Search results for: guide-to-industrial-analytics

Guide to Industrial Analytics

Author : Richard Hill
File Size : 85.47 MB
Format : PDF, ePub, Mobi
Download : 583
Read : 1052
Download »
This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital of Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.

End to end Data Analytics for Product Development

Author : Rosa Arboretti Giancristofaro
File Size : 67.65 MB
Format : PDF, ePub
Download : 543
Read : 1213
Download »
An interactive guide to the statistical tools used to solve problems during product and process innovation End to End Data Analytics for Product Development is an accessible guide designed for practitioners in the industrial field. It offers an introduction to data analytics and the design of experiments (DoE) whilst covering the basic statistical concepts useful to an understanding of DoE. The text supports product innovation and development across a range of consumer goods and pharmaceutical organizations in order to improve the quality and speed of implementation through data analytics, statistical design and data prediction. The book reviews information on feasibility screening, formulation and packaging development, sensory tests, and more. The authors – noted experts in the field – explore relevant techniques for data analytics and present the guidelines for data interpretation. In addition, the book contains information on process development and product validation that can be optimized through data understanding, analysis and validation. The authors present an accessible, hands-on approach that uses MINITAB and JMP software. The book: • Presents a guide to innovation feasibility and formulation and process development • Contains the statistical tools used to solve challenges faced during product innovation and feasibility • Offers information on stability studies which are common especially in chemical or pharmaceutical fields • Includes a companion website which contains videos summarizing main concepts Written for undergraduate students and practitioners in industry, End to End Data Analytics for Product Development offers resources for the planning, conducting, analyzing and interpreting of controlled tests in order to develop effective products and processes.

A User s Guide to Business Analytics

Author : Ayanendranath Basu
File Size : 50.2 MB
Format : PDF, Kindle
Download : 248
Read : 1120
Download »
A User's Guide to Business Analytics provides a comprehensive discussion of statistical methods useful to the business analyst. Methods are developed from a fairly basic level to accommodate readers who have limited training in the theory of statistics. A substantial number of case studies and numerical illustrations using the R-software package are provided for the benefit of motivated beginners who want to get a head start in analytics as well as for experts on the job who will benefit by using this text as a reference book. The book is comprised of 12 chapters. The first chapter focuses on business analytics, along with its emergence and application, and sets up a context for the whole book. The next three chapters introduce R and provide a comprehensive discussion on descriptive analytics, including numerical data summarization and visual analytics. Chapters five through seven discuss set theory, definitions and counting rules, probability, random variables, and probability distributions, with a number of business scenario examples. These chapters lay down the foundation for predictive analytics and model building. Chapter eight deals with statistical inference and discusses the most common testing procedures. Chapters nine through twelve deal entirely with predictive analytics. The chapter on regression is quite extensive, dealing with model development and model complexity from a user’s perspective. A short chapter on tree-based methods puts forth the main application areas succinctly. The chapter on data mining is a good introduction to the most common machine learning algorithms. The last chapter highlights the role of different time series models in analytics. In all the chapters, the authors showcase a number of examples and case studies and provide guidelines to users in the analytics field.

The Complete Guide to Business Analytics Collection

Author : Thomas H. Davenport
File Size : 20.89 MB
Format : PDF
Download : 642
Read : 1113
Download »
A brand new collection of business analytics insights and actionable techniques… 3 authoritative books, now in a convenient e-format, at a great price! 3 authoritative eBooks deliver comprehensive analytics knowledge and tools for optimizing every critical business decision! Use business analytics to drive maximum value from all your business data! This unique 3 eBook package will help you harness your information, discover hidden patterns, and successfully act on what you learn. In Enterprise Analytics, analytics pioneer Tom Davenport and the world-renowned experts at the International Institute for Analytics (IIA) bring together the latest techniques, best practices, and research on large-scale analytics strategy, technology, implementation, and management. Using real-world examples, they cover everything from building better analytics organizations to gathering data; implementing predictive analytics to linking analysis with organizational performance. You'll find specific insights for optimizing supply chains, online services, marketing, fraud detection, and many other business functions; plus chapter-length case studies from healthcare, retail, and financial services. Next, in the up-to-the-minute Analysis Without Paralysis, Second Edition, Babette E. Bensoussan and Craig S. Fleisher help you succeed with analysis without getting mired in advanced math or arcane theory. They walk you through the entire business analysis process, and guide you through using 12 core tools for making better decisions about strategy and operations -- including three powerful tools covered for the first time in this new Second Edition. Then, in Business and Competitive Analysis, Fleisher and Bensoussan help you apply 24 leading business analysis models to gain deep clarity about your business environment, answer tough questions, and make tough choices. They first walk you through defining problems, avoiding pitfalls, choosing tools, and communicating results. Next, they systematically address both “classic” techniques and the most promising new approaches from economics, finance, sociology, anthropology, and the intelligence and futurist communities. For the first time, one book covers Nine Forces, Competitive Positioning, Business Model, Supply Chain Analyses, Benchmarking, McKinsey 7S, Shadowing, Product Line, Win/Loss, Strategic Relationships, Corporate Reputation, Critical Success Factors, Driving Forces, Country Risk, Technology Forecasting, War Gaming, Event/Timeline, Indications, Warning Analyses, Competitor Cash Flow, ACH, Linchpin Analyses, and more. Whether you're an executive, strategist, analyst, marketer, or operations professional, this eBook collection will help you make more effective, data-driven, profitable decisions! From world-renowned analytics and competitive/business intelligence experts Thomas H. Davenport, Babette E. Bensoussan, and Craig S. Fleisher

Introduction to Industrial Internet of Things and Industry 4 0

Author : Sudip Misra
File Size : 52.63 MB
Format : PDF, Kindle
Download : 431
Read : 426
Download »
Industrial IoT (IIoT) and Industry 4.0 are newly developing and fast emerging domains of interest among students, researchers, and professionals in academia and industry. Due to the popular demand of this topic, Introduction to Industrial Internet of Things and Industry 4.0 is written to serve a diverse readership from the domains of computer science and engineering, mechanical engineering, information technology, industrial engineering, electronics engineering, and other related branches of engineering. Based on the lead author’s massive open online courses (MOOCs), this book can be used as a textbook on the emerging paradigm of Industry 4.0 and IIoT, as well as a reference for professionals working in sectors of IIoT. The book covers the significant aspects of IIoT in detail, including sensors, actuators, data transmission, and data acquisition, which form the core of IIoT. Topics and concepts are presented in a comprehensive manner, so that readers can develop expertise and knowledge. The book helps beginners to gain a basic idea of Industry 4.0 and IIoT as the first section is an overview of IoT applications, infrastructure-based protocols, cloud computing, and fog computing. The second section is designed to impart a basic knowledge of Industry 4.0 and IIoT as well as of the different phases of development in industry. Delving into more advanced areas, other sections in the book cover: The business models and reference architecture of IIoT The technological aspects of Industry 4.0 and IIoT Predictive and prescriptive analytics applied in IIoT-based implementations Applications and case studies of IIoT Key enabling technologies of IIoT To aid students and professional master IIoT and Industry 4.0, the book includes conceptual questions, exercises, and learning objectives.

Polymer Additive Analytics

Author : Jan C. J. Bart
File Size : 64.33 MB
Format : PDF, Docs
Download : 199
Read : 492
Download »

A Simple Guide to Technology and Analytics

Author : Brian J. Evans
File Size : 83.60 MB
Format : PDF, ePub
Download : 682
Read : 292
Download »
Everyday technology is constantly changing, and it’s hard to keep up with it at times. What is all this talk about automation, STEM, analytics and super-computers, and how will it really affect my daily life at work and in the home? This book is a simple guide to everyday technology and analytics written in plain language. It starts with explaining how computer networks are increasing in speed so fast that we can do more in less time than ever before. It explains the analytical jargon in plain English and why robotics in the home will be aided by the new technology of the quantum computer. Richly furnished with over 200 illustrations, photos and with minimal equations, A Simple Guide to Technology and Analytics is a ready reference book for those times when you don’t really understand the technology and analytics being talked about. It explains complicated topics such as automated character recognition in a very simple way, and has simple exercises for the reader to fully understand the technology (with answers at the back). It even has explanations on how home appliances work, which are very useful the next time you go shopping for a microwave or TV. Even the Glossary at the back can be used as a quick look-up explanation for those on the go.

The Practitioner s Guide to Cellular IoT

Author : Cameron Coursey
File Size : 84.22 MB
Format : PDF, ePub, Docs
Download : 180
Read : 974
Download »
The Internet of Things (IoT) has grown from a niche market for machine-to-machine communication into a global phenomenon that is touching our lives daily. The key aspects of IoT are covered in this book, including the anatomy of an IoT device and how it is connected to a backend system, the nuances of data extraction and keeping the data safe and secure, the role of the SIM card in cellular connected IoT devices, and how IoT devices are controlled. Low-power wide-area devices that will allow almost anything to be connected, how IoT devices are being connected around the world, and how 5G and edge computing will continue to drive new use cases are explained. Overcoming the challenges of creating IoT applications and hardware is covered. Detailed examples of how IoT is being used in the spaces of industrial, consumer, transportation, robotics, and wearables are provided. The IoT industry is explained. Finally, the future of IoT is covered in light of technical, social, and economic advances.

Data Analytics in the Era of the Industrial Internet of Things

Author : Aldo Dagnino
File Size : 72.86 MB
Format : PDF, ePub
Download : 163
Read : 675
Download »
This book presents the characteristics and benefits industrial organizations can reap from the Industrial Internet of Things (IIoT). These characteristics and benefits include enhanced competitiveness, increased proactive decision-making, improved creativity and innovation, augmented job creation, heightened agility to respond to continuously changing challenges, and intensified data-driven decision making. In a straightforward fashion, the book also helps readers understand complex concepts that are core to IIoT enterprises, such as Big Data, analytic architecture platforms, machine learning (ML) and data science algorithms, and the power of visualization to enrich the domains experts’ decision making. The book also guides the reader on how to think about ways to define new business paradigms that the IIoT facilitates, as well how to increase the probability of success in managing analytic projects that are the core engine of decision-making in the IIoT enterprise. The book starts by defining an IIoT enterprise and the framework used to efficiently operate. A description of the concepts of industrial analytics, which is a major engine for decision making in the IIoT enterprise, is provided. It then discusses how data and machine learning (ML) play an important role in increasing the competitiveness of industrial enterprises that operate using the IIoT technology and business concepts. Real world examples of data driven IIoT enterprises and various business models are presented and a discussion on how the use of ML and data science help address complex decision-making problems and generate new job opportunities. The book presents in an easy-to-understand manner how ML algorithms work and operate on data generated in the IIoT enterprise. Useful for any industry professional interested in advanced industrial software applications, including business managers and professionals interested in how data analytics can help industries and to develop innovative business solutions, as well as data and computer scientists who wish to bridge the analytics and computer science fields with the industrial world, and project managers interested in managing advanced analytic projects.

Guide to Ambient Intelligence in the IoT Environment

Author : Zaigham Mahmood
File Size : 56.76 MB
Format : PDF, ePub, Mobi
Download : 848
Read : 1226
Download »
Ambient intelligence (AmI) is an element of pervasive computing that brings smartness to living and business environments to make them more sensitive, adaptive, autonomous and personalized to human needs. It refers to intelligent interfaces that recognise human presence and preferences, and adjust smart environments to suit their immediate needs and requirements. The key factor is the presence of intelligence and decision-making capabilities in IoT environments. The underlying technologies include pervasive computing, ubiquitous communication, seamless connectivity of smart devices, sensor networks, artificial intelligence (AI), machine learning (ML) and context-aware human-computer interaction (HCI). AmI applications and scenarios include smart homes, autonomous self-driving vehicles, healthcare systems, smart roads, the industry sector, smart facilities management, the education sector, emergency services, and many more. The advantages of AmI in the IoT environment are extensive. However, as for any new technological paradigm, there are also many open issues and limitations. This book discusses the AmI element of the IoT and the relevant principles, frameworks, and technologies in particular, as well as the benefits and inherent limitations. It reviews the state of the art of current developments relating to smart spaces and AmI-based IoT environments. Written by leading international researchers and practitioners, the majority of the contributions focus on device connectivity, pervasive computing and context modelling (including communication, security, interoperability, scalability, and adaptability). The book presents cutting-edge research, current trends, and case studies, as well as suggestions to further our understanding and the development and enhancement of the AmI-IoT vision.

Deep Learning for Internet of Things Infrastructure

Author : Uttam Ghosh
File Size : 72.53 MB
Format : PDF, Mobi
Download : 166
Read : 656
Download »
This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT systems and services across various application domains. The book investigates the challenges posed by the implementation of deep learning on IoT networking models and services. It provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. The book also explores new functions and technologies to provide adaptive services and intelligent applications for different end users. FEATURES Promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of DL-based data analytics of IoT infrastructures Addresses emerging trends and issues on IoT systems and services across various application domains Investigates the challenges posed by the implementation of deep learning on IoT networking models and services Provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT Explores new functions and technologies to provide adaptive services and intelligent applications for different end users Uttam Ghosh is an Assistant Professor in the Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA. Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia. Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom. Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh.

Guide for the selection of chemical agent and toxic industrial material detection equipment for emergency first responders 2000

Author :
File Size : 43.91 MB
Format : PDF, Kindle
Download : 601
Read : 1223
Download »

AWS Certified Data Analytics Study Guide with Online Labs

Author : Asif Abbasi
File Size : 81.69 MB
Format : PDF, ePub, Mobi
Download : 704
Read : 1008
Download »
Virtual, hands-on learning labs allow you to apply your technical skills in realistic environments. So Sybex has bundled AWS labs from XtremeLabs with our popular AWS Certified Data Analytics Study Guide to give you the same experience working in these labs as you prepare for the Certified Data Analytics Exam that you would face in a real-life application. These labs in addition to the book are a proven way to prepare for the certification and for work as an AWS Data Analyst. AWS Certified Data Analytics Study Guide: Specialty (DAS-C01) Exam is intended for individuals who perform in a data analytics-focused role. This UPDATED exam validates an examinee's comprehensive understanding of using AWS services to design, build, secure, and maintain analytics solutions that provide insight from data. It assesses an examinee's ability to define AWS data analytics services and understand how they integrate with each other; and explain how AWS data analytics services fit in the data lifecycle of collection, storage, processing, and visualization. The book focuses on the following domains: • Collection • Storage and Data Management • Processing • Analysis and Visualization • Data Security This is your opportunity to take the next step in your career by expanding and validating your skills on the AWS cloud. AWS is the frontrunner in cloud computing products and services, and the AWS Certified Data Analytics Study Guide: Specialty exam will get you fully prepared through expert content, and real-world knowledge, key exam essentials, chapter review questions, and much more. Written by an AWS subject-matter expert, this study guide covers exam concepts, and provides key review on exam topics. Readers will also have access to Sybex's superior online interactive learning environment and test bank, including chapter tests, practice exams, a glossary of key terms, and electronic flashcards. And included with this version of the book, XtremeLabs virtual labs that run from your browser. The registration code is included with the book and gives you 6 months of unlimited access to XtremeLabs AWS Certified Data Analytics Labs with 3 unique lab modules based on the book.

HBR Guide to Data Analytics Basics for Managers HBR Guide Series

Author : Harvard Business Review
File Size : 27.28 MB
Format : PDF, ePub
Download : 849
Read : 315
Download »
Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes

Guide to Security in SDN and NFV

Author : Shao Ying Zhu
File Size : 41.9 MB
Format : PDF, Mobi
Download : 214
Read : 828
Download »
This book highlights the importance of security in the design, development and deployment of systems based on Software-Defined Networking (SDN) and Network Functions Virtualization (NFV), together referred to as SDNFV. Presenting a comprehensive guide to the application of security mechanisms in the context of SDNFV, the content spans fundamental theory, practical solutions, and potential applications in future networks. Topics and features: introduces the key security challenges of SDN, NFV and Cloud Computing, providing a detailed tutorial on NFV security; discusses the issue of trust in SDN/NFV environments, covering roots of trust services, and proposing a technique to evaluate trust by exploiting remote attestation; reviews a range of specific SDNFV security solutions, including a DDoS detection and remediation framework, and a security policy transition framework for SDN; describes the implementation of a virtual home gateway, and a project that combines dynamic security monitoring with big-data analytics to detect network-wide threats; examines the security implications of SDNFV in evolving and future networks, from network-based threats to Industry 4.0 machines, to the security requirements for 5G; investigates security in the Observe, Orient, Decide and Act (OODA) paradigm, and proposes a monitoring solution for a Named Data Networking (NDN) architecture; includes review questions in each chapter, to test the reader’s understanding of each of the key concepts described. This informative and practical volume is an essential resource for researchers interested in the potential of SDNFV systems to address a broad range of network security challenges. The work will also be of great benefit to practitioners wishing to design secure next-generation communication networks, or to develop new security-related mechanisms for SDNFV systems.

A Practical Guide to Artificial Intelligence and Data Analytics

Author : Rayan Wali
File Size : 58.9 MB
Format : PDF, Docs
Download : 866
Read : 1228
Download »
Due to a limited number of practice facilities in the field of Data Science and Artificial Intelligence, I have written this book to deliver concepts in a simple and clear manner with practical applications from case studies and real-world scenario-based exercises to facilitate the learning process. I also believe that one effectively learns material when after learning the material, they are given an assessment to measure their aptitude. As a result, I have included a full-length assessment, titled Data Science and Analytics Skills Assessment (DSSA), to create a checkpoint that allows one to maximize their study-skills. From this assessment, they can learn from their mistakes, and address holes in their understanding. And, the Data Science and Analytics Skills Assessment is specifically designed to pinpoint these holes, giving a score that accurately reflects their level of understanding.

The Definitive Guide to Marketing Analytics and Metrics Collection

Author : Cesar Brea
File Size : 87.59 MB
Format : PDF, ePub
Download : 681
Read : 915
Download »
A brand new collection introducing today's most powerful strategies and techniques for measuring and optimizing marketing… 3 authoritative books, now in a convenient e-format, at a great price! 3 authoritative Books help you measure, analyze, and optimize every marketing investment you'll ever make Measuring and optimize your marketing investments is more crucial than ever. But, with an explosion in channels and complexity, it's also more challenging than ever. Fortunately, marketing metrics and analytics have taken giant leaps forward in recent years: techniques now exist for accurately quantifying performance and applying what you learn to improve it. In this unique 3 Book package, world-class experts present these new approaches, and show how to profit from them. In Marketing and Sales Analytics, leading consultant Cesar A. Breaexamines the experiences of 15 leaders who've built high-value analytics capabilities in multiple industries. Then, building on what they've learned, he presents a complete blueprint for succeeding with marketing analytics. You'll learn how to evaluate "ecosystemic" conditions for success, frame the right questions, and organize your people, data, and operating infrastructure to answer them. Brea helps you overcome key challenges ranging from governance to overcoming hidden biases. Along the way, he also offers specific guidance on crucial decisions such as "buy vs. build?", "centralize or decentralize?", and "hire generalists or specialists?" Next, in Cutting Edge Marketing Analytics, three pioneering experts introduce today's most valuable marketing analytics methods and tools, and offer a best-practice methodology for successful implementation. They augment this knowledge with hands on case studies, guiding you through solving key problems in resource allocation, segmentation, pricing, campaign management, firm valuation, and digital marketing strategy. All case studies are accompanied by real data used by the protagonists to make decisions. As you practice, you'll gain a deeper understanding of the value of marketing analytics, learn to integrate quantitative analysis with managerial sensibilities, master core statistical tools, and discover how to avoid crucial pitfalls. Finally, in the award-winning Marketing Metrics, Second Edition, Paul W. Farris and his colleagues show how to choose the right metrics for every marketing challenge. You'll learn how to use dashboards to view market dynamics from multiple perspectives, maximize accuracy, and "triangulate" to optimal solutions. You'll discover high-value metrics for promotional strategy, advertising, distribution, customer perceptions, market share, competitors' power, margins, pricing, products and portfolios, customer profitability, sales forces, channels, and more. This extensively updated edition introduces innovative metrics ranging from Net Promoter to social media and brand equity measurement, and shows how to build comprehensive models to optimize every marketing decision you make. If you need to measure and improve marketing performance, this 3-book package will be your most valuable resource. From world-renowned business sustainability experts Cesar A. Brea, Rajkumar Venkatesan, Paul W. Farris, Ronald T. Wilcox, Neil T. Bendle, Phillip E. Pfeifer, and David J. Reibstein

Industrial Data Analytics for Diagnosis and Prognosis

Author : Shiyu Zhou
File Size : 23.18 MB
Format : PDF, Mobi
Download : 682
Read : 1333
Download »
Discover data analytics methodologies for the diagnosis and prognosis of industrial systems under a unified random effects model In Industrial Data Analytics for Diagnosis and Prognosis - A Random Effects Modelling Approach, distinguished engineers Shiyu Zhou and Yong Chen deliver a rigorous and practical introduction to the random effects modeling approach for industrial system diagnosis and prognosis. In the book’s two parts, general statistical concepts and useful theory are described and explained, as are industrial diagnosis and prognosis methods. The accomplished authors describe and model fixed effects, random effects, and variation in univariate and multivariate datasets and cover the application of the random effects approach to diagnosis of variation sources in industrial processes. They offer a detailed performance comparison of different diagnosis methods before moving on to the application of the random effects approach to failure prognosis in industrial processes and systems. In addition to presenting the joint prognosis model, which integrates the survival regression model with the mixed effects regression model, the book also offers readers: A thorough introduction to describing variation of industrial data, including univariate and multivariate random variables and probability distributions Rigorous treatments of the diagnosis of variation sources using PCA pattern matching and the random effects model An exploration of extended mixed effects model, including mixture prior and Kalman filtering approach, for real time prognosis A detailed presentation of Gaussian process model as a flexible approach for the prediction of temporal degradation signals Ideal for senior year undergraduate students and postgraduate students in industrial, manufacturing, mechanical, and electrical engineering, Industrial Data Analytics for Diagnosis and Prognosis is also an indispensable guide for researchers and engineers interested in data analytics methods for system diagnosis and prognosis.

Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner

Author : Olivia Parr-Rud
File Size : 23.18 MB
Format : PDF, ePub, Docs
Download : 361
Read : 315
Download »
This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. This beginnner's guide with clear, illustrated, step-by-step instructions will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. --

Marketing Analytics A Practitioner s Guide To Marketing Analytics And Research Methods

Author : Ashok Charan
File Size : 74.50 MB
Format : PDF, ePub
Download : 352
Read : 1207
Download »
The digital age has transformed the very nature of marketing. Armed with smartphones, tablets, PCs and smart TVs, consumers are increasingly hanging out on the internet. Cyberspace has changed the way they communicate, and the way they shop and buy. This fluid, de-centralized and multidirectional medium is changing the way brands engage with consumers.At the same time, technology and innovation, coupled with the explosion of business data, has fundamentally altered the manner we collect, process, analyse and disseminate market intelligence. The increased volume, variety and velocity of information enables marketers to respond with much greater speed, to changes in the marketplace. Market intelligence is timelier, less expensive, and more accurate and actionable.Anchored in this age of transformations, Marketing Analytics is a practitioner's guide to marketing management in the 21st century. The text devotes considerable attention to the way market analytic techniques and market research processes are being refined and re-engineered. Written by a marketing veteran, it is intended to guide marketers as they craft market strategies, and execute their day to day tasks.