Heuristics in Analytics presents an approach to analysis that accounts for the randomness of business and the competitive marketplace, creating a model that more accurately reflects the scenario at hand. With an emphasis on the importance of proper analytical tools, the book describes the analytical process from exploratory analysis through model developments, to deployments and possible outcomes. Beginning with an introduction to heuristic concepts, readers will find heuristics applied to statistics and probability, mathematics, stochastic, and artificial intelligence models, ending with the knowledge applications that solve business problems. Case studies illustrate the everyday application and implication of the techniques presented, while the heuristic approach is integrated into analytical modeling, graph analysis, text analytics, and more.
Robust analytics has become crucial in the corporate environment, and randomness plays an enormous role in business and the competitive marketplace. Failing to account for randomness can steer a model in an entirely wrong direction, negatively affecting the final outcome and potentially devastating the bottom line. Heuristics in Analytics describes how the heuristic characteristics of analysis can be overcome with problem design, math and statistics, helping readers to:
Every single factor, no matter how large or how small, must be taken into account when modeling a scenario or event—even the unknowns. The presence or absence of even a single detail can dramatically alter eventual outcomes. From raw data to final report, Heuristics in Analytics contains the information analysts need to improve accuracy, and ultimately, predictive, and descriptive power.
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Heuristics in Analytics
A Practical Perspective of What Influences Our AnalyticalWorld
In Heuristics in Analytics, renowned telecommunicationsexperts Carlos Andre Reis Pinheiro and Fiona McNeill describeanalytic processes and how they fit into the heuristic world aroundus. In spite of the strong heuristic characteristics of theanalytical processes, Heuristics in Analytics emphasizes theneed to have the proper tools to engage analytics and shows how toovercome heuristic characteristics through the use of mathematicsand statistics.
This straightforward book explores how important it is toproperly consider the randomness and the heuristic characteristicsin analytics and how crucial analytics are for companies andcorporate environments. Drawing from the authors’ years ofexperience, Heuristics in Analytics looks at:
Packed with case studies on the entire analytical process usingtelecom and insurance companies based in Brazil and Ireland,Heuristics in Analytics provides CFOs, chief marketingofficers, directors of marketing, and business managers with aninsider guide to deploying mathematical and statistical models whenperforming analytics.
In Heuristics in Analytics, renowned telecommunications experts Carlos Andre Reis Pinheiro and Fiona McNeill describe analytic processes and how they fit into the heuristic world around us. In spite of the strong heuristic characteristics of the analytical processes, Heuristics in Analytics emphasizes the need to have the proper tools to engage analytics and shows how to overcome heuristic characteristics through the use of mathematics and statistics.
This straightforward book explores how important it is to properly consider the randomness and the heuristic characteristics in analytics and how crucial analytics are for companies and corporate environments. Drawing from the authors' years of experience, Heuristics in Analytics looks at:
Packed with case studies on the entire analytical process using telecom and insurance companies based in Brazil and Ireland, Heuristics in Analytics provides CFOs, chief marketing officers, directors of marketing, and business managers with an insider guide to deploying mathematical and statistical models when performing analytics.
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Book Description Condition: New. Employ heuristic adjustments for truly accurate analysis Heuristics in Analytics presents an approach to analysis that accounts for the randomness of business and the competitive marketplace, creating a model that more accurately reflects the scenario at hand. Series: Wiley and SAS Business Series. Num Pages: 256 pages, black & white tables, figures. BIC Classification: KJQ. Category: (P) Professional & Vocational. Dimension: 173 x 228 x 23. Weight in Grams: 436. . 2014. 1st Edition. Hardcover. . . . . Seller Inventory # V9781118347607
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