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Applied predictive analytics : principles and techniques for the professional data analyst / / Dean Abbott
Applied predictive analytics : principles and techniques for the professional data analyst / / Dean Abbott
Autore Abbott Dean
Pubbl/distr/stampa Indianapolis, Indiana : , : John Wiley & Sons, , 2014
Descrizione fisica 1 online resource (453 p.)
Disciplina 006.312
Soggetto topico Business - Data processing
Business planning - Data processing
Business - Computer programs
Soggetto genere / forma Electronic books.
ISBN 1-118-72769-X
1-118-72793-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Title Page; Copyright; Contents; Chapter 1 Overview of Predictive Analytics; What Is Analytics?; What Is Predictive Analytics?; Supervised vs. Unsupervised Learning; Parametric vs. Non-Parametric Models; Business Intelligence; Predictive Analytics vs. Business Intelligence; Do Predictive Models Just State the Obvious?; Similarities between Business Intelligence and Predictive Analytics; Predictive Analytics vs. Statistics; Statistics and Analytics; Predictive Analytics and Statistics Contrasted; Predictive Analytics vs. Data Mining; Who Uses Predictive Analytics?
Challenges in Using Predictive AnalyticsObstacles in Management; Obstacles with Data; Obstacles with Modeling; Obstacles in Deployment; What Educational Background Is Needed to Become a Predictive Modeler?; Chapter 2 Setting Up the Problem; Predictive Analytics Processing Steps: CRISP-DM; Business Understanding; The Three-Legged Stool; Business Objectives; Defining Data for Predictive Modeling; Defining the Columns as Measures; Defining the Unit of Analysis; Which Unit of Analysis?; Defining the Target Variable; Temporal Considerations for Target Variable
Defining Measures of Success for Predictive ModelsSuccess Criteria for Classification; Success Criteria for Estimation; Other Customized Success Criteria; Doing Predictive Modeling Out of Order; Building Models First; Early Model Deployment; Case Study: Recovering Lapsed Donors; Overview; Business Objectives; Data for the Competition; The Target Variables; Modeling Objectives; Model Selection and Evaluation Criteria; Model Deployment; Case Study: Fraud Detection; Overview; Business Objectives; Data for the Project; The Target Variables; Modeling Objectives
Model Selection and Evaluation CriteriaModel Deployment; Summary; Chapter 3 Data Understanding; What the Data Looks Like; Single Variable Summaries; Mean; Standard Deviation; The Normal Distribution; Uniform Distribution; Applying Simple Statistics in Data Understanding; Skewness; Kurtosis; Rank-Ordered Statistics; Categorical Variable Assessment; Data Visualization in One Dimension; Histograms; Multiple Variable Summaries; Hidden Value in Variable Interactions: Simpson's Paradox; The Combinatorial Explosion of Interactions; Correlations; Spurious Correlations; Back to Correlations; Crosstabs
Data Visualization, Two or Higher DimensionsScatterplots; Anscombe's Quartet; Scatterplot Matrices; Overlaying the Target Variable in Summary; Scatterplots in More Than Two Dimensions; The Value of Statistical Significance; Pulling It All Together into a Data Audit; Summary; Chapter 4 Data Preparation; Variable Cleaning; Incorrect Values; Consistency in Data Formats; Outliers; Multidimensional Outliers; Missing Values; Fixing Missing Data; Feature Creation; Simple Variable Transformations; Fixing Skew; Binning Continuous Variables; Numeric Variable Scaling; Nominal Variable Transformation
Ordinal Variable Transformations
Record Nr. UNINA-9910453816403321
Abbott Dean  
Indianapolis, Indiana : , : John Wiley & Sons, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Applied predictive analytics : principles and techniques for the professional data analyst / / Dean Abbott
Applied predictive analytics : principles and techniques for the professional data analyst / / Dean Abbott
Autore Abbott Dean
Pubbl/distr/stampa Indianapolis, Indiana : , : John Wiley & Sons, , 2014
Descrizione fisica 1 online resource (453 p.)
Disciplina 006.312
Soggetto topico Business - Data processing
Business planning - Data processing
Business - Computer programs
ISBN 1-118-72769-X
1-118-72793-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Title Page; Copyright; Contents; Chapter 1 Overview of Predictive Analytics; What Is Analytics?; What Is Predictive Analytics?; Supervised vs. Unsupervised Learning; Parametric vs. Non-Parametric Models; Business Intelligence; Predictive Analytics vs. Business Intelligence; Do Predictive Models Just State the Obvious?; Similarities between Business Intelligence and Predictive Analytics; Predictive Analytics vs. Statistics; Statistics and Analytics; Predictive Analytics and Statistics Contrasted; Predictive Analytics vs. Data Mining; Who Uses Predictive Analytics?
Challenges in Using Predictive AnalyticsObstacles in Management; Obstacles with Data; Obstacles with Modeling; Obstacles in Deployment; What Educational Background Is Needed to Become a Predictive Modeler?; Chapter 2 Setting Up the Problem; Predictive Analytics Processing Steps: CRISP-DM; Business Understanding; The Three-Legged Stool; Business Objectives; Defining Data for Predictive Modeling; Defining the Columns as Measures; Defining the Unit of Analysis; Which Unit of Analysis?; Defining the Target Variable; Temporal Considerations for Target Variable
Defining Measures of Success for Predictive ModelsSuccess Criteria for Classification; Success Criteria for Estimation; Other Customized Success Criteria; Doing Predictive Modeling Out of Order; Building Models First; Early Model Deployment; Case Study: Recovering Lapsed Donors; Overview; Business Objectives; Data for the Competition; The Target Variables; Modeling Objectives; Model Selection and Evaluation Criteria; Model Deployment; Case Study: Fraud Detection; Overview; Business Objectives; Data for the Project; The Target Variables; Modeling Objectives
Model Selection and Evaluation CriteriaModel Deployment; Summary; Chapter 3 Data Understanding; What the Data Looks Like; Single Variable Summaries; Mean; Standard Deviation; The Normal Distribution; Uniform Distribution; Applying Simple Statistics in Data Understanding; Skewness; Kurtosis; Rank-Ordered Statistics; Categorical Variable Assessment; Data Visualization in One Dimension; Histograms; Multiple Variable Summaries; Hidden Value in Variable Interactions: Simpson's Paradox; The Combinatorial Explosion of Interactions; Correlations; Spurious Correlations; Back to Correlations; Crosstabs
Data Visualization, Two or Higher DimensionsScatterplots; Anscombe's Quartet; Scatterplot Matrices; Overlaying the Target Variable in Summary; Scatterplots in More Than Two Dimensions; The Value of Statistical Significance; Pulling It All Together into a Data Audit; Summary; Chapter 4 Data Preparation; Variable Cleaning; Incorrect Values; Consistency in Data Formats; Outliers; Multidimensional Outliers; Missing Values; Fixing Missing Data; Feature Creation; Simple Variable Transformations; Fixing Skew; Binning Continuous Variables; Numeric Variable Scaling; Nominal Variable Transformation
Ordinal Variable Transformations
Record Nr. UNINA-9910790941503321
Abbott Dean  
Indianapolis, Indiana : , : John Wiley & Sons, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Applied predictive analytics : principles and techniques for the professional data analyst / / Dean Abbott
Applied predictive analytics : principles and techniques for the professional data analyst / / Dean Abbott
Autore Abbott Dean
Pubbl/distr/stampa Indianapolis, Indiana : , : John Wiley & Sons, , 2014
Descrizione fisica 1 online resource (453 p.)
Disciplina 006.312
Soggetto topico Business - Data processing
Business planning - Data processing
Business - Computer programs
ISBN 1-118-72769-X
1-118-72793-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Title Page; Copyright; Contents; Chapter 1 Overview of Predictive Analytics; What Is Analytics?; What Is Predictive Analytics?; Supervised vs. Unsupervised Learning; Parametric vs. Non-Parametric Models; Business Intelligence; Predictive Analytics vs. Business Intelligence; Do Predictive Models Just State the Obvious?; Similarities between Business Intelligence and Predictive Analytics; Predictive Analytics vs. Statistics; Statistics and Analytics; Predictive Analytics and Statistics Contrasted; Predictive Analytics vs. Data Mining; Who Uses Predictive Analytics?
Challenges in Using Predictive AnalyticsObstacles in Management; Obstacles with Data; Obstacles with Modeling; Obstacles in Deployment; What Educational Background Is Needed to Become a Predictive Modeler?; Chapter 2 Setting Up the Problem; Predictive Analytics Processing Steps: CRISP-DM; Business Understanding; The Three-Legged Stool; Business Objectives; Defining Data for Predictive Modeling; Defining the Columns as Measures; Defining the Unit of Analysis; Which Unit of Analysis?; Defining the Target Variable; Temporal Considerations for Target Variable
Defining Measures of Success for Predictive ModelsSuccess Criteria for Classification; Success Criteria for Estimation; Other Customized Success Criteria; Doing Predictive Modeling Out of Order; Building Models First; Early Model Deployment; Case Study: Recovering Lapsed Donors; Overview; Business Objectives; Data for the Competition; The Target Variables; Modeling Objectives; Model Selection and Evaluation Criteria; Model Deployment; Case Study: Fraud Detection; Overview; Business Objectives; Data for the Project; The Target Variables; Modeling Objectives
Model Selection and Evaluation CriteriaModel Deployment; Summary; Chapter 3 Data Understanding; What the Data Looks Like; Single Variable Summaries; Mean; Standard Deviation; The Normal Distribution; Uniform Distribution; Applying Simple Statistics in Data Understanding; Skewness; Kurtosis; Rank-Ordered Statistics; Categorical Variable Assessment; Data Visualization in One Dimension; Histograms; Multiple Variable Summaries; Hidden Value in Variable Interactions: Simpson's Paradox; The Combinatorial Explosion of Interactions; Correlations; Spurious Correlations; Back to Correlations; Crosstabs
Data Visualization, Two or Higher DimensionsScatterplots; Anscombe's Quartet; Scatterplot Matrices; Overlaying the Target Variable in Summary; Scatterplots in More Than Two Dimensions; The Value of Statistical Significance; Pulling It All Together into a Data Audit; Summary; Chapter 4 Data Preparation; Variable Cleaning; Incorrect Values; Consistency in Data Formats; Outliers; Multidimensional Outliers; Missing Values; Fixing Missing Data; Feature Creation; Simple Variable Transformations; Fixing Skew; Binning Continuous Variables; Numeric Variable Scaling; Nominal Variable Transformation
Ordinal Variable Transformations
Record Nr. UNINA-9910812118003321
Abbott Dean  
Indianapolis, Indiana : , : John Wiley & Sons, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Defining enterprise data and analytics strategy : pragmatic guidance on defining strategy based on successful digital transformation experience of multiple Fortune 500 and other global companies / / Prakash Sah
Defining enterprise data and analytics strategy : pragmatic guidance on defining strategy based on successful digital transformation experience of multiple Fortune 500 and other global companies / / Prakash Sah
Autore Sah Prakash
Pubbl/distr/stampa Singapore : , : Springer, , [2022]
Descrizione fisica 1 online resource (186 pages)
Disciplina 658.4012
Collana Management for Professionals
Soggetto topico Business planning - Data processing
Quantitative research
Planificació empresarial
Gestió del coneixement
Processament de dades
Investigació quantitativa
Soggetto genere / forma Llibres electrònics
ISBN 9789811957192
9789811957185
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996499871703316
Sah Prakash  
Singapore : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Mastering business intelligence with MicroStrategy : build world-class enterprise business intelligence solutions with MicroStrategy 10 / / Dmitry Anoshin, Himani Rana, Ning Ma
Mastering business intelligence with MicroStrategy : build world-class enterprise business intelligence solutions with MicroStrategy 10 / / Dmitry Anoshin, Himani Rana, Ning Ma
Autore Anoshin Dmitry
Edizione [1st edition]
Pubbl/distr/stampa Birmingham : , : Packt Publishing, , 2016
Descrizione fisica 1 online resource (389 pages) : color illustrations
Collana Professional expertise distilled
Soggetto topico Business planning - Data processing
Database management
Soggetto genere / forma Electronic books.
ISBN 1-78588-626-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910511505303321
Anoshin Dmitry  
Birmingham : , : Packt Publishing, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Mastering business intelligence with MicroStrategy : build world-class enterprise business intelligence solutions with MicroStrategy 10 / / Dmitry Anoshin, Himani Rana, Ning Ma
Mastering business intelligence with MicroStrategy : build world-class enterprise business intelligence solutions with MicroStrategy 10 / / Dmitry Anoshin, Himani Rana, Ning Ma
Autore Anoshin Dmitry
Edizione [1st edition]
Pubbl/distr/stampa Birmingham : , : Packt Publishing, , 2016
Descrizione fisica 1 online resource (389 pages) : color illustrations
Collana Professional expertise distilled
Soggetto topico Business planning - Data processing
Database management
ISBN 1-78588-626-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910798524703321
Anoshin Dmitry  
Birmingham : , : Packt Publishing, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Mastering business intelligence with MicroStrategy : build world-class enterprise business intelligence solutions with MicroStrategy 10 / / Dmitry Anoshin, Himani Rana, Ning Ma
Mastering business intelligence with MicroStrategy : build world-class enterprise business intelligence solutions with MicroStrategy 10 / / Dmitry Anoshin, Himani Rana, Ning Ma
Autore Anoshin Dmitry
Edizione [1st edition]
Pubbl/distr/stampa Birmingham : , : Packt Publishing, , 2016
Descrizione fisica 1 online resource (389 pages) : color illustrations
Collana Professional expertise distilled
Soggetto topico Business planning - Data processing
Database management
ISBN 1-78588-626-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910806123903321
Anoshin Dmitry  
Birmingham : , : Packt Publishing, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui