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 histories, it demonstrates 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 Makers Hunting for Needles in Haystacks Breaking the Mind Barrier A World of Applications2.Clearing Up the Confusion Ten Levels of Analytics Four Categories of Modeling Knowledge Supervised vs. Unsupervised Learning Levels and Advanced Data TypesThe Analytic Organization3.Leading a Data Analytics Initiative Starting Small Examples of Poor vs. Good Focus Cultivating the Culture Managing a Data Analytics Initiative The Experiences of a Mobile Phone Service Provider Leadership is Key A Parade of Champions at a Federal Agency A Lack of Leadership at a Financial Firm The Effect of Different Leadership Styles at aGovernment Agency Bold Leadership Required4.Staffing a Data Analytics Project Individual or Team? Assembling the Team What is a Data Scientist? More than Academic Credentials The Most Important Quality Mike Thurber s Story Building Teams through Gap Analysis 5.Acquiring the Right Tools A Variety of Techniques and Disciplines Interface Level of Tools Sources of Tools A Word about Open-Source Tools Tool Trends6.Hiring Data Analytics Consultants Discerning Fact from Hype Evaluating Industry Experience Evaluating Analytics Experience Finding the Right ConsultantThe Modeling Process7.Understanding the Data Mining Process The CRISP-DM Process Resist the Temptation to Take Shortcuts8.Understanding the Business Clarifying Your Objective Defining the Terminology Framing the Questions An Unexpected Finding9.Understanding and Preparing the Data Understanding the Data Cleaning the Data Perfect Data Collecting and Preparing the Data Fostering Cooperation Governing the Data10.Building the Model Inside the Black Box Building an Illustrative Model Non-Linear Models Choosing a Model Response Surfaces of Predictive Models The Trade-off between Accuracy and Interpretability Choosing and Testing Modeling Algorithms Dealing with Variance Model Ensembles11.Validating the Model Technical Validation Checking for Mistakes Checking for Generalization Using Experts to Qualify Model Results Target Shuffling Business ValidationPutting the Model into Practice12.Deploying the Model Planning & Budgeting for Deployment Business Processes Are Key Example: FindingTaxpayer Fraud Four Important Questions13.Realizing the TransfoTransformation Realizing the Potential The Tipping PointAppendix

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