Data Analytics and Big Data

Data Analytics and Big Data

The main purpose of this book is to investigate, explore and describe approaches and methods to facilitate data understanding through analytics solutions based on its principles, concepts and applications.

Author: Soraya Sedkaoui

Publisher: John Wiley & Sons

ISBN: 9781786303264

Category: Computers

Page: 220

View: 803

The main purpose of this book is to investigate, explore and describe approaches and methods to facilitate data understanding through analytics solutions based on its principles, concepts and applications. But analyzing data is also about involving the use of software. For this, and in order to cover some aspect of data analytics, this book uses software (Excel, SPSS, Python, etc) which can help readers to better understand the analytics process in simple terms and supporting useful methods in its application.
Categories: Computers

Big Data Analytics Systems Algorithms Applications

Big Data Analytics  Systems  Algorithms  Applications

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis.

Author: C.S.R. Prabhu

Publisher: Springer Nature

ISBN: 9789811500947

Category: Computers

Page: 412

View: 442

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.
Categories: Computers

BIG DATA ANALYTICS

BIG DATA ANALYTICS

This book dwells on all the aspects of Big Data Analytics and covers the subject in its entirety.

Author: Raj Kamal

Publisher: McGraw-Hill Education

ISBN: 9789353164973

Category: Computers

Page: 534

View: 364

Big Data Analytics(BDA) is a rapidly evolving field that finds applications in many areas such as healthcare, medicine, advertising, marketing, and sales. This book dwells on all the aspects of Big Data Analytics and covers the subject in its entirety. It comprises several illustrations, sample codes, case studies and real-life analytics of datasets such as toys, chocolates, cars, and student’s GPAs. The book will serve the interests of undergraduate and post graduate students of computer science and engineering, information technology, and related disciplines. It will also be useful to software developers. Salient Features: - Comprehensive coverage on Big Data NoSQL Column-family, Object and Graph databases, programming with open-source Big Data - Hadoop and Spark ecosystem tools, such as MapReduce, Hive, Pig, Spark, Python, Mahout, Streaming, GraphX - Inclusion of latest topics machine learning, K-NN, predictive-analytics, similar and frequent item sets, clustering, decision-tree, classifiers recommenders, real-time streaming data analytics, graph networks, text, web structure, web-links, social network analytics. - Web supplement includes instructional PPT’s, solution of exercises, analysis using open source datasets of a car company, and topics for advanced learning.
Categories: Computers

Big Data Science Analytics

Big Data Science   Analytics

Big data is defined as collections of datasets whose volume, velocity or variety is so large that it is difficult to store, manage, process and analyze the data using traditional databases and data processing tools.

Author: Arshdeep Bahga

Publisher: Vpt

ISBN: 0996025545

Category: Computers

Page: 544

View: 365

Big data is defined as collections of datasets whose volume, velocity or variety is so large that it is difficult to store, manage, process and analyze the data using traditional databases and data processing tools. We have written this textbook to meet this need at colleges and universities, and also for big data service providers.
Categories: Computers

Analytics and Data Science

Analytics and Data Science

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.

Author: Amit V. Deokar

Publisher: Springer

ISBN: 9783319580975

Category: Computers

Page: 297

View: 281

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.
Categories: Computers

Big Data Analytics Methods

Big Data Analytics Methods

This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.

Author: Peter Ghavami

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 9781547401581

Category: Business & Economics

Page: 254

View: 901

Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.
Categories: Business & Economics

Data Science

Data Science

This book, Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't, presents you with a step-by-step approach to Data Science as well as secrets only ...

Author: Herbert Jones

Publisher: Createspace Independent Publishing Platform

ISBN: 172964239X

Category:

Page: 128

View: 796

Did you know that the value of data usage has increased job opportunities, but that there are few specialists? These days, everyone is aware of the role that data can play, whether it is an election, business or education. But how can you start working in a wide interdisciplinary field that is occupied with so much hype? This book, Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't, presents you with a step-by-step approach to Data Science as well as secrets only known by the best Data Scientists. It combines analytical engineering, Machine Learning, Big Data, Data Mining, and Statistics in an easy to read and digest method. Data gathered from scientific measurements, customers, IoT sensors, and so on is very important only when one can draw meaning from it. Data Scientists are professionals that help disclose interesting and rewarding challenges of exploring, observing, analyzing, and interpreting data. To do that, they apply special techniques that help them discover the meaning of data. Becoming the best Data Scientist is more than just mastering analytic tools and techniques. The real deal lies in the way you apply your creative ability like expert Data Scientists. This book will help you discover that and get you there. The goal with Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't is to help you expand your skills from being a basic Data Scientist to becoming an expert Data Scientist ready to solve real-world data centric issues. At the end of this book, you will learn how to combine Machine Learning, Data Mining, analytics, and programming, and extract real knowledge from data. As you read, you will discover important statistical techniques and algorithms that are helpful in learning Data Science. When you have finished, you will have a strong foundation to help you explore many other fields related to Data Science. This book will discuss the following topics: What Data Science is What it takes to become an expert in Data Science Best Data Mining techniques to apply in data Data visualization Logistic regression Data engineering Machine Learning Big Data Analytics And much more! Don't waste any time. Grab your copy today and learn quick tips from the best Data scientists!
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Big Data Analytics

Big Data Analytics

Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics.

Author: Mrutyunjaya Panda

Publisher: CRC Press

ISBN: 9781351622592

Category: Business & Economics

Page: 316

View: 948

Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.
Categories: Business & Economics

Handbook of Big Data Analytics

Handbook of Big Data Analytics

Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field.

Author: Wolfgang Karl Härdle

Publisher: Springer

ISBN: 9783319182841

Category: Computers

Page: 538

View: 342

Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.
Categories: Computers

Understanding Big Data Analytics for Enterprise Class Hadoop and Streaming Data

Understanding Big Data  Analytics for Enterprise Class Hadoop and Streaming Data

This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform.

Author: Paul Zikopoulos

Publisher: McGraw Hill Professional

ISBN: 9780071790543

Category: Computers

Page: 176

View: 444

Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data--volume, variety, and velocity--are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide. Learn how IBM hardens Hadoop for enterprise-class scalability and reliability Gain insight into IBM's unique in-motion and at-rest Big Data analytics platform Learn tips and tricks for Big Data use cases and solutions Get a quick Hadoop primer
Categories: Computers

Managerial Perspectives on Intelligent Big Data Analytics

Managerial Perspectives on Intelligent Big Data Analytics

While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers ...

Author: Sun, Zhaohao

Publisher: IGI Global

ISBN: 9781522572787

Category: Computers

Page: 335

View: 337

Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.
Categories: Computers

Cloud Computing for Geospatial Big Data Analytics

Cloud Computing for Geospatial Big Data Analytics

This book introduces the latest research findings in cloud, edge, fog, and mist computing and their applications in various fields using geospatial data.

Author: Himansu Das

Publisher: Springer

ISBN: 9783030033590

Category: Computers

Page: 289

View: 713

This book introduces the latest research findings in cloud, edge, fog, and mist computing and their applications in various fields using geospatial data. It solves a number of problems of cloud computing and big data, such as scheduling, security issues using different techniques, which researchers from industry and academia have been attempting to solve in virtual environments. Some of these problems are of an intractable nature and so efficient technologies like fog, edge and mist computing play an important role in addressing these issues. By exploring emerging advances in cloud computing and big data analytics and their engineering applications, the book enables researchers to understand the mechanisms needed to implement cloud, edge, fog, and mist computing in their own endeavours, and motivates them to examine their own research findings and developments.
Categories: Computers

Scala Programming for Big Data Analytics

Scala Programming for Big Data Analytics

This is followed by sections on Scala fundamentals including mutable/immutable variables, the type hierarchy system, control flow expressions and code blocks.

Author: Irfan Elahi

Publisher: Apress

ISBN: 9781484248102

Category: Business & Economics

Page: 306

View: 679

Gain the key language concepts and programming techniques of Scala in the context of big data analytics and Apache Spark. The book begins by introducing you to Scala and establishes a firm contextual understanding of why you should learn this language, how it stands in comparison to Java, and how Scala is related to Apache Spark for big data analytics. Next, you’ll set up the Scala environment ready for examining your first Scala programs. This is followed by sections on Scala fundamentals including mutable/immutable variables, the type hierarchy system, control flow expressions and code blocks. The author discusses functions at length and highlights a number of associated concepts such as functional programming and anonymous functions. The book then delves deeper into Scala’s powerful collections system because many of Apache Spark’s APIs bear a strong resemblance to Scala collections. Along the way you’ll see the development life cycle of a Scala program. This involves compiling and building programs using the industry-standard Scala Build Tool (SBT). You’ll cover guidelines related to dependency management using SBT as this is critical for building large Apache Spark applications. Scala Programming for Big Data Analytics concludes by demonstrating how you can make use of the concepts to write programs that run on the Apache Spark framework. These programs will provide distributed and parallel computing, which is critical for big data analytics. What You Will Learn See the fundamentals of Scala as a general-purpose programming language Understand functional programming and object-oriented programming constructs in Scala Use Scala collections and functions Develop, package and run Apache Spark applications for big data analytics Who This Book Is For Data scientists, data analysts and data engineers who intend to use Apache Spark for large-scale analytics. /div
Categories: Business & Economics

Big Data Analytics Methods and Applications

Big Data Analytics   Methods and Applications

Big Data Analytics - Methods and Applications is a comprehensive book that examines various big data modelling and analytics approaches, infrastructure and security issues in analysis of big data, applications of big data in business, ...

Author: Jovan Pehcevski

Publisher: Arcler Press

ISBN: 1773615041

Category: Computers

Page: 428

View: 360

Big Data Analytics - Methods and Applications is a comprehensive book that examines various big data modelling and analytics approaches, infrastructure and security issues in analysis of big data, applications of big data in business, finance and management. Provides the readers with insights on methodology and applications of Big Data Analytics so as to understand the practical use of big data analytics along with the opportunities and challenges faced during the course.
Categories: Computers

Big Data Analytics with Hadoop 3

Big Data Analytics with Hadoop 3

What you will learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more ...

Author: Sridhar Alla

Publisher: Packt Publishing Ltd

ISBN: 9781788624954

Category: Computers

Page: 482

View: 266

Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3 Key Features Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink Exploit big data using Hadoop 3 with real-world examples Book Description Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. What you will learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more efficient big data processing Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics Set up a Hadoop cluster on AWS cloud Perform big data analytics on AWS using Elastic Map Reduce Who this book is for Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3’s powerful features, or you’re new to big data analytics. A basic understanding of the Java programming language is required.
Categories: Computers

Big Data Analytics for Intelligent Healthcare Management

Big Data Analytics for Intelligent Healthcare Management

The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data.

Author: Nilanjan Dey

Publisher: Academic Press

ISBN: 9780128181478

Category: Science

Page: 312

View: 786

Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data. Examines the methodology and requirements for development of big data architecture, big data modeling, big data as a service, big data analytics, and more Discusses big data applications for intelligent healthcare management, such as revenue management and pricing, predictive analytics/forecasting, big data integration for medical data, algorithms and techniques, etc. Covers the development of big data tools, such as data, web and text mining, data mining, optimization, machine learning, cloud in big data with Hadoop, big data in IoT, and more
Categories: Science

Practical Guide to SAP HANA and Big Data Analytics

Practical Guide to SAP HANA and Big Data Analytics

In this book written for SAP BI, big data, and IT architects, the authors expertly provide clear recommendations for building modern analytics architectures running on SAP HANA technologies.

Author: Dominique Alfermann

Publisher: Espresso Tutorials GmbH

ISBN: 9783960128649

Category:

Page: 235

View: 809

In this book written for SAP BI, big data, and IT architects, the authors expertly provide clear recommendations for building modern analytics architectures running on SAP HANA technologies. Explore integration with big data frameworks and predictive analytics components. Obtain the tools you need to assess possible architecture scenarios and get guidelines for choosing the best option for your organization. Know your options for on-premise, in the cloud, and hybrid solutions. Readers will be guided through SAP BW/4HANA and SAP HANA native data warehouse scenarios, as well as field-tested integration options with big data platforms. Explore migration options and architecture best practices. Consider organizational and procedural changes resulting from the move to a new, up-to-date analytics architecture that supports your data-driven or data-informed organization. By using practical examples, tips, and screenshots, this book explores: - SAP HANA and SAP BW/4HANA architecture concepts - Predictive Analytics and Big Data component integration - Recommendations for a sustainable, future-proof analytics solutions - Organizational impact and change management
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Data Science and Big Data Analytics

Data Science and Big Data Analytics

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use.

Author: EMC Education Services

Publisher: John Wiley & Sons

ISBN: 9781118876053

Category: Computers

Page: 432

View: 439

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!
Categories: Computers

Big Data Analytics

Big Data Analytics

This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big ...

Author: Saumyadipta Pyne

Publisher: Springer

ISBN: 9788132236283

Category: Computers

Page: 276

View: 226

This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.
Categories: Computers

Big Data Analytics for E Commerce Complete Self Assessment Guide

Big Data Analytics for E Commerce Complete Self Assessment Guide

You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in.

Author: Gerardus Blokdyk

Publisher: 5starcooks

ISBN: 0655502149

Category:

Page: 290

View: 823

Is Big Data Analytics for E-Commerce dependent on the successful delivery of a current project? Is a fully trained team formed, supported, and committed to work on the Big Data Analytics for E-Commerce improvements? Is Big Data Analytics for E-Commerce currently on schedule according to the plan? Are improvement team members fully trained on Big Data Analytics for E-Commerce? What is the total cost related to deploying Big Data Analytics for E-Commerce, including any consulting or professional services? This amazing Big Data Analytics for E-Commerce self-assessment will make you the reliable Big Data Analytics for E-Commerce domain authority by revealing just what you need to know to be fluent and ready for any Big Data Analytics for E-Commerce challenge. How do I reduce the effort in the Big Data Analytics for E-Commerce work to be done to get problems solved? How can I ensure that plans of action include every Big Data Analytics for E-Commerce task and that every Big Data Analytics for E-Commerce outcome is in place? How will I save time investigating strategic and tactical options and ensuring Big Data Analytics for E-Commerce costs are low? How can I deliver tailored Big Data Analytics for E-Commerce advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Big Data Analytics for E-Commerce essentials are covered, from every angle: the Big Data Analytics for E-Commerce self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Big Data Analytics for E-Commerce outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Big Data Analytics for E-Commerce practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Big Data Analytics for E-Commerce are maximized with professional results. Your purchase includes access details to the Big Data Analytics for E-Commerce self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard, and... - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation ...plus an extra, special, resource that helps you with project managing. INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
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