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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 | ||
| ||
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 | ||
| ||
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 | ||
| ||
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 | ||
| ||
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 | ||
| ||
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 | ||
| ||
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 | ||
| ||
Practical Business Analytics Using R and Python : Solve Business Problems Using a Data-driven Approach / / by Umesh R. Hodeghatta, Umesha Nayak
| Practical Business Analytics Using R and Python : Solve Business Problems Using a Data-driven Approach / / by Umesh R. Hodeghatta, Umesha Nayak |
| Autore | Hodeghatta Umesh R. |
| Edizione | [2nd ed. 2023.] |
| Pubbl/distr/stampa | Berkeley, CA : , : Apress : , : Imprint : Apress, , 2023 |
| Descrizione fisica | 1 online resource (716 pages) |
| Disciplina | 658.4012028553 |
| Soggetto topico |
Decision making - Data processing
Business planning - Data processing R (Computer program language) Python (Computer program language) |
| ISBN |
9781484287545
1484287541 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Section 1: Introduction to Analytics -- Chapter 1: Business Analytics Revolution -- Chapter 2: Foundations of Business Analytics -- Chapter 3: Structured Query Language (SQL) Analytics -- Chapter 4: Business Analytics Process -- Chapter 5: Exploratory Data Analysis (EDA) -- Chapter 6: Evaluating Analytics Model Performance -- Section II: Supervised Learning and Predictive Analytics -- Chapter 7: Simple Linear Regressions -- Chapter 8: Multiple Linear Regressions -- Chapter 9: Classification -- Chapter 10: Neural Networks -- Chapter 11: Logistic Regression -- Section III: Time Series Models -- Chapter 12: Time Series – Forecasting -- Section IV: Unsupervised Model and Text Mining -- Chapter 13: Cluster Analysis -- Chapter 14: Relationship Data Mining -- Chapter 15: Mining Text and Text Analytics -- Chapter 16: Big Data and Big Data Analytics -- Section V: Business Analytics Tools -- Chapter 17: R programming for Analytics -- Chapter 18: Python Programming for Analytics. |
| Record Nr. | UNINA-9910686772103321 |
|
Hodeghatta Umesh R.
|
||
| Berkeley, CA : , : Apress : , : Imprint : Apress, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
