BUSINESS MODELING AND DATA MINING BY DORIAN PYLE PDF

: Business Modeling and Data Mining (The Morgan Kaufmann Series in Data Management Systems): Dorian Pyle. Business Modeling and Data Mining demonstrates how real world business problems can be formulated so that data mining can answer them. The concepts . Download Citation on ResearchGate | On Jan 1, , Dorian Pyle and others published Business modeling and data mining }.

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This book provides practical guidance on how to identify and structure real-world business questions in terms that can be answered by quantitative models and data mining. Business Modeling and Data Mining demonstrates how real world business problems can be formulated so that data mining can answer them. The concepts and techniques presented in this book are the essential building blocks in understanding what models are and how they can be used practically to reveal hidden assumptions and needs, determine problems, discover data, determine costs, and explore the whole domain of the problem.

This book articulately explains how to understand both the strategic and tactical aspects of any business problem, identify where the key leverage points are and determine where quantitative techniques of analysis — such as data mining – can yield most benefit. It addresses techniques for discovering how to turn colloquial expression and vague descriptions of a business problem first into qualitative models and then into well-defined quantitative models using data mining that can then be used to find a solution.

The book completes the process by illustrating how these findings from data mining can be turned into strategic or tactical implementations.

Business Modeling and Data Mining

Would you like to tell us about a lower price? If you are a seller for this product, would you like to suggest updates through seller support? This book articulately explains how to understand both the strategic and tactical aspects of any business problem, identify where the key leverage points are and determine where quantitative techniques of analysis — such as data mining — can yield most benefit. Read more Read less.

Discover Prime Book Box for Kids. Customers who viewed this item also viewed. Page 1 of 1 Start over Page 1 of 1. Data Science for Business: Customers who bought this item also bought. Book Description This book provides practical guidance on how to identify and structure real-world business questions in terms that can be answered by quantitative models and data mining.

Morgan Kaufmann; 1 edition May 20, Language: Try the Kindle edition and experience these great reading features: Share your thoughts with other customers. Write a customer review. Showing of 5 reviews. Top Reviews Most recent Top Reviews. There was a problem filtering reviews right now. Please try again later. A must have for any data miner that takes his profession seriously.

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Business modeling and data mining are carefully separated, as they should be. This crucial distinction has greatly enlightened my view on business problems. First discover the framework for the business problem, determine the leverage point, and then build and refine the best possible model. All steps are described in practical detail, making the book extremely actionable, and tool independent.

First, how to determine the appropriate problem to analyze? Then, what are the right data, and how do I get them? Only then does the data mining begin, and a groundbreaking, comprehensive methodology is put forward to come up with the best possible model in every circumstance.

The business modeling and data mining methodologies explicate at every possible step in the process – what to do, and how to proceed. In addition, a lot of supporting material provides insight on topics like working with conditional probabilities, regression to the mean, visualizing model performance and errors in problem space, etc.

Pyle’s previous book set the mark with regards to data preparation. This book is much broader in its scope and should actually be read before the previous one. It’s pretty hefty, but more than worth the read. The translation of the business problem into a Data Mining problem is the key for successful data mining projects.

Mr Pyle’s book deals with this subject in a remarkable way. The book is organized in four parts. The first part provides an introductory material. It shows a broad view of the modelling and mining. This part allowed me to grasp the key concepts, connect them among themselves and have a “map of the territory” as Mr.

The second part shows many techniques for dealing with business situations and how to translate them into a data mining problem. Many of these topics were new for me and I was able to learn and apply a lot of these powerful methodology. Part 3 is mainly about the data mining algorithms, different approach to solve data mining problems and how to improve the results. Although I knew about this subject, many topics are discussed in a very interesting point of view. Finally, the part 4 provides a full interactive methodology which summarizes the previous parts.

I have found this part very helpful in my work as business modeling consultant. Summarizing, I think that this book is excellent and it would be read by anyone who wants to apply data analysis to the real world. Business Modelling and Data Mining is an extremely clear and didactic work that explains and exemplifies business-oriented data analysis. Its structure goes from general to particular, from theory to practice. It is a work about concepts and its applications.

In the so complex, uncertain and fast world of today, those is charge of making decisions in business need to discover which useful information is contained in their data bases to be able to take the necessary measures tending to achieve competitive advantages.

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This work explains how to be successful in that direction, integrating qualitative and quantitative analysis of concepts. Pyle’s added value is linking data mining to business. The reader with a previous knowledge of data mining will be able to understand its useful application in the world of business. The one already familiar with business will learn about new technologies to improve tactic and strategic decision-making.

It is evident from my words that I do not agree with Alphonse LaTuune’s vision, who I think has misinterpreted this book’s purpose. Whereas detailed explanations on how to work with data mining algorithms are not necessary, it is important to highlight how to add value to decisions in business.

The latter is, definitely, Business Intelligence. Whether you want to initiate learning, or deepen your doorian of the subject, do not hesitate to read this book.

Business modeling and data mining / Dorian Pyle. – Version details – Trove

You will not regret it. Modsling selected Pyle’s book, sight unseen, as an introduction for undergraduate students in an information science curriculum. A third the way through the course students are beginning to ask “where’s the beef?

Even a business reader in search of an overview of the topic will likely find this discussion weighted with waffling wordiness. The author devotes page after page to talking about models and mining in a style that is somehow both wordy and imprecise.

I recommend the next edition edit the first pages or so down to 30, and devote the word-count more to real life examples, specific mathematical explanations, and practical exercises. See all 5 reviews. Amazon Giveaway allows you to run promotional giveaways in order to create buzz, reward your audience, and attract new followers and customers.

Business Modeling and Data Mining by Pyle, Dorian

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