) concepts in a practical way, highlighting the broad scope of applications across industries, companies, and business functions. The discussion covers key aspects of UDA implementation, beginning with an explanation of the data and the information it provides, then moving into a holistic framework for implementation. Case studies show how real-world companies are leveraging UDA in security and customer management, and provide clear examples of both traditional business applications and newer, more innovative practices. Roughly 80 percent of today's data is unstructured in the form of emails, chats, social media, audio, and video. These data assets contain a wealth of valuable information that can be used to great advantage, but accessing that data in a meaningful way remains a challenge for many companies. This book provides the baseline knowledge and the practical understanding companies need to put this data to work. Supported by research with several industry leaders and packed with frontline stories from leading organizations such as Google, Amazon, Spotify, LinkedIn, Pfizer Manulife, AXA, Monster Worldwide, Under Armour, the Houston Rockets, DELL, IBM, and SAS Institute, this book provide a framework for building and implementing a successful UDA center of excellence. You will learn: How to increase Customer Acquisition and Customer Retention with UDA The Power of UDA for Fraud Detection and Prevention The Power of UDA in Human Capital Management & Human Resource The Power of UDA in Health Care and Medical Research The Power of UDA in National Security The Power of UDA in Legal Services The Power of UDA for product development The Power of UDA in Sports The future of UDA From small businesses to large multinational organizations, unstructured data provides the opportunity to gain consumer information straight from the source. Data is only as valuable as it is useful, and a robust, effective UDA strategy is the first step toward gaining the full advantage. Unstructured Data Analytics lays this space open for examination, and provides a solid framework for beginning meaningful analysis. |
| forrester wave data management for analytics: Enterprise Big Data Engineering, Analytics, and Management Atzmueller, Martin, 2016-06-01 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. |
| forrester wave data management for analytics: Big Data Infrastructure Technologies for Data Analytics Yuri Demchenko, |
| forrester wave data management for analytics: Business Intelligence & Data Warehousing Simplified Arshad Khan, 2011-10-15 This book targets business and IT professionals who need an introduction to business intelligence and data warehousing through a simple question/answer format. Organized into 30 odd chapters, each on a different topic, the book contains approximately 500 questions with answers and tips. Topics include evolution and fundamentals, characteristics and process, architecture and objects, metadata, data conversion, ETL, data storage, infrastructure, data access, data marts, implementation approaches, planning, design, Inmon vs. Kimball, multi-dimensionality, OLAP, facts and dimensions, common mistakes and tips, etc. The book can also be used as a supplemental textbook, for various data warehousing/business intelligence courses. |
| forrester wave data management for analytics: Big Data Analytics for Sensor-Network Collected Intelligence Hui-Huang Hsu, Chuan-Yu Chang, Ching-Hsien Hsu, 2017-02-02 Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services. It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality. In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS - Contains contributions from noted scholars in computer science and electrical engineering from around the globe - Provides a broad overview of recent developments in sensor collected intelligence - Edited by a team comprised of leading thinkers in big data analytics |
| forrester wave data management for analytics: Application of Big Data for National Security Babak Akhgar, Gregory B. Saathoff, Hamid R Arabnia, Richard Hill, Andrew Staniforth, Petra Saskia Bayerl, 2015-02-14 Application of Big Data for National Security provides users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and crime, including a wide range of case studies and application scenarios. This book combines expertise from an international team of experts in law enforcement, national security, and law, as well as computer sciences, criminology, linguistics, and psychology, creating a unique cross-disciplinary collection of knowledge and insights into this increasingly global issue. The strategic frameworks and critical factors presented in Application of Big Data for National Security consider technical, legal, ethical, and societal impacts, but also practical considerations of Big Data system design and deployment, illustrating how data and security concerns intersect. In identifying current and future technical and operational challenges it supports law enforcement and government agencies in their operational, tactical and strategic decisions when employing Big Data for national security - Contextualizes the Big Data concept and how it relates to national security and crime detection and prevention - Presents strategic approaches for the design, adoption, and deployment of Big Data technologies in preventing terrorism and reducing crime - Includes a series of case studies and scenarios to demonstrate the application of Big Data in a national security context - Indicates future directions for Big Data as an enabler of advanced crime prevention and detection |
| forrester wave data management for analytics: Fundamentals of Service Systems Jorge Cardoso, Hansjörg Fromm, Stefan Nickel, Gerhard Satzger, Rudi Studer, Christof Weinhardt, 2015-12-12 This textbook addresses the conceptual and practical aspects of the various phases of the lifecycle of service systems, ranging from service ideation, design, implementation, analysis, improvement and trading associated with service systems engineering. Written by leading experts in the field, this indispensable textbook will enable a new wave of future professionals to think in a service-focused way with the right balance of competencies in computer science, engineering, and management. Fundamentals of Service Systems is a centerpiece for a course syllabus on service systems. Each chapter includes a summary, a list of learning objectives, an opening case, and a review section with questions, a project description, a list of key terms, and a list of further reading bibliography. All these elements enable students to learn at a faster and more comfortable peace. For researchers, teachers, and students who want to learn about this new emerging science, Fundamentals of Service Systems provides an overview of the core disciplines underlying the study of service systems. It is aimed at students of information systems, information technology, and business and economics. It also targets business and IT practitioners, especially those who are looking for better ways of innovating, designing, modeling, analyzing, and optimizing service systems. |
| forrester wave data management for analytics: Marketing and Sales Automation Uwe Hannig, Uwe Seebacher, 2023-05-02 This book clarifies based on latest findings and research what one needs to know about marketing and sales automation, how to manage projects to implement them, select and implement tools, and what results can be achieved. It also outlines what can be expected in the future such as the automation of corporate communication and Human Resources. The range of topics spans from the creation of a valid data base in the context of applied AI for realizing predictive intelligence and the effects of data regulations such as the European General Data Protection Regulation (GDPR) when addressing customers and prospects to recommendations for selecting and implementing the necessary IT systems. Experts also report on their experiences in regard to Conversion-rate-optimization (CRO) and provide tips and assistance on how to optimize and ensure the highest RoI for marketing and sales automation. A special focus will be placed on the dovetailing of marketing and sales and the management of the customer journey as well as the improvement of the customer experience. |
| forrester wave data management for analytics: 360 Derajat Manajemen Data Dr. Tjahjanto, S.Kom, MM & Mahasiswa Magister Ilmu Komputer UBL, 2021-08-05 Buku 360 Derajat Manajemen Data ini adalah karya Dosen dan Mahasiswa Magister Ilmu Komputer, yang memang berisikan multi dimensi dari Manajemen Data, yang bisa dilengkapi dari teori hingga contoh kasus terkini, atau tambahan link yang berupa QR Code untuk bisa link ke materi tambahan pendukung di internet (menuju materi kekinian). |
| forrester wave data management for analytics: Big Data: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2016-04-20 The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics. |
| forrester wave data management for analytics: Applied Data Science Martin Braschler, Thilo Stadelmann, Kurt Stockinger, 2019-06-13 This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors – some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science: first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors’ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry. |
| forrester wave data management for analytics: Disruptive Analytics Thomas W. Dinsmore, 2016-08-27 Learn all you need to know about seven key innovations disrupting business analytics today. These innovations—the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics—are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities. Enterprises who seize the opportunity will thrive and prosper, while others struggle and decline: disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization. Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today. What You'll Learn Discover how the open source business model works and how to make it work for you See how cloud computing completely changes the economics of analytics Harness the power of Hadoop and its ecosystem Find out why Apache Spark is everywhere Discover the potential of streaming and real-time analytics Learn what Deep Learning can do and why it matters See how self-service analytics can change the way organizations do business Who This Book Is For Corporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants. |
| forrester wave data management for analytics: Performance Evaluation and Benchmarking for the Analytics Era Raghunath Nambiar, Meikel Poess, 2018-01-02 This book constitutes the thoroughly refereed post-conference proceedings of the 8th TPC Technology Conference, on Performance Evaluation and Benchmarking, TPCTC 2017, held in conjunction with the43rd International Conference on Very Large Databases (VLDB 2017) in August/September 2017. The 12 papers presented were carefully reviewed and selected from numeroussubmissions. The TPC remains committed to developing new benchmark standards to keep pace with these rapid changes in technology. |
| forrester wave data management for analytics: Building the Data Lakehouse Bill Inmon, Ranjeet Srivastava, Mary Levins, 2021-10 The data lakehouse is the next generation of the data warehouse and data lake, designed to meet today's complex and ever-changing analytics, machine learning, and data science requirements. Learn about the features and architecture of the data lakehouse, along with its powerful analytical infrastructure. Appreciate how the universal common connector blends structured, textual, analog, and IoT data. Maintain the lakehouse for future generations through Data Lakehouse Housekeeping and Data Future-proofing. Know how to incorporate the lakehouse into an existing data governance strategy. Incorporate data catalogs, data lineage tools, and open source software into your architecture to ensure your data scientists, analysts, and end users live happily ever after. |
| forrester wave data management for analytics: Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis Osman, Ibrahim H., 2013-08-31 Organizations can use the valuable tool of data envelopment analysis (DEA) to make informed decisions on developing successful strategies, setting specific goals, and identifying underperforming activities to improve the output or outcome of performance measurement. The Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis highlights the advantages of using DEA as a tool to improve business performance and identify sources of inefficiency in public and private organizations. These recently developed theories and applications of DEA will be useful for policymakers, managers, and practitioners in the areas of sustainable development of our society including environment, agriculture, finance, and higher education sectors. |
| forrester wave data management for analytics: AI and the Future of Banking Tony Boobier, 2020-04-06 An industry-specific guide to the applications of Advanced Analytics and AI to the banking industry Artificial Intelligence (AI) technologies help organisations to get smarter and more effective over time – ultimately responding to, learning from and interacting with human voices. It is predicted that by 2025, half of all businesses will be using these intelligent, self-learning systems. Across its entire breadth and depth, the banking industry is at the forefront of investigating Advanced Analytics and AI technology for use in a broad range of applications, such as customer analytics and providing wealth advice for clients. AI and the Future of Banking provides new and established banking industry professionals with the essential information on the implications of data and analytics on their roles, responsibilities and personal career development. Unlike existing books on the subject which tend to be overly technical and complex, this accessible, reader-friendly guide is designed to be easily understood by any banking professional with limited or no IT background. Chapters focus on practical guidance on the use of analytics to improve operational effectiveness, customer retention and finance and risk management. Theory and published case studies are clearly explained, whilst considerations such as operating costs, regulation and market saturation are discussed in real-world context. Written by a recognised expert in AI and Advanced Analytics, this book: Explores the numerous applications for Advanced Analytics and AI in various areas of banking and finance Offers advice on the most effective ways to integrate AI into existing bank ecosystems Suggests alternative and complementary visions for the future of banking, addressing issues like branch transformation, new models of universal banking and ‘debranding’ Explains the concept of ‘Open Banking,’ which securely shares information without needing to reveal passwords Addresses the development of leadership relative to AI adoption in the banking industry AI and the Future of Banking is an informative and up-to-date resource for bank executives and managers, new entrants to the banking industry, financial technology and financial services practitioners and students in postgraduate finance and banking courses. |
| forrester wave data management for analytics: Rise of the Data Cloud Frank Slootman, Steve Hamm, 2020-12-18 The rise of the Data Cloud is ushering in a new era of computing. The world’s digital data is mass migrating to the cloud, where it can be more effectively integrated, managed, and mobilized. The data cloud eliminates data siloes and enables data sharing with business partners, capitalizing on data network effects. It democratizes data analytics, making the most sophisticated data science tools accessible to organizations of all sizes. Data exchanges enable businesses to discover, explore, and easily purchase or sell data—opening up new revenue streams. Business leaders have long dreamed of data driving their organizations. Now, thanks to the Data Cloud, nothing stands in their way. |
| forrester wave data management for analytics: Computer Science , |
| forrester wave data management for analytics: T-Bytes Hybrid Cloud Infrastructure IT-Shades, 2020-08-10 This document brings together a set of latest data points and publicly available information relevant for Hybrid Cloud Infrastructure Industry. We are very excited to share this content and believe that readers will benefit from this periodic publication immensely. |
| forrester wave data management for analytics: Practical Data Analytics for Innovation in Medicine Gary D. Miner, Linda A. Miner, Scott Burk, Mitchell Goldstein, Robert Nisbet, Nephi Walton, Thomas Hill, 2023-02-08 Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition discusses the needs of healthcare and medicine in the 21st century, explaining how data analytics play an important and revolutionary role. With healthcare effectiveness and economics facing growing challenges, there is a rapidly emerging movement to fortify medical treatment and administration by tapping the predictive power of big data, such as predictive analytics, which can bolster patient care, reduce costs, and deliver greater efficiencies across a wide range of operational functions. Sections bring a historical perspective, highlight the importance of using predictive analytics to help solve health crisis such as the COVID-19 pandemic, provide access to practical step-by-step tutorials and case studies online, and use exercises based on real-world examples of successful predictive and prescriptive tools and systems. The final part of the book focuses on specific technical operations related to quality, cost-effective medical and nursing care delivery and administration brought by practical predictive analytics. Brings a historical perspective in medical care to discuss both the current status of health care delivery worldwide and the importance of using modern predictive analytics to help solve the health care crisis Provides online tutorials on several predictive analytics systems to help readers apply their knowledge on today’s medical issues and basic research Teaches how to develop effective predictive analytic research and to create decisioning/prescriptive analytic systems to make medical decisions quicker and more accurate |
| forrester wave data management for analytics: It's All Analytics! Scott Burk, Gary D. Miner, 2020-05-25 It's All Analytics! The Foundations of AI, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government (978-0-367-35968-3, 325690) Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially in the last 25 years, there has been an explosion of terms and methods that automate and improve decision-making and operations. One term, analytics, is an overarching description of a compilation of methodologies. But AI (artificial intelligence), statistics, decision science, and optimization, which have been around for decades, have resurged. Also, things like business intelligence, online analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology and terminology? This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject. The authors include the basics such as algorithms, mental concepts, models, and paradigms in addition to the benefits of machine learning. The book also includes a chapter on data and the various forms of data. The authors wrap up this book with a look at the next frontiers such as applications and designing your environment for success, which segue into the topics of the next two books in the series. |
| forrester wave data management for analytics: Proceedings of the 10th International Conference on Intellectual Capital, knowledge Management and Organisational Learning Dr Annie Green, 2013-01-09 |
| forrester wave data management for analytics: Social Knowledge Management in Action Remko Helms, Jocelyn Cranefield, Jurriaan van Reijsen, 2017-02-23 Knowledge management (KM) is about managing the lifecycle of knowledge consisting of creating, storing, sharing and applying knowledge. Two main approaches towards KM are codification and personalization. The first focuses on capturing knowledge using technology and the latter on the process of socializing for sharing and creating knowledge. Social media are becoming very popular as individuals and also organizations learn how to use it. The primary applications of social media in a business context are marketing and recruitment. But there is also a huge potential for knowledge management in these organizations. For example, wikis can be used to collect organizational knowledge and social networking tools, which leads to exchanging new ideas and innovation. The interesting part of social media is that, by using them, one immediately starts to generate content that can be useful for the organization. Hence, they naturally combine the codification and personalisation approaches to KM. This book aims to provide an overview of new and innovative applications of social media and to report challenges that need to be solved. One example is the watering down of knowledge as a result of the use of organizational social media (Von Krogh, 2012). |
| forrester wave data management for analytics: SAP HANA 2.0 Denys Van Kempen, 2019 Enter the fast-paced world of SAP HANA 2.0 with this introductory guide. Begin with an exploration of the technological backbone of SAP HANA as a database and platform. Then, step into key SAP HANA user roles and discover core capabilities for administration, application development, advanced analytics, security, data integration, and more. No matter how SAP HANA 2.0 fits into your business, this book is your starting point. In this book, you'll learn about: a. Technology Discover what makes an in-memory database platform. Learn about SAP HANA's journey from version 1.0 to 2.0, take a tour of your technology options, and walk through deployment scenarios and implementation requirements. b. Tools Unpack your SAP HANA toolkit. See essential tools in action, from SAP HANA cockpit and SAP HANA studio, to the SAP HANA Predictive Analytics Library and SAP HANA smart data integration. c. Key Roles Understand how to use SAP HANA as a developer, administrator, data scientist, data center architect, and more. Explore key tasks like backend programming with SQLScript, security setup with roles and authorizations, data integration with the SAP HANA Data Management Suite, and more. Highlights include: 1) Architecture 2) Administration 3) Application development 4) Analytics 5) Security 6) Data integration 7) Data architecture 8) Data center |
| forrester wave data management for analytics: AI, Blockchain and Self-Sovereign Identity in Higher Education Hamid Jahankhani, Arshad Jamal, Guy Brown, Eustathios Sainidis, Rose Fong, Usman J. Butt, 2023-06-22 This book aims to explore the next generation of online learning challenges including the security and privacy issues of digital transformation strategies that is required in teaching and learning. Also, what efforts does the industry need to invest in changing mind-sets and behaviours of both students and faculty members in adoption of virtual and blended learning? The book provides a comprehensive coverage of not only the technical and ethical issues presented by the use of AI, blockchain and self-sovereign identity, but also the adversarial application of AI and its associated implications. The authors recommend a number of novel approaches to assist in better detecting, thwarting and addressing AI challenges in higher education. The book provides a valuable reference for cyber security experts and practitioners, network security professionals and higher education strategist and decision-makers. It is also aimed at researchers seeking to obtain a more profound knowledge of machine learning and deep learning in the context of cyber security and AI in higher education. Each chapter is written by an internationally renowned expert who has extensive experience in industry or academia. Furthermore, this book blends advanced research findings with practice-based methods to provide the reader with advanced understanding and relevant skills. |
| forrester wave data management for analytics: Machine Learning Techniques and Analytics for Cloud Security Rajdeep Chakraborty, Anupam Ghosh, Jyotsna Kumar Mandal, 2021-12-21 MACHINE LEARNING TECHNIQUES AND ANALYTICS FOR CLOUD SECURITY This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions The aim of Machine Learning Techniques and Analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical handling. The conventional cryptography approach is less applied in resource-constrained devices. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment. Machine learning algorithms can also be used to meet various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, measures for passive attacks, protocols design, privacy system designs, applications, and many more. The book also contains case studies/projects outlining how to implement various security features using machine learning algorithms and analytics on existing cloud-based products in public, private and hybrid cloud respectively. Audience Research scholars and industry engineers in computer sciences, electrical and electronics engineering, machine learning, computer security, information technology, and cryptography. |
| forrester wave data management for analytics: Big Data, Data Mining, and Machine Learning Jared Dean, 2014-05-07 With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole. |
| forrester wave data management for analytics: Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making Cengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari, 2019-07-05 This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic. |
| forrester wave data management for analytics: Enterprise Cloud Strategy Barry Briggs, Eduardo Kassner, 2016-01-07 How do you start? How should you build a plan for cloud migration for your entire portfolio? How will your organization be affected by these changes? This book, based on real-world cloud experiences by enterprise IT teams, seeks to provide the answers to these questions. Here, you’ll see what makes the cloud so compelling to enterprises; with which applications you should start your cloud journey; how your organization will change, and how skill sets will evolve; how to measure progress; how to think about security, compliance, and business buy-in; and how to exploit the ever-growing feature set that the cloud offers to gain strategic and competitive advantage. |
| forrester wave data management for analytics: The Art and Science of Social Media Mastery: Profitable Key Roles for a Social Media Manager Abbas Alateya, The Global Institute chairman of Social Media Managers (GISMMs) has presented the first-ever integration of Essential and Strategic Roles for a social media manager. This book offers a comprehensive compilation of academic research and expert insights. Delve into the essential roles and tasks integral to effective social media management in this dynamic field. This book is a comprehensive guide for both seasoned and aspiring social media managers in public or private sectors, including corporations of varying sizes and non-profit organizations. It offers a compilation of academic research and expert insights on Essential and Strategic Roles required for effective social media management. |
| forrester wave data management for analytics: Human Resource Intelligence und Analytics Stefan Strohmeier, Franca Piazza, 2015-01-13 Das Buch bietet einen umfassenden Überblick über die Anwendung und Implementierung von Business-Intelligence-Lösungen im Personalmanagement. Business-Intelligence-Systeme finden als Analyse- und Planungssysteme verbreitete Anwendung in vielfältigen Unternehmensbereichen wie Vertrieb/Customer Relationship Management, Logistik/Supply Chain Management sowie Personalmanagement. Daher beschäftigt sich Autoren und Herausgeber intensiv mit der Anwendung von Business-Intelligence-Systemen im Personalmanagement und geben einen ausführlichen systematischen Einblick in entsprechende grundlegende technologische Konzepte und personalwirtschaftliche Anforderungen. Ziel des Buches ist daher eine spezifisch auf die Anwendungsdomäne Personalmanagement ausgerichtete Ausarbeitung der Business-Intelligence-Konzeption in technischer und fachlicher Hinsicht. |
| forrester wave data management for analytics: Customer analytics Núria Braulio Gil, Josep Curto Díaz, 2015-01-01 Las organizaciones han usado estrategias, como la inteligencia de negocio, para tomar mejores decisiones a partir de los datos. Actualmente, en la era de los datos, nuestros clientes son más inteligentes, están más informados y ya no son tan leales con nuestra marca. Esperan experiencias inolvidables y profundamente personalizadas en cada una de las interacciones con nuestra organización. Como resultado, las organizaciones están obligadas a transformar sus estrategias para conocer mejor las necesidades y preferencias de sus clientes, basándose en una enorme cantidad de datos. |
| forrester wave data management for analytics: Digital Marketing Technologies Hashem Aghazadeh, |
| forrester wave data management for analytics: Radical Business Model Transformation Carsten Linz, Günter Müller-Stewens, Alexander Zimmermann, 2017-01-03 Many companies are relying on a business model that is fundamentally suited to a different era. Now, organizations are under pressure from new trends such as digitization and servitization. Trying to adapt to a new environment, they risk relying on improvements that only scratch the surface of developing a radically different value proposition. Based on rigorous research into companies that have successfully and radically redesigned their business models, Radical Business Model Transformation shows why they made the leap, what they had to do to achieve it and how it has transformed the potential for their organizations. This book is a step-by-step guide for leaders who want to seize the opportunity of new business models and gain a competitive advantage. It explains how to assess the status quo, identify the value of future business models and develop a transformation path. It also provides advice on how to involve both the leadership team and all other employees in order to implement successful business model transformation. Illustrative case studies of organizations that have crossed the line to a more transformative business range from exponential-growth companies like Netflix and global players like Xerox, SAP and Daimler to mid-sized hidden champions like Knorr-Bremse and LEGIC. Radical Business Model Transformation is essential reading for business leaders, transformation experts and MBA students interested in ensuring that their business model is future-proof and can withstand the new proliferation of innovations that are set to transform the business landscape. Online supporting resources include a business model transformation calculator to help design your transformation path. |
| forrester wave data management for analytics: Applied Business Analytics Nathaniel Lin, 2015 Now that you've collected the data and crunched the numbers, what do you do with all this information? How do you take the fruit of your analytics labor and apply it to business decision making? How do you actually apply the information gleaned from quants and tech teams? Applied Business Analytics will help you find optimal answers to these questions, and bridge the gap between analytics and execution in your organization. Nathaniel Lin explains why analytics value chains often break due to organizational and cultural issues, and offers in the trenches guidance for overcoming these obstacles. You'll learn why a special breed of analytics deciders is indispensable for any organization that seeks to compete on analytics; how to become one of those deciders; and how to identify, foster, support, empower, and reward others who join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at every level: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ -- and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer |
| forrester wave data management for analytics: Evidence-Based Cybersecurity Pierre-Luc Pomerleau, David Maimon, 2022-06-23 The prevalence of cyber-dependent crimes and illegal activities that can only be performed using a computer, computer networks, or other forms of information communication technology has significantly increased during the last two decades in the USA and worldwide. As a result, cybersecurity scholars and practitioners have developed various tools and policies to reduce individuals' and organizations' risk of experiencing cyber-dependent crimes. However, although cybersecurity research and tools production efforts have increased substantially, very little attention has been devoted to identifying potential comprehensive interventions that consider both human and technical aspects of the local ecology within which these crimes emerge and persist. Moreover, it appears that rigorous scientific assessments of these technologies and policies in the wild have been dismissed in the process of encouraging innovation and marketing. Consequently, governmental organizations, public, and private companies allocate a considerable portion of their operations budgets to protecting their computer and internet infrastructures without understanding the effectiveness of various tools and policies in reducing the myriad of risks they face. Unfortunately, this practice may complicate organizational workflows and increase costs for government entities, businesses, and consumers. The success of the evidence-based approach in improving performance in a wide range of professions (for example, medicine, policing, and education) leads us to believe that an evidence-based cybersecurity approach is critical for improving cybersecurity efforts. This book seeks to explain the foundation of the evidence-based cybersecurity approach, review its relevance in the context of existing security tools and policies, and provide concrete examples of how adopting this approach could improve cybersecurity operations and guide policymakers' decision-making process. The evidence-based cybersecurity approach explained aims to support security professionals', policymakers', and individual computer users' decision-making regarding the deployment of security policies and tools by calling for rigorous scientific investigations of the effectiveness of these policies and mechanisms in achieving their goals to protect critical assets. This book illustrates how this approach provides an ideal framework for conceptualizing an interdisciplinary problem like cybersecurity because it stresses moving beyond decision-makers' political, financial, social, and personal experience backgrounds when adopting cybersecurity tools and policies. This approach is also a model in which policy decisions are made based on scientific research findings. |
Forrester 公司简介
作为全球最具影响力的独立研究咨询公司之一，Forrester 协助商业和技术领袖，推动以客户为中心的愿景、战略及执行力，由此驱动商业增长。Forrester 每年面向世界超过690,000名消费者和 …
Forrester
Discover the top 10 emerging technologies shaping 2025, based on Forrester’s exhaustive research. Explore the impact, use cases, and benefit horizons of technologies like agentic AI, …
Forrester 中国: 畅想变革
Forrester 作为全球最具影响力的独立研究咨询公司之一，提供与中国市场相关的研究洞察、市场趋势和最佳实践，例如：中国客户体验趋势、科技厂商在中国的本土化策略、中国科技市场展望 …
Analyst Briefings - Forrester
Forrester analysts use briefings to learn about changes in markets, providers, and services. To increase their understanding of your business, the analyst will ask you clarifying questions.
2021-年亚太区市场趋势预测 - Forrester
Forrester预测2021年，亚太地区将在欧美之前率先走出疫情，企业将在技术驱动的体验、运营、产品和生态系统方向加倍投入实践。 立即下载指南，了解未来一年值得亚太商业和技术领导者 …
Use Journey Maps To Kick-Start A CX Transformation | Forrester
Guide to learn how to leverage new or existing journey maps to spur investment and interest in CX, as well as boost performance.
Momentum Is Building For CX, But Will It Continue? - Forrester
Forrester’s CX Index™ 2019 results reveal that more brands are inching forward along their CX transformation journey. But these are early days yet, and most firms are stagnant. …
Asia Pacific - Forrester
Apr 3, 2025 · Read Forrester's insights on financial services, marketing, technology, and more in the Asia Pacific (APAC) region.
Align Your Revenue Generating Ecosystem - Forrester
Forrester’s SiriusDecisions Research delivers operational intelligence and fact-based insights to functional leaders of B2B organizations and their teams so they can align across the revenue …
Forrester Europe Predictions 2021: All Complimentary Resources
Discover the insights necessary to prepare your organisation for 2021 using Forrester's European Predictions Resources Finder.
Forrester 公司简介
作为全球最具影响力的独立研究咨询公司之一，Forrester 协助商业和技术领袖，推动以客户为中心的愿景、战略及执行力，由此驱动商业增长。Forrester 每年面向世界超过690,000名消费者和 …
Forrester
Discover the top 10 emerging technologies shaping 2025, based on Forrester’s exhaustive research. Explore the impact, use cases, and benefit horizons of technologies like agentic AI, …
Forrester 中国: 畅想变革
Forrester 作为全球最具影响力的独立研究咨询公司之一，提供与中国市场相关的研究洞察、市场趋势和最佳实践，例如：中国客户体验趋势、科技厂商在中国的本土化策略、中国科技市场展望 …
Analyst Briefings - Forrester
Forrester analysts use briefings to learn about changes in markets, providers, and services. To increase their understanding of your business, the analyst will ask you clarifying questions.
2021-年亚太区市场趋势预测 - Forrester
Forrester预测2021年，亚太地区将在欧美之前率先走出疫情，企业将在技术驱动的体验、运营、产品和生态系统方向加倍投入实践。 立即下载指南，了解未来一年值得亚太商业和技术领导者关 …
Use Journey Maps To Kick-Start A CX Transformation | Forrester
Guide to learn how to leverage new or existing journey maps to spur investment and interest in CX, as well as boost performance.
Momentum Is Building For CX, But Will It Continue? - Forrester
Forrester’s CX Index™ 2019 results reveal that more brands are inching forward along their CX transformation journey. But these are early days yet, and most firms are stagnant. …
Asia Pacific - Forrester
Apr 3, 2025 · Read Forrester's insights on financial services, marketing, technology, and more in the Asia Pacific (APAC) region.
Align Your Revenue Generating Ecosystem - Forrester
Forrester’s SiriusDecisions Research delivers operational intelligence and fact-based insights to functional leaders of B2B organizations and their teams so they can align across the revenue …
Forrester Europe Predictions 2021: All Complimentary Resources
Discover the insights necessary to prepare your organisation for 2021 using Forrester's European Predictions Resources Finder.
