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Other titles in the FT Press Operations Management series:

Managerial Analytics: An Applied Guide to Principles, Methods, Tools, and Best Practices (FT Press Operations Management)

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Synopses & Reviews

Publisher Comments:

“A manager who wants to learn the underlying techniques and their applicability is bound to tutorials from a data scientist with good communication skills. This book gives managers the opportunity to learn the concepts by themselves, and thus, it should be on a bookshelf of everyone who leads and manages analytics efforts.”

–Diego Klabjan, Professor of Industrial Engineering and Management Sciences, Director of Master of Science in Analytics Program, Northwestern University

 

“Watson and Nelson help to bridge the gap between the marketing hype and the technical details, making it easier to evaluate analytics-based solutions and better understand their potential.”

–Irv Lustig, Ph.D., Manager, Optimization and Mathematical Software, Business Analytics and Math Science, IBM Research at IBM

 

Analytics and Big Data Demystified

The up-to-the-minute introduction for every manager

• Everything you need to know to get results!

• Concepts, applications, tools, techniques, and pitfalls to avoid

• How to derive more value from tools and data you already own

Want to start leveraging analytics and Big Data for profit? Managerial Analytics is your ideal first resource. Whatever your industry or management role, this up-to-date guide will help you get started fast, get started right, and quickly start driving value.

 

Right now, analytics is helping organizations do everything from saving money to saving lives. Chances are, your organization has enormous opportunities to derive value through analytics—if you apply it properly.

 

Managerial Analytics will show you how. This book is for every manager who knows they can benefit from analytics, but doesn’t know where to start…every consultant and software provider who wants to deliver better results to clients…every professional tasked with evaluating analytics products or vendors.

 

Using practical examples, the authors demystify each form of analytics: descriptive analytics for presenting and visualizing data; predictive analytics for recognizing trends and relationships; and prescriptive analytics for optimizing decisions based on what you know and expect.

 

For each, they introduce today’s best tools and techniques, offering just enough technical detail to help you make the best possible choices. You’ll learn how modern analytics differs from older techniques; what kind of questions you can now answer for the first time; and how to extend the power of analytics throughout your entire organization.

 

• What analytics is, what it isn’t…

…and what it really means to “compete on analytics”

• Developing the right mindset for the successful analytics project

Thinking clearly about your problem and your data

• Leveraging the tools and data you already have

Surprising opportunities to gain value from existing resources

• Overcoming pitfalls that lead to the wrong answers

Getting the right samples, avoiding “confirmation bias,” and more

Synopsis:

The field of analytics is rapidly evolving, making it difficult for professionals and students to keep up the most current and effective applications.  Managerial Analytics will help readers sort through all these new options and identify the appropriate solution. In this reference, authors Watson, Nelson and Cacioppi accurately define and identify the components of analytics and big data, giving readers the knowledge needed to effectively assess new aspects and applications. Building on this foundation, they review tools and solutions, identify the offerings best aligned to one’s requirements, and show how to tailor analytics applications to an organization’s specific needs.  Drawing on extensive experience implementing, planning, and researching advanced analytics for business, the authors clearly explain all this, and more:  

  • What analytics is and isn’t: great examples of successful usage – and other examples where the term is being degraded into meaninglessness
  • The difference between using analytics and “competing on analytics”
  • How to get started with big data, by analyzing the most relevant data
  • Components of analytics systems, from databases and Excel to BI systems and beyond
  • Anticipating and overcoming “confirmation bias” and other pitfalls
  • Understanding predictive analytics and getting the high-quality random samples necessary
  • Applying game theory, Efficient Frontier, benchmarking, and revenue management models
  • Implementing optimization at the small and large scale, and using it to make “automatic decisions”

About the Author

MICHAEL WATSON (Evanston, IL) is a recognized leader in the supply chain network design community. He has been involved with network design projects since 1998 through LogicTools, ILOG, IBM, and now The Optimization and Analytics Group. He is also an adjunct professor at Northwestern University teaching Master’s level operations and supply chain courses in the McCormick School of Engineering’s MEM) and Analytics programs and Kellogg’s MMM program.

DEREK NELSON (Evanston, IL) is Adjunct Professor at Northwestern University in the McCormick School of Engineering, and worldwide client technical lead for IBM’s ILOG Supply Chain Applications. He has been involved in the design and implementation of optimization based solutions at many companies across a wide range of industries since 2001; and has been a guest speaker at universities including MIT and Ohio State. PETE CACIOPPI (Eugene, OR) is lead scientist for IBM’s network design product, He has been working on this product since 1997, and is responsible for translating business problems into mathematical optimization problems, and finding innovative ways to solve these complex problems. He holds an M.S. in Operations Research and Computer Science from the University of Chicago.

Table of Contents

Part 1: State of the Field

1. Definition of Analytics

2. Descriptive Analytics

3. Predictive Analytics

Part 2: Tools and Applications

4. Prisoners Dilemma and Game Theory

5. Efficient Frontier and benchmarking

6. Optimization

 

The first book that completely demystifies modern “big data” analytics, explains the tools and applications, guides you around the pitfalls, and helps you apply analytics for profit.

Product Details

ISBN:
9780133407426
Author:
Watson, Michael
Publisher:
Pearson
Author:
Nelson, Derek
Author:
Cacioppi, Peter
Subject:
BUSINESS STRATEGY
Subject:
Production & Operations Management
Subject:
big data; business analytics; managerial analytics; analytics; big data problems; big data case studies; predictive models; optimization; automatic decisions; supply chain management; operations management
Subject:
Business management
Copyright:
Series:
FT Press Analytics
Publication Date:
20131215
Binding:
HARDCOVER
Language:
English
Pages:
256
Dimensions:
9.255 x 6.298 x 0.914 in 481 gr

Related Subjects

Business » Business Plans
Business » General
Business » Human Resource Management
Business » Management
Business » Project Management
Business » Strategy
Business » Writing
Reference » Science Reference » Technology
Science and Mathematics » Mathematics » Probability and Statistics » Statistics

Managerial Analytics: An Applied Guide to Principles, Methods, Tools, and Best Practices (FT Press Operations Management) New Hardcover
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$69.99 In Stock
Product details 256 pages Pearson - English 9780133407426 Reviews:
"Synopsis" by ,

The field of analytics is rapidly evolving, making it difficult for professionals and students to keep up the most current and effective applications.  Managerial Analytics will help readers sort through all these new options and identify the appropriate solution. In this reference, authors Watson, Nelson and Cacioppi accurately define and identify the components of analytics and big data, giving readers the knowledge needed to effectively assess new aspects and applications. Building on this foundation, they review tools and solutions, identify the offerings best aligned to one’s requirements, and show how to tailor analytics applications to an organization’s specific needs.  Drawing on extensive experience implementing, planning, and researching advanced analytics for business, the authors clearly explain all this, and more:  

  • What analytics is and isn’t: great examples of successful usage – and other examples where the term is being degraded into meaninglessness
  • The difference between using analytics and “competing on analytics”
  • How to get started with big data, by analyzing the most relevant data
  • Components of analytics systems, from databases and Excel to BI systems and beyond
  • Anticipating and overcoming “confirmation bias” and other pitfalls
  • Understanding predictive analytics and getting the high-quality random samples necessary
  • Applying game theory, Efficient Frontier, benchmarking, and revenue management models
  • Implementing optimization at the small and large scale, and using it to make “automatic decisions”
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