Book Description
Single most authoritative guide from the inventor of the technique.
- Presents unique modeling techniques for e-commerce, and shows strategies for optimizing performance.
- Companion Web site provides updates on dimensional modeling techniques, links related to sites, and source code where appropriate.
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"The latest edition of the single most authoritative guide on dimensional modeling for data warehousing! Dimensional modeling has become the most widely accepted approach for data warehouse design. Here is a complete library of dimensional modeling techniques--the most comprehensive collection ever written. Greatly expanded to cover both basic and advanced techniques for optimizing data warehouse design, this second edition to Ralph Kimball's classic guide is more than sixty percent updated."
Customer Reviews:
Good for Dimentional Modeling.......2007-10-05
I did not get chance to read it, but everybody says it the best source to learn Dimensional Modeling. I our project, the DBA is doing it.
A tool rather than a toolkit.......2007-07-03
This book delivers exactly what it says. Except that word "toolkit" in its title - you'd better think about this book being a single tool, not a whole toolkit. Ralph Kimball actually has a whole lot of books on data warehousing published, this is one of them, a tool in the toolkit. This one seems like a good starting point to the entire series, and it only shows a single facet - the dimensional modeling.
The book explains the basic principles of creating dimensions and fact tables in a data warehouse (assuming a relational star schema), and then dedicates a chapter per industry to show how those principles apply to sales, order management, CRM, accounting, human resources, financial services, telecoms, logistics, education, health care, e-commerce, insurance etc. Each one appears to be significantly different from the others.
There is a couple of teaser chapters starting with "we have that other book covering this, but will brief you out". Nice and makes you want to read the other books too.
The book also includes guidelines to the warehouse building process, in terms like "know your business sponsor", "talk to your users" and so on. Difficult to say what it has to do with dimensional modeling, perhaps it's included in all the books in the series.
There is no word on software, hardware, physical architecture, tuning or performance in this book. It is a textbook in dimensional modeling, period.
The book is written clearly, has a handful of simple and uniform diagrams and is easy to follow. It only leaves you wondering just how exactly large is the whole data warehouse area, how many pieces you need to collect yet.
Recommended.
Building a Data Warehouse.......2007-03-09
Excelent book, it shows how to build a good data warehouse by using the best patterns. I recommend the book to you, it is not as boring as another books regarding this issue, in addition it is cheap.
Great Book.......2007-03-08
This is a great book. Wish there was something like this for relational(3NF) modeling as well.
Raman Marwah.
very bad.... .......2006-12-11
whatever pioneer or genius he is in the DW industry, the book is pretty bad, i wouldn't recommend it at all. the way he tries to convey concepts, explain techniques....
very bad organization, not clear but confusing sometimes, and very poor logical flow... he tries to make a big deal out of DW, when in fact it's not such a fancy or intellect intensive subject. very simple concepts are even hard to understand. someone else would be able to write a book more powerful and straight to the point in 100 pages MAX, and be much more useful....
it sucks when leaders don't know how to express themselves, maybe he was looking forward to have readers learn enough in DW to get projects started but not be able to do squat, and get some business from consulting...
Book Description
Valuable software, realistic examples, and fascinating topics . . . everything you need to master the most widely used management science techniques using Microsoft® Excel™ is right here! Learning to make decisions in today's business world takes training and experience. Cliff Ragsdale--the respected innovator in the field of management science--is an outstanding guide to help you learn the skills you need, use Microsoft Excel for Windows to implement those skills, and gain the confidence to apply what you learn to real business situations. SPREADSHEET MODELING AND DECISION ANALYSIS gives you step-by-step instructions and annotated screen shots to make examples easy to follow. Plus, interesting sections called The World of Management Science show you how each topic has been applied in a real company.
Customer Reviews:
A Good Book for Finance/IT majors.......2007-09-17
This book does what it sets out to do: teach spreadsheet modeling. I'm only on the third chapter, but the author does a good job including step by step instructions on how to create winning models. The author is also very easy to understand. So if you're going to be doing optimization and modeling in your work, I highly recommend this book.
Great book, and includes @RISK.......2007-08-06
Ragsdale really makes spreadsheet modeling accessible to real-world business situations. It was a great asset to my MBA coursework. As a student, it came with a free student version of @RISK risk analysis software as well.
Good practical text.......2006-11-12
A good book for those studying decision making techniques or as a reference for managers looking to upgrade their skills
Decision analysis.......2006-11-02
Excellent book; I am considering it as a textbook for a Managerial Sciences course. The examples are clear and real increasing the interest of the students.
Good book , worth to read.......2006-02-17
This book is designated as the textbook for our master's level management modeling class. The author concerntrated on the application of Microsoft Solver to solve various of optimazation problems that we freqently faced in the real business opreations. Overall, this is good book for entry-level management modeling study.
Book Description
This text helps prospective and experienced principals, administrators, and supervisors increase their knowledge and skills through concepts, case-studies, and simulations. Part I presents important theoretical concepts and research findings that can improve educators’ problem-solving and leadership effectiveness. Part II consists of over 65 reality-based case studies, “In-Basket Exercises,” simulations, and role-plays to illustrate problems and issues. The case studies, simulations, and exercises stimulate class discussion and reflection on key issues facing today’s school administrator and offer guidelines for thoughtful problem-solving and resolution.
Book Description
The second edition of Management Science: The Art of Modeling with Spreadsheets by Steve Powell and Ken Baker will expand upon the essential skills needed to develop real expertise in business modeling. By adding more coverage of management science topics, broader coverage of Excel, focused chapters, and new exercises and cases, this edition will be easier to use in a wide variety of undergraduate and MBA courses.
Customer Reviews:
Can't Deliver.......2007-10-18
In short, I never received the book. Do not do business with this organization.
Average customer rating:
- Obsolete software
- The Art of Modeling with Spreadsheets: Management Science, Spreadsheet Engineering, and Modeling Craft
- nice use of a spreadsheet
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The Art of Modeling with Spreadsheets: Management Science, Spreadsheet Engineering, and Modeling Craft
Stephen G. Powell , and
Kenneth R. Baker
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ASIN: 0471209376 |
Book Description
Successful business modeling is much more than a technical discipline; it's an art. And as in most professional disciplines, you can tell the experts apart from the novices by the creativity they bring to the craft. That's why Steve Powell and Ken Baker's THE ART OF MODELING WITH SPREADSHEETS covers spreadsheet engineering, management science techniques, and those essential craft skills needed to develop real expertise in business modeling. Features: * Balanced and streamlined coverage of spreadsheet engineering, management science techniques, and modeling craft. * The CD-ROM packaged with this text features all of the spreadsheets referred to in the text, as well as three software tools of special importance to business analysts: Premium Solver, Crystal Ball, and Sensitivity Toolkit (featuring four sensitivity tools)
Customer Reviews:
Obsolete software.......2007-04-26
A once useful entree to the spreadsheet modeling literature, this book is now obsolete. The version listed here is copyrighted 2004 but comes with a CD containing release 2000.2 of Crystal Ball which Decisioneering is no longer event supporting. This old version of the software as well as the Advanced Solver add-in has compatibility problems with Windows XP -not to mention Vista, and Wiley does not stand behind the product. Once I loaded the advanced solver, the solver feature no longer produced optimal solutions.
Extremely disappointing to buy a $90 textbook with obsolete software that causes Excel to malfunction and cannot be updated. Impossible to consider this as a class text book. If the publishers will not keep the product current it should be withdrawn from the market, and reputable vendors should at least WARN buyers, if they choose to continue to market and sell this once useful product.
The Art of Modeling with Spreadsheets: Management Science, Spreadsheet Engineering, and Modeling Craft.......2007-03-11
I am very impressed with this book.Overall the book is truly comprehensive and explains the topics using easy examples. These examples can be further explored using EXCEL. I think it will be helpful for the people first learning the lecture of decision analysis.
nice use of a spreadsheet.......2005-04-11
Powell takes the interesting approach of showing how to model a solution to a problem, and using a spreadsheet as the engine within which to embed the solution. Who would have thought in the 70s, when the first computer spreadsheets arose, that one day they could be applied to this?
Much of the book revolves around the issues of modelling. How to extract this from a problem. Here, this is as in many other texts. But we then see how a spreadsheet can be built up, with the equations that relate a group of input cells to write a value in an output cell, being those that model the solution.
To a computer programmer, this use of a spreadsheet might seem a little confining. After all, shouldn't you write code in some general purpose language like C++ or Java, to do this? But the number of programmers who can do this well is fairly small. Whereas spreadsheets have a far broader audience, even in terms of who is able to program them. That is the audience Powell writes for.
Book Description
Designed for learning professionals and drawing on both game creators and instructional designers, Learning by Doing explains how to select, research, build, sell, deploy, and measure the right type of educational simulation for the right situation. It covers simple approaches that use basic or no technology through projects on the scale of computer games and flight simulators. The book role models content as well, written accessibly with humor, precision, interactivity, and lots of pictures. Many will also find it a useful tool to improve communication between themselves and their customers, employees, sponsors, and colleagues. As John Coné, former chief learning officer of Dell Computers, suggests, “Anyone who wants to lead or even succeed in our profession would do well to read this book.”
Download Description
Designed for learning professionals and drawing on both game creators and instructional designers, Learning by Doing explains how to select, research, build, sell, deploy, and measure the right type of educational simulation for the right situation. It covers simple approaches that use basic or no technology through projects on the scale of computer games and flight simulators. The book role models content as well, written accessibly with humor, precision, interactivity, and lots of pictures. Many will also find it a useful tool to improve communication between themselves and their customers, employees, sponsors, and colleagues. As John Con, former chief learning officer of Dell Computers, suggests, & Anyone who wants to lead or even succeed in our profession would do well to read this book.
Customer Reviews:
Learning By Doing.......2007-06-02
Although Aldrich provides a good guide with an overall view of pitfalls or benefits of serious games, I did not think there was enough depth in design and effective learning techniques for my research needs. For an HR or training professional who wants to get an extensive overview in this field, this book would be very useful.
highest recommendations as an introduction to the most current research and pedagogy in educational technology.......2007-04-18
In 1985, I started developing educational computer simulations in DOS on the IBM PC. Since that time I have been involved in every new form of educational technology.... touchscreen, videodisc, CD-ROM, internet. For the last 8 years I have been consulting in corporate training. To try to stay smart, I read everything I can get my hands on.
After reading Learning by Doing by Clark Aldrich, I am completly blown away. Clark is a genius. This book is relavent and puts into context everything I have been doing for 22 years.
This book captures in a fun, easy to read informative style, both the pedagogy and technology for creating state of the art e-learning experiences.
I have never been motivated to write an Amazon review before, but I can't over emphasize my enthusiasm for this book. I have already had several of my clients buy this book. The book is well researched and completely current with latest trends and advancements. The use of bullet lists and charts/ diagrams is very helpful. The index is more comprehensive and complete than any book I have ever seen. Clark's editorial comments are right on target.
The book is not a dense encyclopedia, so if that is what you are looking for then supplement your library with some of the other current titles on blended learning. I give this book my highest recommendations as an introduction/ overview to the most current research and pedagogy in the use of educational technology for corporate training.
I especially recommend this book for corporate trainers who are trying to figure out how to evolve from instructor led to a blended learning paradigm.
Read this book second.......2005-12-08
I just finished reading "Learning By Doing" from cover to cover. Those who are practicing in this field will want to read this book to learn of techniques that might not be readily apparent such as branching stories and interactive spreadsheets. I would recommend that they read "What Video Games Have to Teach Us About Learning and Literacy" by James Paul Gee first, however, as I found the writing style of "Learning By Doing" a little sparse, like fleshed out bullet point slides. It is clear, though, that the author has a lot of experience in this topic and his book is a contribution to the field.
Another Winner by Clark.......2005-10-30
It is no secret that "conventional eLearning" is not as engaging, interactive and interesting-and therefore also not as effective-as it should be. And we know that even current technology has the potential to do much more for "eLearning," or "technology-enabled learning" than we see today. And the rate of change in most technology is accelerating rather than slowing. It is the future potential that excites most of us who are involved in learning technology.
Games and simulations (G&S) is clearly one of the most interesting and exciting areas of learning technology and undoubtedly will play a big part of "next generation (e)Learning," whether in schools, universities, government or industry. This is now being recognized, and evidenced by the growing number of "conferences-within-conferences" (seen most recently at the Training Fall Conference and Expo in Long Beach) or the Serious Games Summit in WDC-to mention just two-dedicated to the topic of G&S.
Clark's book is a most welcome addition to the growing literature covering G&S-and it is a book I highly recommend for anyone interested in learning technology. And if you are involved in some way in learning and training, you cannot avoid technology and if you want to be conversant and be ready to make (smart) decisions on issues that undoubtedly will soon come your way, if they have not already, the ROI on the money spent on Clark's book will no doubt be great.
Clark is a highly respected analyst-with a long history of insightful writing on learning and learning technology (which thousands of practitioners and analysts have enjoyed for a number of years)-as well as a simulation developer, and a business executive (leading Simulearn). Few others can equal his credentials in the area of learning technology so even before the book arrived in my mailbox I knew that this would be one I would enjoy and find very useful. It did not disappoint me.
Not only is it well written but it is a very nice combination of the following:
-- Clear analysis of different types of G&S. This is very useful as it will help future discussion and dialog and reduce the confusion that results when people think they are talking about the same things but in fact are not. Even if one does not agree with Clark's taxonomy he is nevertheless doing us a service by stimulating a richer dialog around these issues.
-- Lots of good examples. Especially for readers interested in using G&S in their organizations, and therefore need to understand the practical side of G&S, Clark's book is very useful as it provides a range of different examples covering the different types of G&S discussed in the book. The examples come from different types of users and sectors, and few application areas exist where G&S could not be highly useful.
-- Challenges that lie ahead. Because of Clark's varied background he is very well positioned to reflect on the challenges that lie ahead and to give a realistic assessment of where we are heading with G&S. As with other analysts, like Clark Quinn, for instance, Aldrich recognizes that the future for G&S is no cakewalk. It is very hard-and often costly-to build high quality, customized simulations, for instance, as Clark learned when he built Virtual Leader. But as tools and technology improve, as more vendors compete and offer better products, and as buyers recognize the benefits of G&S (See the excellent work by James Gee at the Games and Professional Practice Simulations at the Academic ADL Co-lab, for instance) and demand thus accelerates, "effective cost" per user (nominal cost normalized by learning effectiveness) will no longer be a major adoption barrier.
Clark is also one of the most popular speakers on the conference circuit so once you have read his book you will have more to talk to him about when you meet him at one or more of the upcoming events where he will speak.
Eilif Trondsen, Ph.D.
Director
Learning on Demand Program
SRI Consulting Business Intelligence
(...)
Aldrich Framework Extends to Assessment.......2005-09-17
[...]
I really enjoyed "Learning by Doing" Clark. Your frame of thinking helps place things into a space for mulling over the possibilities. I noticed the big "we have no idea" at the end of the interviews on the question of measuring the effectiveness. That is a big challenge, and I think the way there is already being constructed by Mislevy and others in the "adaptive testing" arena - but instead of giving an adaptive test, we'll just make an unobtrusive observation using the same rigorous theory base without hurting the playability, fun, sim aspects.
What you called the "universal truths" (I wasn't as convinced about sticking it in the intersection of games and sims) are also called "generic structures" in the systems dynamics literature - you probably know that. It makes one wonder if in the authoring environments of the future, those structures will be facilitated through wizards to help people build games and sims. With a few critical questions, the agent could "fill-in" a generic structure to some extent...including capturing the causal chains of events (e.g. what happens first?, when that goes up what does it do to the second thing?).
I really like the clarity of the framework of "sim, game, pedagogy" crossed with "systems, cyclical, linear" and also the idea that sims allow-uses discovery/practice, games allows-uses testing/softening and pedagogy allows-uses presentation/support. The Mislevy (et al) assessment model has four parts: task model (a bit like the sim in that it is the model of everything that the user could be doing, sets the context and expectation), user model (a bit like the game in that it models in clear computational terms what the "winning" user will be doing), the evidence model and presentation layer (collects data, makes judgements about what the user knows, and selects the next item to present to the user). The presentation layer is a bit mechanical...so really the three essential parts of any assessment are the task, user and evidence models, which I think can be brought into a useful alignment with your framework - in order to go after that issue about metrics of effectiveness.
Another thing your model makes me think of is that on the content type side, cyclical contains linear and is contained by systems. e.g. systems models have both linear and cyclic causal relationships, simple cycles are first created by two linear relatinships that bounce back to each other...and curvilinear paths of many kinds are essentially linear at the microscopic level. So that leads me to wonder (and I think your chapters make this point) that pedagogy is contained in games (i.e. games teach) and are contained by sims (i.e. sims can be fun, have prefered goal states like "winning" or "succeeding", use scores, give feedback. etc.) These metaphors might break down on some issues, but they're giving me pause to reflect and relate to your framework.
Book Description
A Straightforward, No-Nonsense Guide to Building the Most Accurate, Complete, and Useful Data Models Possible. How do I know if my data model is accurate? When is a model really complete? Is it possible for a model to be both technically perfect and of no use to an organization, and what can I do to avoid that problem? This book provides answers to these and other crucial data modeling questions. While there are plenty of books that describe the characteristics of finished high-quality data models, only The Data Modeling Handbook gets down to the nitty-gritty of actually building one. Packed with real-world examples, annotated diagrams, and a wealth of rules and best practices, this field-tested guide provides experienced data modelers, architects, and engineers with hands-on guidance from two noted data management experts.
- The only book offering clear, straightforward rules and guidelines for judging model accuracy and completeness
- Presents all rules in several notations, including IDEF1X, Martin, Chen, and Finkelstein
- Compares and contrasts the most popular modeling styles and demonstrates how great models can be built using any type of notation
- Explains how to use an organization's plans, policies, objectives, and strategies to build accurate, complete, and useful models
- Offers detailed guidance to establishing a continuous quality evaluation program that's easy to implement and follow
- Packed with real-world examples and annotated diagrams illustrating each point covered
- Describes how to use Case tools most effectively to build high-quality models
Customer Reviews:
Poor choice for experienced modelers - just ok for beginners.......2004-05-14
This book oversimplifies the examples and expects a leap of faith to truly understand the information engineering technique of data modeling.
May be good in the class room; but in actual practice there are much better references available such as Silverston, Inmon, Kimball, and of course the Zachman framework.
Very academic in nature, more theory than reality.......2004-02-05
Anyone that has been modeling very long will see this book for what it is ... after you look at it once, you'll put it on your bookshelf and leave it there. Save yourself the money ... There are much better reference books available. Try David Hay's book on patterns, or Len Silverston, or Graeme Simsion. Check out the DAMA reference guide .. at least it's built by actual practitioners.
The help screens on the Data modeling tools are more advanced in explaining data modeling than this book.
Probably great for theorists - managers or teachers that don't know what they are doing! But the real modelers will seek help elsewhere.
Misleading or, if you want, wrong.......2003-09-26
The authors deny the fifth normal form and state special-case rules as if they were universal. Examples: Eliminate triads; Two entities cannot have more than one relationship. Although in some specific situations the advice might be valid, anyone who is trying to learn from the reading will be misled. Less harmful, even interesting, for a professor (to learn how not to approach the teaching of DB modeling).
Poor, underdocumented examples. Oversimplification. Unfortunately at the time I had only the title to choose from. Good thing most books now have a table of contents.
Database modeling still doesn't have strong references as database theory does (Date's, Ramakrishnan's, Elmasri's only to cite three). There are excellent theoretical (Thalheim's "Entity-Relationship Modeling" is good) and philosophical approaches (finally they re-published Kent's opera-prima "Data and Reality", fabulous).
The picture is poor when it comes to hands-on modeling. Bruce's "Designing Quality Databases..." is an exception. Good and useful for someone who is developing modeling expertise. But I especially don't recommend Reingruber&Gregory's book.
Very good one to start a good model.......2003-08-28
It is a very good book for a Data base designer and a data modeler. I strongly recommand this book to all database people.
I'd rather visit the dentist.......2003-03-25
This book is about as much fun to read as a book about differential equations. Good concepts, but the context is very dry and puts me to sleep. I've been in the industry for several years, and I bought this book as a reference. But I find myself cringing every time I need to use it.
Amazon.com
Recall the old saying about all work and no play making Jack a dull boy? World-class companies today need play--serious play--if they want to make truly innovative products, argues Michael Schrage, an MIT Media Lab fellow and Fortune magazine columnist. In Serious Play he writes, "When talented innovators innovate, you don't listen to the specs they quote. You look at the models they've created." Whether it's a spreadsheet that tests a new financial model or a foam prototype of a calculator, what interests Schrage is not the model itself, but the behavior that play--be it modeling, prototyping, or simulation--inspires.
Schrage examines the approaches to successful prototyping at companies such as AT&T, Boeing, Microsoft, and DaimlerChrysler and describes the kind of culture that's needed for encouraging innovation. In the last chapter, he lays out the 10 rules of serious play, including: Be willing to fail early and often; know when the costs outweigh the benefits; know who wins and who loses from an innovation; build a prototype that engages customers, vendors, and colleagues; create markets around prototypes; and simulate the customer experience. Well-written and inspiring, Serious Play, is a first-rate user's guide for managers, project leaders, and other innovators. --Dan Ring
Book Description
Serious Play is about serious work: how the world's leading companies model, prototype, and simulate to innovate. Increasingly, prototypes are the key platforms and models are the core media for managing risk and creating value. They allow for cost-effective creativity, encourage profitable improvisation, and inspire organizations to collaborate in unexpected ways.
Serious Play is a crisply written handbook for product, process and project leaders who are determined to manage their innovation initiatives successfully.
As digital technologies for modeling and simulation offer more value for less money, they provoke fundamental challenges to organizational culture and design. MIT research associate Michael Schrage asserts that conventional wisdom surrounding innovation gets turned inside out: What innovative companies choose not to model often proves more important than what they do. Contrary to the popular assumption that innovative teams generate innovative prototypes, in fact innovative prototypes generate innovative teams. How innovators play with their models and simulations invariably matters far more than what they actually plan. In fact, Schrage shows why innovative firms cannot seriously plan unless they seriously play.
Drawing upon a range of companies as diverse as Walt Disney, Boeing, Merrill Lynch, General Electric, IBM, IDEO, Microsoft, Royal Dutch Shell, DaimlerChrysler and American Airlines, Schrage identifies the common patterns and practices that distinguish productive prototyping cultures from pathological ones. He explores the intimate connection between how leading innovators model reality and how they actually manage it. He examines prototyping failures as rigorously as he explains prototyping successes.
The essential message of
Serious Play is that tomorrow's innovations will increasingly be the byproduct of how companies and their customers behave-and misbehave-around this new generation of models, prototypes, and simulations. The distinction between serious play and serious work dissolves as technology gives innovators ever-increasing opportunities to simulate and prototype their ideas. As the media for modeling radically change, so will the organizations that use them.
With real-world examples and engaging anecdotes, Schrage argues that the future of prototyping is the future of innovation. A User's Guide included in the book helps readers quickly take away the innovation practices profiled throughout. A landmark book by one of the most perceptive voices in the field of innovation,
Serious Play will lay serious claim to the hearts and minds of forward-looking business managers.
Download Description
Successful innovation demands more than a good strategic plan; it requires creative improvisation. Much of the "serious play" that leads to breakthrough innovations is increasingly linked to experiments with models, prototypes, and simulations. As digital technology makes prototyping more cost-effective, serious play will soon lie at the heart of all innovation strategies, influencing how businesses define themselves and their markets. Author Michael Schrage is one of today's most widely recognized experts on the relationship between technology and work. In Serious Play, Schrage argues that the real value in building models comes less from the help they offer with troubleshooting and problem solving than from the insights they reveal about the organization itself. Technological models can actually change us--improving the way we communicate, collaborate, learn, and innovate. With real-world examples and engaging anecdotes, Schrage shows how companies such as Disney, Microsoft, Boeing, IDEO, and DaimlerChrysler use serious play with modeling technologies to facilitate the collaborative interactions that lead to innovation. A user's guide included with the book helps readers apply many of the innovation practices profiled throughout. A landmark book by one of the most perceptive voices in the field of innovation.
Customer Reviews:
Readable User-Friendly Book on Innovation.......2005-04-30
I am enjoying this book. I like the title "Serious Play", but I dislike the sub-title "How the World's Best Companies Simulate to Innovate". Companies don't innovate people do is my thought. I think the author could have taken this concept one step further. That is tie in the concepts of how innovation relates to chaos theory and fractals and larger concepts. The author's ideas are not that new to me because I am a project manager in a software engineering environment where prototyping and iterations is the name of the game. We have at most 3 months to make a difference, to deliver and then we are swept into the ocean of change. You have a small window of opportunity before both the game and the players change.
I think that the world may be on the verge of moving so fast that we begin to see things like the wiki, open source culture in that it takes all of us innovating collectively in serious play. Long term I wonder if you are not free, workable and now, you are not in the game.
Some concepts for me are:
1) Importance of being able to improvise in the moment
2) Prototyping both reveals the underlying power cutural structures and changes them.
3) Human beings are relationship morphing entities.
4) the importance of shared collaboration space that invite clever interactions between people.
5) Treating prototypes as conversation pieces
6) Watch for the underlying feeling of geniune fun
7) The importance of the challenge or obstacles to the game
8) We shape our models, our models shape us
9) "In order to have actionable meaning, the fuzzy mental models ... must be externalized in representations in ways... that can be grasped"
10) Prototypes force individuals to confront the tyranny of tradeoffs (i.e. difficult decisions)
11) "All models are attempt to manage the complexity by making it simpler and more accessible"
While the text is very readable I had trouble pulling out the underlying structure of the book. But I felt redeemed when I read the User's Guide at the end of the book. Interesting you would think a User's Guide would go at the beginning. Fortunately I do not read sequentially so I found that chapter fairly quickly.
Three years on, still a great book.......2002-09-16
Here's the best review I can give Michael Schrage's "Serious Play": Three years on, it's consistently the first book I pull out of my bookshelf when I'm looking for ideas for presentations, thoughts on introducing new products or services, etc. His commentary on "mean-time-to-payback" is something that will stick with you for years. It's brilliant stuff, written in clear, concise terms. And, surprisingly, very little of it is dated. Unlike many books from that era, there's no .com or Enron fixation for the author to be embarrassed about. Schrage's examples are pulled from health care technology, animation, theater...in short, an eye-opening spectrum of ideas. I consider "Serious Play" one of my best purchases ever.
Preaching to the choir.......2002-08-22
This is a good book for someone to read if they are skeptical of the benefits of prototypes. However, since I already know the value of interactive prototypes I became quickly tired with the book.
Other critiques: it felt like the author had a bunch of cool little examples lying around and finally got the idea to put it together, surrounded by some fluffy text to make it thick enough to sell as a book, and put it on the market. Lots of space is taken up by these excerpts, as well as big text in the margins summing up "important points," which I would usually find useful but instead gave the impression of just taking up space.
Also, the author makes repeated use of similes to the point that it got annoying; "Just like a is to b, c is to d."
At one point, the author brings up the difference between a "simulation" and a "prototype," and just when you think the core of the matter is going to be distinguished the author backs out, leaving you wondering why they brought it up in the first place if they weren't going to take a stab at defining and differentiating them.
Sorry, but given the hype I was sorely disappointed. Read the first chapter or so in a bookstore before actually buying this.
Enlightening.......2002-07-11
This book gave me a very good and new insight of how to manage prototyping. It is enlightening for not only it explains and lists the topics that are important. It also gives us lots of practical examples of implementations.
I kept refering it, and i DON't usually do that.........2001-03-14
The most significant aspect of this book is that it provides a vocabulary and a language to discuss the nature of creative prototyping and modeling behaviors. The first thing you do is take off the cover, otherwise people think you're reading a really cheesy book. It's everything but that. It's been 4 weeks, and i'm on my 3rd time through it. I reference it and re-use it over and over. I've since recommended it to a genetic scientist friend of mine that works for a major drug company, a software engineer, and a broadcast designer. The thinking in this book has an epidemic effect with those that read it, and the excitement that it carries into their work and mine is the most influential and direct I have ever experienced. Some books are relevant once, but this will be accessed for years to come. This is my first book recommendation i have ever made. that is all...
Book Description
This fourth edition of Simulation with Arena has the same goal as the first three editions: to provide a comprehensive treatment of simulation concepts in general and the Arena simulation software in particular. It starts by having the reader develop simple, well-animated, high-level models, and then progresses to advanced modeling and analysis. Statistical design and analysis of simulation experiments is integrated with the modeling chapters, reflecting the joint nature of these activities in good simulation studies. The objective is to help the reader carry out effective simulation modeling, analysis, and projects using the Arena simulation system. An informal, tutorial writing style is used to aid the beginner in fully understanding the ideas and topics presented. Included is a CD containing the current version of the Arena academic software and the examples referenced throughout the text.
Starting with an introduction to simulation concepts, the book progresses through an overview of the Arena software, basic model development, input analysis, additional modeling constructs, output analysis, and advanced modeling. It also includes chapters on integrating Arena simulation models with other applications, specialized statistical issues, continuous simulation, and conducting a successful simulation study. It is intended primarily to be a text in a first course on simulation or for self-study. However, the later chapters could be incorporated into an advanced or graduate-level course.
Building on the success of the first three editions, published in 1998, 2002, and 2004, this edition retains the basic outline and tutorial style, built around a sequence of successively more complicated examples. All the examples and discussion, however, have been modified and updated to be consistent with the current version of the Arena software, and additional examples have been developed, along with more exercises. As before, a password-protected website for instructors provides support in terms of downloadable lecture slides and solutions to end-of-chapter exercises.
The book draws heavily on the experience and expertise of the authors, a professor at the University of Cincinnati specializing in simulation, and two seasoned members of Rockwell Software (formerly Systems Modeling), the developers of Arena, who are active in product design and development, training, consulting, and applications.
Customer Reviews:
A bit too messy.......2007-02-12
This book has been co-authored by a university professor and two Rockwell people. It neither serves its purpose as a "theory" book nor an "applied" book.
It leads you through the process of creating a simulation by using examples.
I would have preferred this to be more of a reference book answering questions such as "If I want to do this what modules should I use?". Instead, when faced with a minor question (e.g. how to count exiting entities with different attributes?) I end up reading half the book and still not find a suitable answer.
The occasionnal jokes are quite funny though!
Book Description
"Mr. Salov has taken one of my favorite creations – Perfect Profit – and provided an expanded description of his interpretation of it and put it in your hands with the included software. Like I said fifteen years ago, Perfect Profit is an important tool for the trading system developer. See for yourself."
—Robert Pardo, President, Pardo Capital Limited
"A very in-depth reference for programmers that should serve well into the future. The code herein lends itself well to other syntactically similar programming languages such as Java, PHP, and C#."
—Ralph Vince
The goal of trading is to make money, and for many, profits are the best way to measure that success. Author Valerii Salov knows how to calculate potential profit, and in Modeling Maximum Trading Profits with C++, he outlines an original and thought-provoking approach to trading that will help you do the same.
This detailed guide will show you how to effectively calculate the potential profit in a market under conditions of variable transaction costs, and provide you with the tools needed to compute those values from real prices. You'll be introduced to new notions of s-function, s-matrix, s-interval, and polarities of s-intervals, and discover how they can be used to build the r- and l-algorithms as well as the first and second profit and loss reserve algorithms. Optimal money management techniques are also illustrated throughout the book, so you can make the most informed trading decisions possible.
Filled with in-depth insight and expert advice, Modeling Maximum Trading Profits with C++ contains a comprehensive overview of trading, money management, and C++. A companion CD-ROM is also included to help you test the concepts described throughout the book before you attempt to use them in real-world situations.
Customer Reviews:
should have been a short journal article.......2007-06-29
SUMMARY: A potentially useful concept taken to ridiculous extremes.
The main theme is around the concept of *potential profit* offered by a particular market. When building automated trading strategies or evaluating human trader performance, the problem could be decomposed into a product of some intrinsic profit offered by the market and the percentage of that profit that is captured by a particular trader or strategy. This book spends most of its attention on the former factor and various derived performance metrics.
*Potential profit* is defined by an idealized strategy that has *perfect foresight about all future prices over a given time interval*. In addition to the original concept apparently suggested by Robert Pardo, the book's definition is made more realistic by constraining such a strategy with non-zero transaction costs. Although this connection is not made by the author, the concept is related to those used in offline algorithms and competitive analysis (see, for example, Online Computation and Competitive Analysis): in essence, you want to quantify the amount of *regret* you experience comparing your performance to that of a perfect adversary or algorithm that is allowed to solve the offline version of the same problem (with all of the future data available at the outset).
Three iterations of potential profit algorithms are introduced:
1. "r-/l-algorithms": position size is constrained with a given maximum. The perfect strategy can be proven to be pure reversal -- except for initial and final transactions, the maximum profit is obtained by always switching positions between +max_size and -max_size at certain transaction points. Although the underlying problem could be solved using a generic optimizer, Salov introduces a concept of *s-intervals* that makes it easy to see how the global maximum can be computed with a simple linear algorithm. This algorithm offers conceptual elegance of solving its related problem exactly -- the later two are heuristic improvements for less constrained versions of the problem.
2. "first P&L reserve algorithm": strategy remains a pure reversal strategy but position size is allowed to vary subject only to self-financing/account margin/buying power constraints. #2 can improve on #1 due to increases in account buying power after the initial entry/exit transactions.
3. "second P&L reserve algorithm": same as #2 but the strategy is allowed to change existing positions in between the transaction points used by #1 and #2, i.e. the strategy is no longer pure reversal. Again, #3 can improve on #1 due to increases in account buying power during trading.
Since both #2 and #3 consider how account equity grows over time subject to self-financing restrictions, connections to Kelly/Shannon
maximum growth rate formulas arise naturally. In later chapters, all algorithms are used to derive performance metrics and to compare potential profits offered by various markets using real-life price data.
Unfortunately, in my view the author should have stopped at #1 and not gone on for 180 more pages. Granted, the overall approach of comparing your actual performance to that of some idealized benchmark strategy is extremely sound and useful. As a benchmark, a single simple idealized strategy is sufficient. But the author does not emphasize enough that the single biggest advantage the idealized strategy has is the perfect knowledge of future prices. Algorithm #1 already has this advantage built in and there seems to be little practical value in gleaning further incremental benefits by adding optimal account growth heuristics. (Optimizing position sizes can't be done in real-life without simultaneously controlling risk etc.) In fact, the last chapter has a cocoa contract example making 13000% returns in just 5 days! Similarly, in some examples algorithms #2 and #3 manage to grow exponentially into such large position sizes that they overflow a 32-bit integer -- it is surprising that the author does not see the ridiculousness of that and reluctantly suggests that the algorithms should be applied to "short time intervals" or "with high transaction costs".
Other book shortcomings that seemed glaring to me:
- only deterministic strategies are considered. Real-life strategies have to incorporate uncertainty modeling in their decisioning. Furthermore, deterministic-only strategies can't reach Nash equilibria for some problems.
- only two commission cost models are considered: fixed per transaction and cost as a function of instrument price. Something like cost/share would invalidate much of the discussion.
- because they have perfect price foresight all idealized algorithms unavoidably go wild on max'ing out position sizes. In real life, risk management constraints on open positions can kick in sooner than margin constraints, unless you are diversified across many positions (situation not considered in the book).
- after observing how much the transaction costs can impact these idealized strategies, the author nonetheless goes on and makes very ballpark guesses about slippage etc -- it seems incongruent after all that energy spent on perfecting those strategies.
15 years is not enough: a new market property.......2007-02-25
I am a professional mathematician with a personal interest in mathematical finance and I know the author. I did not expect Dr. Salov to be writing a book but eventually I became one of the first readers. The book focuses on modeling and calculation of the potential profit - a new and fascinating market property. It also contains a gentle introduction explaining basic trading, financial and programming terms and helping better to understand the main topic. Therefore, the book should be interesting for all market participants: trading system developer, trader, theoretician working on finance or someone who wishes to learn the field of trading systems and quantitative finance.
It is interesting that the potential profit, as introduced by Robert Pardo, corresponds to a classical notion of a total variation of a function, the function being the time sequence of prices of a commodity. Computation of the potential profit in the presence of e.g. transaction costs becomes a sophisticated mathematical problem which Dr. Salov solves using the newly suggested r- and l-algorithms. In a systematic way, the author introduces s-function, s-matrix, polarity, s-intervals and proves their properties, producing an effective r- and l-algorithms.
While Robert Pardo introduced potential profit as a new concept, Valerii Salov brings this concept to a substantially higher level. He considers the maximum profit as a market property, which must be combined with a sequence of trading actions - trading strategy. He systematically comes the way from simple market and trading systems performance measures to a powerful and automatic tool filtering the most critical price events. This becomes possible because he takes into account transaction costs such as commissions, slippage, and others. A motivation for each decision leading to the complete software, new algorithms, or money management is carefully explained.
I highly recommend reading this book for anyone interested in development of trading systems and who wants to understand better the work of markets.
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