The Data and Analytics Playbook

The book teaches readers how to use proven methods and accelerators to break through data obstacles to provide faster, higher quality delivery of mission critical programs.

The Data and Analytics Playbook

Author: Lowell Fryman

Publisher: Morgan Kaufmann

ISBN: 0128025476

Page: 292

View: 431

The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality explores the way in which data continues to dominate budgets, along with the varying efforts made across a variety of business enablement projects, including applications, web and mobile computing, big data analytics, and traditional data integration. The book teaches readers how to use proven methods and accelerators to break through data obstacles to provide faster, higher quality delivery of mission critical programs. Drawing upon years of practical experience, and using numerous examples and an easy to understand playbook, Lowell Fryman, Gregory Lampshire, and Dan Meers discuss a simple, proven approach to the execution of multiple data oriented activities. In addition, they present a clear set of methods to provide reliable governance, controls, risk, and exposure management for enterprise data and the programs that rely upon it. In addition, they discuss a cost-effective approach to providing sustainable governance and quality outcomes that enhance project delivery, while also ensuring ongoing controls. Example activities, templates, outputs, resources, and roles are explored, along with different organizational models in common use today and the ways they can be mapped to leverage playbook data governance throughout the organization. Provides a mature and proven playbook approach (methodology) to enabling data governance that supports agile implementation Features specific examples of current industry challenges in enterprise risk management, including anti-money laundering and fraud prevention Describes business benefit measures and funding approaches using exposure based cost models that augment risk models for cost avoidance analysis and accelerated delivery approaches using data integration sprints for application, integration, and information delivery success

Exam Prep for The Data and Analytics Playbook

This book provides over 2,000 Exam Prep questions and answers to accompany the text The Data and Analytics Playbook Items include highly probable exam items: World Wide Web, Microprocessor, Arithmetic logic unit, OS X, SMTPS, Executable, ...

Exam Prep for  The Data and Analytics Playbook

Author:

Publisher:

ISBN:

Page:

View: 382

Data Analytics Applied to the Mining Industry

Business and Human Rights Journal, 2016. 1(2): pp. 307–313. 40. Fryman, L., G.
Lampshire, and D. Meers, The Data and Analytics Playbook: Proven Methods for
Governed Data and Analytic Quality. 2016: Morgan Kaufmann, Burlington, MA.

Data Analytics Applied to the Mining Industry

Author: Ali Soofastaei

Publisher: CRC Press

ISBN: 0429781768

Page: 254

View: 667

Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how data needs to be collected, stored and managed to enable the different advanced data analytics methods to be applied effectively in practice, through use of case studies, and worked examples. Aimed at graduate students, researchers, and professionals in the industry of mining engineering, this book: Explains how to implement advanced data analytics through case studies and examples in mining engineering Provides approaches and methods to improve data-driven decision making Explains a concise overview of the state of the art for Mining Executives and Managers Highlights and describes critical opportunity areas for mining optimization Brings experience and learning in digital transformation from adjacent sectors

Analytics Best Practices A Business driven Playbook for Creating Value through Data Analytics

Building the right data analytics team starts at the highest level in the company. At
a strategic or board level, there is still a lack of awareness on the potential of
digital technologies on business performance. McKinsey's research says just 16
% ...

Analytics Best Practices  A Business driven Playbook for Creating Value through Data Analytics

Author: Prashanth H Southekal, PhD, MBA

Publisher: Technics Publications

ISBN: 1634628292

Page: 208

View: 850

Deliver enterprise data analytics success by following Prashanth’s prescriptive and practical techniques. Today, organizations across the globe are looking at ways to glean insights from data analytics and make good business decisions. However, not many business enterprises are successful in data analytics. According to Gartner, 80% of analytics programs do not deliver business outcomes. Mckinsey consulting says, less than 20% of the companies have achieved analytics at scale. So, how can a business enterprise avoid analytics failure and deliver business results? This book provides ten key analytics best practices that will improve the odds of delivering enterprise data analytics solutions successfully. It is intended for anyone who has a stake and interest in deriving insights from data analytics. The three key differentiating aspects of this book are: · Practicality. This book offers prescriptive, superior, and practical guidance. · Completeness. This book looks at data analytics holistically across the four key data analytics domains - data management, data engineering, data science, and data visualization. · Neutrality. This book is technologically agnostic and looks at analytics concepts without any reference to commercial analytics products and technologies. Dr. Southekal proves why he is one of the leading thinkers on data and analytics today. ‘Analytics Best Practices’ is an indispensable guide for business leaders and those looking to get into the analytics field on the nuances, challenges, and immense opportunities with data. Douglas B. Laney Principal, Data & Analytics Strategy, Caserta, and author of “Infonomics” Dr. Southekal’s book is a treasure trove of best practices and practical examples from the field of Data Analytics. Upen Varanasi CEO & Co-Founder, Riversand Technologies What I like about this book is its focus on real-world best practices with an extensive set of practical tips and tricks. It provides an important bridge between the data management and business operations sides of a business. Michael Wade Professor of Innovation & Strategy, IMD Business School Prashanth’s book is accessible and practical – an excellent guide for corporate leaders who want to produce meaningful business results from the use of data and analytics to create true business value. Irina Pelphrey Senior Director, Walmart Corporation This book is a must on the desks of business executives and decision makers at all levels in an organization who want to truly understand what it takes to become a successful data driven organization. Ram Kumar Senior Vice President, Quantium Dr. Prashanth Southekal has created a practical guidebook for realizing business value from data and analytics investments. Highly recommended. Randy Bean Founder & CEO, NewVantage Partners Prashanth’s second book starts with the right title – it is always about BUSINESS VALUE. The practices explored here will help anyone interested to achieve these goals. Mario Faria Gartner Research Board The Analytics Best Practices book is one of the most comprehensive and well-researched books I have come across on data analytics. Ameet Shetty Former Chief Data and Analytics Officer, McDonald's Corporation I would encourage all professionals to read this easy to navigate, thoughtful and pragmatic book as it is relevant to all of us seeking to maximize the ROI for our organizations. Lisa M. Wardlaw Former EVP, Global Chief Digital Strategy Officer, MunichRe Deriving actionable insights from data requires that linkage to be clear between art and science and this book does just that. Chris Leonard, Director, Digital Strategy & Transformation, Plains Midstream Prashanth’s book simplifies the complex world of data analytics, and one to understand the drivers of bringing valued results to an organization. Matthew Joyce Senior Solution Architect, SAS-Institute

The Data Driven Transformation Playbook

Packed with case studies and real world examples, the book brings together views, opinions and practitioners experience for the first time along with the authors' original theories, concepts and methodologies.

The Data Driven Transformation Playbook

Author: CAROLINE. JACKSON CARRUTHERS (PETER.)

Publisher:

ISBN: 9781783303878

Page: 208

View: 996

How do you start the journey to truly getting the most from your data? Many businesses need or want to transform to survive or to thrive. The digital transformation was all about technology and platforms driving business and customers on line. Data enabled transformation is about exploiting data to provide key insights to drive business value. The Data Driven Transformation Playbook is a must-have guide to transforming your business into a data enabled organisation. Written by Caroline Carruthers and Peter Jackson, two award-winning CDOs and authors of the bestselling Chief Data Officers Playbook, it provides direct, engaging and pragmatic guidance for current and aspiring CDOs, CEOs, COOs, data change practitioners and programme managers. Packed with case studies and real world examples, the book brings together views, opinions and practitioners experience for the first time along with the authors' original theories, concepts and methodologies. It takes a step-by-step approach covering: why organisations would want to be data enabled checking readiness preparing for transformation making the change happen embedding the new culture and moving forward.

Analytics Best Practices

It is intended for anyone who has a stake and interest in deriving insights from data analytics. The three key differentiating aspects of this book are: Practicality. This book offers prescriptive, superior, and practical guidance.

Analytics Best Practices

Author: Prashanth Southekal

Publisher: Technics Publications

ISBN: 9781634628273

Page: 208

View: 336

Deliver enterprise data analytics success by following Prashanth's prescriptive and practical techniques. Today, organizations across the globe are looking at ways to glean insights from data analytics and make good business decisions. However, not many business enterprises are successful in data analytics. According to Gartner, 80% of analytics programs do not deliver business outcomes. Mckinsey consulting says, less than 20% of the companies have achieved analytics at scale. So, how can a business enterprise avoid analytics failure and deliver business results? This book provides ten key analytics best practices that will improve the odds of delivering enterprise data analytics solutions successfully. It is intended for anyone who has a stake and interest in deriving insights from data analytics. The three key differentiating aspects of this book are: Practicality. This book offers prescriptive, superior, and practical guidance. Completeness. This book looks at data analytics holistically across the four key data analytics domains - data management, data engineering, data science, and data visualization. Neutrality. This book is technologically agnostic and looks at analytics concepts without any reference to commercial analytics products and technologies. Dr. Southekal proves why he is one of the leading thinkers on data and analytics today. 'Analytics Best Practices' is an indispensable guide for business leaders and those looking to get into the analytics field on the nuances, challenges, and immense opportunities with data. Douglas B. Laney Principal, Data & Analytics Strategy, Caserta, and author of "Infonomics"

The Analytics Lifecycle Toolkit

140 THE ANALYTICS LIFECYCLE TOOLKIT Table 5.3 Best practice area: Data
sensemaking Process Key Activities Data identification ... As part of the analytics
playbook, we have a number of tools that we can utilize as we tackle challenges.

The Analytics Lifecycle Toolkit

Author: Gregory S. Nelson

Publisher: John Wiley & Sons

ISBN: 1119425069

Page: 464

View: 803

PRAISE FOR THE ANALYTICS LIFECYCLE TOOLKIT "Full of wisdom and experience about analytics, this book's greatest strength is its lifecycle approach. From framing the question to getting results, you'll learn how analytics can really have an impact on organizations." —Thomas H. Davenport, Ph.D., Author of Competing on Analytics and Only Humans Need Apply "This book condenses a lot of deep thinking on the wide field of analytics strategy. Analytics is not easy—there are no quickie AI/BI/ML shortcuts to understanding your data, your business, or your processes. You have to build a diverse team of talent. You have to respect the hazards of 'fishing expeditions' that may need false-discovery-rate adjustments. You should consider designed experiments to get the true behavior of a process, something that observational data may hint at, but not provide complete understanding. There are dimensions of data wrangling, feature engineering, and data sense-making that all call for different skills. But with deep investment in analytics comes deep insight into processes and tremendous opportunity for improvements. This book puts analytics in the context of a strategic business system, with all its dimensions." —John Sall, Ph.D., SAS co-founder and chief architect of JMP "The Analytics Lifecycle Toolkit provides a clear prescription for organizations aiming to develop a high-performing and scalable analytics capability. Greg organizes and develops with unusual clarity some of the critical nontechnical aspects of the analytics value-chain, and links them with the technical as building blocks in a comprehensive practice. Studying this map of how to negotiate the challenges to effectiveness and efficiency in analytics could save organizations months, or even years of painful trial and error on the road to proficiency." —Scott Radcliffe, Executive Director, Data Analytics at Cox Communications "Many books exist that answer the question 'what is the right tool to solve a problem?' This is one of the few books I've read that answers the much more difficult question 'how do we make analytics become transformative throughout our organization?' Incorporating elements of data science, design thinking, and organizational theory, this book is a valuable resource for executives looking to build analytics into their organizational DNA, data scientists looking to expand their organizational reach, and analytics programs that teach students not just how to do data science, but how to use data science to affect tangible change." —Jeremy Petranka, Ph.D., Assistant Dean Master of Quantitative Management at Duke University's Fuqua School of Business "This book is the 'thinking person's guide to analytics.' Greg has gone deep on some topics and provided considerable references across the analytics lifecycle. This is one of the best books on analytics I have read…and I think I have read them all!" —Bob Gladden, Vice President, Enterprise Analytics, Highmark Health

The Chief Data Officer s Playbook

The professional services firm EY currently identifies four technology areas that it
believes are key to innovation: Artificial Intelligence, Robotic Process Automation,
Blockchain and Analytics. At least three of these are pure 'data', therefore it ...

The Chief Data Officer s Playbook

Author: Caroline Carruthers

Publisher: Facet Publishing

ISBN: 1783302577

Page: 208

View: 115

The new and rapidly expanding role of the Chief Data Officer (CDO) is of significant interest and relevance to organisations and data professionals internationally. Written by two practicing CDOs, this new book offers a jargon-free, practical guide to making better decisions based on data. Content covered includes: - why does any organisation need a CDO? - the secret ingredients of the successful CDO - avoiding the hype cycle - building the CDO team - who leads the technology? - the CDO and data governance: enablement not red tape. This book will offer key insights for CDOs looking to understand their position better, for aspiring CDOs and data officers looking at career progression, for those recruiting CDOs, and offers essential knowledge for anyone else operating in the current data environment.

The Marketing Playbook

They also knew that there should be a better, more complete way that would also
take advantage of data types that current analysis methods couldn't handle. And
they had a key insight on the technology that would take analytics from point A ...

The Marketing Playbook

Author: John Zagula

Publisher: Penguin

ISBN: 1440684979

Page: 336

View: 658

Every company needs to figure out the best way to beat the competition. What do you do if the other guy is already dominating the market? Should you challenge them head on or lie low for a while? Should you offer customers high-end features or a low-end price? Or both? During their years at Microsoft, John Zagula and Richard Tong answered such questions so effectively that they helped Microsoft Office and Windows grow from a 10 percent to 90 percent market share. As venture capitalists, Zagula and Tong have continued to test and perfect their system with hundreds of companies of all sizes and at all stages. Now they’re sharing their best ideas and methods in an easy-to-apply book that will be enormously helpful to marketers in every industry and leaders in every size company. The Marketing Playbook explains the five basic strategies for a competitive market—The Drag Race Play, The Best of Both Play, The High-Low Play, The Platform Play, and The Stealth Play. It illustrates how each one works, how to pick the best one for a given situation, and then how to implement it effectively in the real world. Just like a great sports coach with a well-designed playbook, managers who read this book will have the tools, tips, and tricks they need to leapfrog market research, craft a smart strategy, motivate their team, and start scoring major points with customers and against the opposition.

Mapping Innovation A Playbook for Navigating a Disruptive Age

map for Experian's strategy, which they called “Data Solutions and Decisions
Systems” or “DS squared” for short, to exploit the opportunities they saw in the
marketplace (Figure 3.2). It encompassed four key functional areas (data,
analytics, ...

Mapping Innovation  A Playbook for Navigating a Disruptive Age

Author: Greg Satell

Publisher: McGraw Hill Professional

ISBN: 1259862240

Page: 240

View: 613

Map the innovation space—and blaze a path to profits and growth Countless books, articles, and other advice promise leaders solutions to the complex challenges they face. Some offer quick, silver-bullet remedies—a straight line to success!—and some are so technical that readers get lost before they begin. Now, there’s Mapping Innovation, a refreshing alternative in the crowded business innovation space. Engaging and informative without sacrificing substance and expertise, this groundbreaking guide provides thorough background on some of the greatest innovations of the past century as well as . It details the processes that advanced them from inception to world-changing products—and shows you how to replicate their success. Business innovation expert Greg Satell helps you find your way by revealing the four models of innovation: Basic Research, Breakthrough Innovation, Sustaining Innovation, and Disruptive Innovation. One size does not fit all, so he provides a framework—the Innovation Matrix—for discovering which “type” of innovation process best suits the problem you need to solve. It’s about asking the right questions, so that you can apply the right strategies to the problems you need to solve. In the end, you’ll have a crystal clear model for disrupting the marketplace, scaling your efforts to propel your enterprise forqward, and leverage digital platforms to your advantage. Mapping Innovation offers a simple and accessible but powerful approach to developing a strategy that will put you light years ahead of the competition!.

Big Data Big Climb

This book will provide your credit union with the tools it needs to reduce member friction, analyze actual competition, and identify disruption to improve the lives of its members and gain competitive advantage.

Big Data Big Climb

Author: Anne Legg

Publisher:

ISBN:

Page: 153

View: 205

Data is one of the most robust assets Credit Unions have, yet there are few resources available to help the industry leverage this asset. Anne Legg's Big Data Big climb is a must-have guide for those who are looking to improve their members' lives using data. This foundational primer on data transformation uses the metaphor of climbing Mt Kilimanjaro to provide both clarity and a framework on this subject. With sections titled "Which is more mature your data or a teen," and "A Credit Union governs its loans, so why not its data" as well as "Building Credit Union Hakuna Matata" his book cuts through techno-jargon and translates data transformation concepts into a playbook for credit unions to leverage their robust data to create revolutionary member relationships.This must-have guide provides guidance on assessing the current credit union data state, creating an enterprise vision. building member-centric data strategies, demystifying data maturity, establishing a data governance practice, building a data analytics program, developing a data consumptive culture, and building continuous data-centric capabilities. Not only is the book packed with real-world examples, assessment guides, and case studies, the author has created BONUS content available online for only Big Data/Big Climb readers. This book will provide your credit union with the tools it needs to reduce member friction, analyze actual competition, and identify disruption to improve the lives of its members and gain competitive advantage. It is a must-read across boards, leadership teams, department leads, and member contact talent.

Big Data Big Analytics

Emerging Business Intelligence and Analytic Trends for Today's Businesses
Michael Minelli, Michele Chambers, ... The CIO Playbook: Strategies and Best
Practices for IT Leaders to Deliver Value by Nicholas R. Colisto Enterprise IT
Strategy, ...

Big Data  Big Analytics

Author: Michael Minelli

Publisher: John Wiley & Sons

ISBN: 1118239156

Page: 224

View: 921

Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.

Architecting Experience

' The quick answer to this is 'through the application of data and analytics to drive highly relevant, contextual targeted content and adaptive experience', but since this answer is not as easy to achieve as it is to say, Architecting ...

Architecting Experience

Author: Scot R Wheeler

Publisher: World Scientific

ISBN: 9814678430

Page: 280

View: 922

' In a world with a seemingly infinite amount of content and scores of methods for consuming that content, marketing communication today is about appealing to individuals, person by person. Effectively appealing to customers requires delivery of brand experiences built on relevance and recognition of context. Just as in any conversation, delivering relevance in context requires understanding the person one is speaking with and shared environment. Wheeler answers the biggest question facing digital marketers today: "with an ever expanding array of digital touch points at one's disposal, how does one deliver content and experiences around one's brand that build relationships and drives results?" The quick answer to this is "through the application of data and analytics to drive highly relevant, contextual targeted content and adaptive experience", but since this answer is not as easy to achieve as it is to say, Architecting Experience has been designed to help readers develop the understanding of marketing data, technology and analytics required to make this happen. Contents:The Foundations of PersonalizationStrategy, Technology, Science & ArtThe Applied Digital Analytics Playbook (ADAP) Part OneThe Changing World of Owned MediaEarned Media: Organic Social & SEOPaid Media AnalyticsTesting & Optimization. Marketing Automation. AttributionData Management, Models, and AlgorithmsThe Cultural and Organizational Impact of Data Readership: Suitable for postgraduate students in Digital and Direct Marketing Master''s programs and professionals in IT, Research, and Marketing. Key Features:Each chapter includes links to additional references, a set of review questions, and how-to exercisesProvides insight on a wider array of marketing technologies and perspective on how they are applied, overlap and/or complement each other in practice than any competing title, which specialize in one area of technology (e.g. dashboards and reporting, marketing automation, real-time buying)Provides education on the data-driven marketing technologies presently being utilized or adopted within digital marketing in paid, earned and owned channels such as web, social and mobile analytics, Customer Relationship Management tools, Marketing Automation systems, Data Management Platforms and Demand Side Platforms, and reveals how data should ideally flow into, out of and between these systems to make them work most effectively in creating integrated experiences for customersKeywords:Data;Analytics;Measurement;Marketing Analytics;Marketing Automation;Digital Analytics;Marketing Technology;Web Analytics;Mobile Analytics;Mobile measurement;Social Media Analytics;Media Measurement;Marketing Measurement;Marketing ROI;ROMI;Targeting;Personalization;Digital Marketing;Marketing;Experience Design;User Experience;UX'

Profiting from the Data Economy

Will television advertising take a page from the digital playbook with the delivery
of marketing messages based on what is ... organizations, and businesses, the
ability to implement such analytics hinges on the availability of consumer data.

Profiting from the Data Economy

Author: David A. Schweidel

Publisher: Pearson Education

ISBN: 0133819841

Page: 288

View: 270

Today, the insights available through "big data" are potentially limitless – ranging from improved product recommendations and more well-targeted promotions to more efficient public agencies. In Profiting From the Data Economy , cutting-edge academic researcher, David Schweidel, considers the role that individual consumers, innovators and government will play in shaping tomorrow's data economy. For each group, the author identifies both what can be gained and what is at stake. Writing for decision-makers, strategists, and stakeholders of all kinds, he reveals how today's data explosion will affect consumers' relationships with businesses, and the roles government may play in the process. The book puts you in the shoes of individuals generating data, innovators seeking to capitalize on it, and regulators seeking to protect consumers – and shows how all these roles will be increasingly interconnected in the future. For analytics executives; senior managers; CIOs, CEOs, CMOs; marketing specialists, and analysts; and consultants involved with Big Data, marketing, customer privacy, or related issues. This guide will also be valuable in many business analytics, digital marketing, and social media courses and academic programs.

Modeling Techniques in Predictive Analytics with Python and R

A Guide to Data Science Thomas W. Miller ... MapReduce: Simplifed Data
Processing on Large Clusters. ... ESPN The Magazine (Analytics Issue). http://
espn.go.com/blog/playbook/dollars/post/_/id/2935/ meet-the-worlds-top-nba-
gambler.

Modeling Techniques in Predictive Analytics with Python and R

Author: Thomas W. Miller

Publisher: FT Press

ISBN: 013389214X

Page: 448

View: 844

Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Modeling Techniques in Predictive Analytics

Orange: Data mining fruitful and fun—A historical perspective. ... Variable
selection for market basket analysis. ... The Magazine (Analytics Issue). http://
espn.go.com/blog/playbook/dollars/post/_/id/2935/ meet-the-worlds-top-nba-
gambler.

Modeling Techniques in Predictive Analytics

Author: Thomas W. Miller

Publisher: FT Press

ISBN: 0133886190

Page: 384

View: 577

To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Understanding the Predictive Analytics Lifecycle

Through the use of case studies across a range of industries that include banking, megaresorts, mobile operators, healthcare, manufacturing, and retail, the book illustrates each phase of the predictive analytics cycle to create a playbook ...

Understanding the Predictive Analytics Lifecycle

Author: Alberto Cordoba

Publisher:

ISBN: 9781118936740

Page: 221

View: 942

"Covers each phase of the development of a predictive analytics initiative. Through the use of case studies across a range of industries that include banking, megaresorts, mobile operators, healthcare, manufacturing, and retail, the book illustrates each phase of the predictive analytics cycle to create a playbook for future projects"--

Beyond Big Data

Social data analytics takes text segments, as illustrated in Figure 1.6, and creates
structured information, as shown in ... Behavior Maybe our politicians should take
a playbook out of 14 Chapter 1 Introduction to Social MDM Data Distillation.

Beyond Big Data

Author: Martin Oberhofer

Publisher: IBM Press

ISBN: 0133509818

Page: 272

View: 287

Drive Powerful Business Value by Extending MDM to Social, Mobile, Local, and Transactional Data Enterprises have long relied on Master Data Management (MDM) to improve customer-related processes. But MDM was designed primarily for structured data. Today, crucial information is increasingly captured in unstructured, transactional, and social formats: from tweets and Facebook posts to call center transcripts. Even with tools like Hadoop, extracting usable insight is difficult—often, because it’s so difficult to integrate new and legacy data sources. In Beyond Big Data, five of IBM’s leading data management experts introduce powerful new ways to integrate social, mobile, location, and traditional data. Drawing on pioneering experience with IBM’s enterprise customers, they show how Social MDM can help you deepen relationships, improve prospect targeting, and fully engage customers through mobile channels. Business leaders and practitioners will discover powerful new ways to combine social and master data to improve performance and uncover new opportunities. Architects and other technical leaders will find a complete reference architecture, in-depth coverage of relevant technologies and use cases, and domain-specific best practices for their own projects. Coverage Includes How Social MDM extends fundamental MDM concepts and techniques Architecting Social MDM: components, functions, layers, and interactions Identifying high value relationships: person to product and person to organization Mapping Social MDM architecture to specific products and technologies Using Social MDM to create more compelling customer experiences Accelerating your transition to highly-targeted, contextual marketing Incorporating mobile data to improve employee productivity Avoiding privacy and ethical pitfalls throughout your ecosystem Previewing Semantic MDM and other emerging trends

A PRACTITIONER S GUIDE TO BUSINESS ANALYTICS Using Data Analysis Tools to Improve Your Organization s Decision Making and Strategy

" -- Thomas C. Redman, PhD, the Data Doc, Navesink Consulting Group "Executives beware. This is not your typical management book. This book contains real information from analytical professionals who are outside the executive bubble. . .

A PRACTITIONER S GUIDE TO BUSINESS ANALYTICS  Using Data Analysis Tools to Improve Your Organization   s Decision Making and Strategy

Author: Randy Bartlett

Publisher: McGraw-Hill Education

ISBN: 9780071807593

Page: 256

View: 271

The Definitive Guide to Using Analytics for Better Business Decisions "A must-read for anyone who is directly or indirectly leading or managing an analytics function--and anyone who wants to make better decisions based on analytics, not just intuition or an 'overemphasis on industry knowledge, which crowds out good analytics.'" -- Charlotte E. Sibley, President, Sibley Associates, a bioPharma consulting company "Over the long term, those who show the greatest imagination, grow the right skills, build the deepest organizations, and follow rigorous statistical practice will reap the greatest rewards from their analytics efforts. A Practitioner's Guide to Business Analytics lights the way." -- Thomas C. Redman, PhD, the Data Doc, Navesink Consulting Group "Executives beware. This is not your typical management book. This book contains real information from analytical professionals who are outside the executive bubble. . . . Hold on to your seat and be prepared to change the way you think about leaders, leadership qualities, and leadership skills needed for future success in the changing business landscape." -- Thomas J. Scott, Director/Advisor, Marketing Sciences Solutions, TGaS Advisors "Randy Bartlett has written an important and useful book, filling at least some of the large void between books that exhort managers to think more analytically without explaining how, and overly technical books that only quantitative analysts would appreciate. Particular strengths are the recommendations about how to organize to integrate analytical expertise into decision-making and the guidance about how managers can assess whether they are getting good analytical advice." -- Douglas A. Samuelson, D.Sc., President and Chief Scientist, InfoLogix, Inc., Annandale, VA; quantitative analyst, inventor, entrepreneur and executive About the Book: The real tragedy of a company failing while using analytics is the fact that its leaders will have the data to explain the failure, but they won't have the capabilities in place to filter the data and convert it into actionable business insights. One implication of Big Data is that we need to adapt . . . quickly. A Practitioner's Guide to Business Analytics integrates powerful strategies for leveraging analytics inside a business with a how-to playbook of tactics to make it happen. The case for competing based on analytics is clear, but until now, there hasn't been authoritative guidance for inciting a corporate community to evolve into a thriving, analytics-driven environment. This hands-on book gives you the tools, knowledge, and strategies to capture the level of organizational commitment you need to get business analytics up and running in your company. It helps you define what business analytics is, quantify the exponential value it brings to an organization, and show others how to harness its power to gain advantage over competitors. Accomplished business information professional Randy Bartlett brings his comprehensive coverage to life with firsthand accounts of using business analytics at brand-name global companies. Through in-depth examinations of success stories and failures in analytics-based decision making and data analyses, he fully prepares you to: Assess your company's analytics needs and capabilities, and develop a strategic analytics plan Steward the three pillars of Best Statistical Practice and accurately measure the quality of analytics-based decisions and data analyses Build and organize a specialized Business Analytics Team to lead infrastructural changes Upgrade the foundation that supports business analytics--data collection, data software, and data management Create the essential synergy for success between the Business Analytics Team and IT Effectively integrating analytics into everyday decision making, corporate culture, and business strategy is a multifront exercise in leadership, execution, and support. The specialized tools and skill sets required to succeed are finally in one resource--A Practitioner's Guide to Business Analytics.

Event Driven Architecture

The system should allow for a local playbook type model that can be stored for
future use. Ideally, the ... FEDA should not be reliant on a person transmitting
data to another person in the system to achieve a result. Of course ... The system
needs to enable extensive reporting and potential integration with analytics tools.
And ...

Event Driven Architecture

Author: Hugh Taylor

Publisher: Pearson Education

ISBN: 9780321635150

Page: 336

View: 525

Improving Business Agility with EDA Going beyond SOA, enterprises can gain even greater agility by implementing event-driven architectures (EDAs) that automatically detect and react to significant business events. However, EDA planning and deployment is complex, and even experienced SOA architects and developers need expert guidance. In Event-Driven Architecture, four leading IT innovators present both the theory of EDA and practical, step-by-step guidance to implementing it successfully. The authors first establish a thorough and workable definition of EDA and explore how EDA can help solve many of today’s most difficult business and IT challenges. You’ll learn how EDAs work, what they can do today, and what they might be able to do as they mature. You’ll learn how to determine whether an EDA approach makes sense in your environment and how to overcome the difficult interoperability and integration issues associated with successful deployment. Finally, the authors present chapter-length case studies demonstrating how both full and partial EDA implementations can deliver exceptional business value. Coverage includes How SOA and Web services can power event-driven architectures The role of SOA infrastructure, governance, and security in EDA environments EDA core components: event consumers and producers, message backbones, Web service transport, and more EDA patterns, including simple event processing, event stream processing, and complex event processing Designing flexible stateless events that can respond to unpredictable customers, suppliers, and business partners Addressing technical and business challenges such as project management and communication EDA at work: real-world applications across multiple verticals Hugh Taylor is a social software evangelist for IBM Lotus Software. He coauthored Understanding Enterprise SOA and has written extensively on Web services and SOA. He holds an MBA from Harvard Business School. Angela Yochem is an executive in a multinational technology company and is a recognized thought leader in architecture and large-scale technology management. Les Phillips, VP, enterprise architecture, at SunTrust Banks Inc., is responsible for defining the strategic and business IT foundation for many areas of the enterprise. Frank Martinez, EVP, product strategy, at SOA Software, is a recognized expert on distributed, enterprise application, and infrastructure platforms. He has served as senior operating executive for several venture-backed firms and helped build Intershop Communications into a multibillion-dollar public company.