Mining Your Own Business: A Primer For Executives On Understanding And Employing Data Mining And Predictive Analytics

 Mining Your Own Business: A Primer for Executives on Understanding and Employing Data Mining and Predictive Analytics Text fb2 book

In this practical guide for organizational leaders and top-level executives, industry experts Jeff Deal and Gerhard Pilcher explain in clear, understandable English…What data mining and predictive analytics are,Why they are such powerful management tools,How and when to use them for greatest positive impact across a broad spectrum of industries.Complete with solid advice and instructive case histo...

Paperback: 184 pages
Publisher: Data Science Publishing (September 19, 2016)
Language: English
ISBN-10: 9780996712101
ISBN-13: 978-0996712101
ASIN: 0996712100
Product Dimensions: 6 x 0.4 x 9 inches
Amazon Rank: 388607
Format: PDF ePub fb2 djvu book

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For predictive analytics to work, two different "species" must cooperate in harmony: the business leader and the quant. In order to function together, they each have to adapt. On the one hand, the quant needs to attain a business-oriented vantage. An...



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monstrates how to harness the power of data mining and predictive analytics, while avoiding costly mistakes. Use it to gain a quick overview of the subject and as a handy resource to be referred to again and again.If you re preparing to lead or participate in a data analytics initiative, this is the one book you must read!Receiving early, strong praise from business government leaders who are using these powerful management tools to achieve dramatic goals for projects and their organizations.CONTENTSIntroduction and Overview1.Empowering the Decision MakersHunting for Needles in HaystacksBreaking the Mind BarrierA World of Applications2.Clearing Up the ConfusionTen Levels of AnalyticsFour Categories of Modeling KnowledgeSupervised vs. Unsupervised LearningLevels and Advanced Data TypesThe Analytic Organization3.Leading a Data Analytics InitiativeStarting SmallExamples of Poor vs. Good FocusCultivating the CultureManaging a Data Analytics InitiativeThe Experiences of a Mobile Phone Service ProviderLeadership is KeyA Parade of Champions at a Federal AgencyA Lack of Leadership at a Financial FirmThe Effect of Different Leadership Styles at aGovernment AgencyBold Leadership Required4.Staffing a Data Analytics ProjectIndividual or Team?Assembling the TeamWhat is a Data Scientist?More than Academic CredentialsThe Most Important QualityMike Thurber s StoryBuilding Teams through Gap Analysis5.Acquiring the Right ToolsA Variety of Techniques and DisciplinesInterface Level of ToolsSources of ToolsA Word about Open-Source Tools Tool Trends6.Hiring Data Analytics ConsultantsDiscerning Fact from HypeEvaluating Industry ExperienceEvaluating Analytics ExperienceFinding the Right ConsultantThe Modeling Process7.Understanding the Data Mining ProcessThe CRISP-DM ProcessResist the Temptation to Take Shortcuts8.Understanding the BusinessClarifying Your ObjectiveDefining the TerminologyFraming the QuestionsAn Unexpected Finding9.Understanding and Preparing the DataUnderstanding the DataCleaning the DataPerfect DataCollecting and Preparing the DataFostering CooperationGoverning the Data10.Building the ModelInside the Black BoxBuilding an Illustrative ModelNon-Linear ModelsChoosing a ModelResponse Surfaces of Predictive ModelsThe Trade-off between Accuracy and InterpretabilityChoosing and Testing Modeling AlgorithmsDealing with VarianceModel Ensembles11.Validating the ModelTechnical ValidationChecking for MistakesChecking for GeneralizationUsing Experts to Qualify Model ResultsTarget ShufflingBusiness ValidationPutting the Model into Practice12.Deploying the ModelPlanning & Budgeting for DeploymentBusiness Processes Are KeyExample: FindingTaxpayer FraudFour Important Questions13.Realizing the TransfoTransformationRealizing the PotentialThe Tipping PointAppendix