Data analytics for business: AI-ML-PBI-SQL-R
Gespeichert in:
1. Verfasser: | |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
London ; New York
Routledge
2024
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Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | xii, 270 Seiten Illustrationen, Diagramme |
ISBN: | 9781032372624 9781032372631 |
Internformat
MARC
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Datensatz im Suchindex
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Contents PART ONE Fundamental Business 1 2 Insights 1 3 introduction 1J Data Analytics and Applications 3 1.2 Learning Outcomes 5 1.3 Tools and Data 6 Databases 2.1 8 Introduction 2.1.1 8 Overview 8 2.1.2 Motivation and Managers 9 2.1.3 Database Integration and Cloud Solutions 2.1.4 Security, Ethics and Law '; 2.2 Systems 2.2.1 Concept 2.2.3 Setup and Configuration 2.2.4 Databases 2.3 SQL-Tables 13 ■ « ,- 2.2.2 Database Engines 12 12 13 - 14 15 18 21 2.3.1 Definition 21 2.3.2 Inserting Records 22 2.3.3 Deleting Records 23 2.3.4 Normal Forms 23 2.3.5 Data Access and R 26
CONTENTS 2.4 SQL - Queries 2.5 Unconditional Query 31 2.4.2 View 32 2.4.3 Conditional Query 33 2.4.4 Group and Aggregate 33 2.4.5 Join Query 34 Entity Relationships Directional ER 37 2.5.2 Combining Entities 40 Business Intelligence 3.1 Introduction 3.1.1 3.2 3.4 3.5 3.6 Definitions Tools 3.2.1 3.3 37 2.5.1 2.6 Summary 3 31 2.4.1 41 43 43 43 45 PBI Overview Design and Visualisations 47 48 3.3.1 Visualisations 48 3.3.2 FBI Crash Course 53 3.3.3 PBI General Considerations Analytics 69 72 3.4.1 Trends and Forecasts 73 3.4.2 PBI Key Influencers Visual 75 3.4.3 DAX Functions Miscellaneous 77 80 3.5.1 Best Practiccs/Sharcd Experiences 80 3.5.2 Bit-Size Challenges 80 3.5.3 Create Custom R Visualfor PBI Summary 85 88 PART TWO Coding and Frameworks 91 4 Data Science Languages 93 Introduction 93 4.1 4.1.1 4.2 Language R 94 Data Types and Operations 96 4.2.1 Arithmetic and Basic DataTypes 4.2.2 Compound Data Types 4.2.3 String Operations and RegularExpressions vi 94 4.1.2 Projects and Libraries 96 105 ш
4.3 Controls and Functions 4.3.1 4.3.2 If Conditions Loops - Control Flow 4.3.3 Functions 4.4 5 I I ! Il4 114 11b 4.3.4 Coding with GPT lib 4.3.5 Data Transfer Function 120 Summary Data Analytics Frameworks 12I 12 1 5.1 Introduction 12! 5.2 Modelling and Applications 124 5.2.1 5.3 5.4 126 121! Machine Learning Roadmap 5.3.1 Preprocessing, Splitting and Balancing I Ю Bl 5.3.2 Learning 1 11 5.3.3 Evaluation and Application 114 Knowledge Discovery in Databases (KDD) 1 IS 5.4.2 5.6 124 5.2.3 Business Applications 5.4.1 5.5 Business Scenario Example 5.2.2 Real World and Prediction Model KDD - Problem and Resourcing KDD - Data Cleansing and Preprocessing 11b 1 !» 5.4.3 KDD - Data Mining and Evaluation 140 5.4.4 KDD - Interpretation and Exploitation Cross-Industry Standard Process for DataMining 141 141 5.5.1 Understanding 141 5.5.2 Preparation and Modelling 14! 5.5.3 Evaluation and Deployment 14! Summary 144 PART THREE Learning ^’ 6 Statistical Learning 147 6.1 Introduction 147 6.2 Models and Quality Measures 14» 6.3 6.2.1 Quality Measures 14» 6.2.2 Confusion Matrix 1 Descriptive Statistics 156 6.3.1 Exploring Data ] 6.3.2 Correlation 1f)1 6.4 Linear Regression vii
CONTENTS 6.4.1 Simple Linear Regression 6.4.2 Multivariate Linear Regression 6.5 6.6 165 166 6.4.3 Applications, ML Parts and Statistik - 167 Logistic Regression 174 6.5.1 177 Multiple Classes - One versus AM 6.5.2 Old Faithful Example 179 Summary 181 7 Supervised Machine Learning 183 7.1 Introduction 183 7.2 Regression and Classification Trees 184 7.2.1 Regression Tree 7.2.2 Classification Trees 7.3 184 191 Tree-Based Algorithms 193 7.3.1 Random Forest 193 7.3.2 Trees 195 7.4 Nearest Neighbours Classifier 195 7.5 Summary 198 8 Unsupervised Machine Learning 199 8.1 Introduction 199 8.2 K-Means Clustering 200 8.2.1 8.3 Application 200 8.2.2 Concept and Algorithm 202 Hierarchical Clustering 204 8.3.1 206 Dendrogram 8.4 Self-Organising Maps 208 8.5 Expectation Maximisation 212 8.6 Summary 217 PART FOUR Artificial Intelligence 9 219 Artificial Intelligence 221 Introduction 221 9.1.1 Al Applications 222 9.1.2 Classic Al Areas 9.1 9.2 9.3 viii 223 Learning - ANN and SVM 224 9.2.1 Recap 224 9.2.2 ANN Model 226 9.2.3 Support Vector Machines (SVM) 231 Problem Solving - GA and SA 238 9.3.1 239 Knapsack Problem
9.4 9.3.2 Brute Force 2 5’1 9.3.3 Genetic Algorithm 241 9.3.4 Methods Overview 242 Games - Minimax 244 Chess 244 9.4.1 9.4.2 Minimax Algorithm 248 9.5 Reasoning Under Uncertainty - BBN 2" 2 9.6 Summary 2 54 PART FIVE References ^’1 -^ i Index ix |
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illustrated | Illustrated |
index_date | 2024-07-03T23:39:36Z |
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institution | BVB |
isbn | 9781032372624 9781032372631 |
language | English |
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spelling | Garn, Wolfgang Verfasser (DE-588)1330556909 aut Data analytics for business AI-ML-PBI-SQL-R Wolfgang Garn London ; New York Routledge 2024 xii, 270 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Unternehmen (DE-588)4061963-1 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Wirtschaftsinformatik (DE-588)4112736-5 gnd rswk-swf Unternehmen (DE-588)4061963-1 s Datenanalyse (DE-588)4123037-1 s Wirtschaftsinformatik (DE-588)4112736-5 s DE-604 Erscheint auch als Online-Ausgabe 978-1003336099 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034987127&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Garn, Wolfgang Data analytics for business AI-ML-PBI-SQL-R Unternehmen (DE-588)4061963-1 gnd Datenanalyse (DE-588)4123037-1 gnd Wirtschaftsinformatik (DE-588)4112736-5 gnd |
subject_GND | (DE-588)4061963-1 (DE-588)4123037-1 (DE-588)4112736-5 |
title | Data analytics for business AI-ML-PBI-SQL-R |
title_auth | Data analytics for business AI-ML-PBI-SQL-R |
title_exact_search | Data analytics for business AI-ML-PBI-SQL-R |
title_exact_search_txtP | Data analytics for business AI-ML-PBI-SQL-R |
title_full | Data analytics for business AI-ML-PBI-SQL-R Wolfgang Garn |
title_fullStr | Data analytics for business AI-ML-PBI-SQL-R Wolfgang Garn |
title_full_unstemmed | Data analytics for business AI-ML-PBI-SQL-R Wolfgang Garn |
title_short | Data analytics for business |
title_sort | data analytics for business ai ml pbi sql r |
title_sub | AI-ML-PBI-SQL-R |
topic | Unternehmen (DE-588)4061963-1 gnd Datenanalyse (DE-588)4123037-1 gnd Wirtschaftsinformatik (DE-588)4112736-5 gnd |
topic_facet | Unternehmen Datenanalyse Wirtschaftsinformatik |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034987127&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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