Use machine learning and Oracle Business Intelligence Enterprise Edition (OBIEE) as a comprehensive BI solution. This book follows a when-to, why-to, and how-to approach to explain the key steps involved in utilizing the artificial intelligence components now available for a successful OBIEE implementation. Oracle Business Intelligence with Machine Learning covers various technologies including using Oracle OBIEE, R Enterprise, Spatial Maps, and machine learning for advanced visualization and analytics.
The machine learning material focuses on learning representations of input data suitable for a given prediction problem. This book focuses on the practical aspects of implementing machine learning solutions using the rich Oracle BI ecosystem. The primary objective of this book is to bridge the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to machine learning with OBIEE.
What You Will Learn
- See machine learning in OBIEE
- Master the fundamentals of machine learning and how it pertains to BI and advanced analytics
- Gain an introduction to Oracle R Enterprise
- Discover the practical considerations of implementing machine learning with OBIEE
Who This Book Is For
Analytics managers, BI architects and developers, and data scientists.
| About the Authors |
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vii | |
| About the Technical Reviewer |
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| Acknowledgments |
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| Introduction |
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1 | (10) |
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Artificial Intelligence and Machine Learning |
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2 | (5) |
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Overview of Machine Learning |
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4 | (1) |
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Patterns, Patterns, Patterns |
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5 | (2) |
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7 | (1) |
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7 | (1) |
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Introduction to Machine-Learning Components in OBIEE |
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8 | (1) |
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8 | (1) |
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9 | (1) |
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9 | (1) |
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10 | (1) |
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Chapter 2 Business Intelligence, Big Data, and the Cloud |
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The Goal of Business Intelligence |
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11 | (3) |
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12 | (2) |
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But Why Machine Learning Now? |
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14 | (1) |
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A Picture Is Worth a Thousand Words |
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14 | (3) |
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17 | (3) |
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The Future of Data Preparation with Machine Learning |
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18 | (1) |
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Oracle Business Intelligence Cloud Service |
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19 | (1) |
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19 | (1) |
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19 | (1) |
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20 | (1) |
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20 | (3) |
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Chapter 3 The Oracle R Technologies and R Enterprise |
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23 | (76) |
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R Technologies for the Enterprise |
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23 | (15) |
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23 | (2) |
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25 | (13) |
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Using ORE for Machine Learning and Business Intelligence with OBIEE: Start-to-Finish Pragmatics |
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38 | (51) |
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Using the ORD randomForest Algorithm to Predict Wine Origin |
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38 | (3) |
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Using Embedded R Execution in Oracle DB and the ORE R Interface to Predict Wine Origin |
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41 | (11) |
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Using ore.randomForest Instead of R's randomForest Model |
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52 | (5) |
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Using Embedded R Execution in Oracle DB with the ORE SQL Interface to Predict Wine Origin |
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57 | (9) |
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Generating PNG Graph Using the ORE SQL Interface and Integrating It with OBIEE Dashboard |
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66 | (4) |
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Integrating the PNG Graph with OBIEE |
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70 | (17) |
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Creating the OBIEE Analysis and Dashboard with the Uploaded RPD |
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87 | (2) |
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Machine Learning Trending a Match for EDW |
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89 | (9) |
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98 | (1) |
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Chapter 4 Machine Learning with OBIEE |
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99 | (8) |
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The Marriage of Artificial Intelligence and Business Intelligence |
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99 | (2) |
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Evolution of OBIEE to Its Current Version |
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101 | (2) |
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The Birth and History of Machine Learning for OBIEE |
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103 | (2) |
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OBIEE on the Oracle Cloud as an Optimal Platform |
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105 | (1) |
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Machine Learning in OBIEE |
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105 | (1) |
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106 | (1) |
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Chapter 5 Use Case: Machine Learning in OBIEE 12c |
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107 | (28) |
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107 | (2) |
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Predicting Wine Origin: Using a Machine-Learning Classification Model |
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108 | (1) |
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Using Classified Wine Origin as a Base for Predictive Analytics - Extending BI using machine Learning techniques in OBIEE |
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108 | (1) |
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Using the BI Dashboard for Actionable Decision-Making |
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108 | (1) |
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Technical and Functional Analysis of the Use Cases |
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109 | (24) |
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Analysis of Graph Output: Pairs Plot of Wine Origin Prediction Using Random Forest |
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111 | (1) |
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Analysis of Graph Output: Predicting Propensity to Buy Based on Wine Source |
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111 | (1) |
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Analysis at a More Detailed Level |
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112 | (9) |
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Use Case(s) of Predicting Propensity to Buy |
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121 | (12) |
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133 | (2) |
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Chapter 6 Implementing Machine Learning in OBIEE 12c |
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135 | (60) |
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Business Use Case Problem Description and Solution |
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135 | (52) |
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136 | (1) |
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136 | (11) |
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147 | (21) |
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168 | (5) |
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173 | (1) |
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Implementing the Solution Using the ORE SQL Interface |
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174 | (13) |
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Integrating PNG Output with the OBIEE Dashboard |
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187 | (6) |
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193 | (2) |
| Index |
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Rosendo Abellera : From his beginnings in the US intelligence community more than 25 years ago, Rosendo Abellera has made a life-long career out of utilizing data and information as a critical asset. Coupled with his extensive experience in software, he has become an expert practitioner in the field of business intelligence (BI) and analytics and one of the most experienced practitioners in the industry. As a pioneer in BI, he architected analytical solutions and consulted to some prominent, recognized organizations through the years. Spanning across a multitude of industries, this list includes AAA, Accenture, Comcast, US Department of Interior (DOI), ESPN, Harvard University, John Hancock Financial, Koch Industries, Mercury Systems, Pfizer, Staples, and State Street Corp., for example. Moreover, he has held key management positions to establish the BI practices of several prominent consulting firms and also founded an Oracle Partner firm specializing in what wasthen the newly-branded OBIEE. He is currently a consultant in the Analytics Practice of Mythics Consulting, a leading Oracle Platinum Partner. Rosendo is a veteran of the US Air Force and the National Security Agency (NSA) where he served in Europe and Asia as a cryptologist and linguist for several languages. Lakshman Bulusu is a Senior Oracle Consultant with 23 years of experience in the fields of Oracle RDBMS, SQL, PL/SQL, EDW/BI/EPM, and Oracle-related Java. As an Enterprise-level data warehouse, and business intelligence solution architect/technical manager in the ORACLE RDBMS space, he focused on a best-fit solution architecture and implementation of the Oracle Industry Data Model for telecom. He has worked for major clients in the pharma/healthcare, telecom, financial (banking), retail, and media industry verticals, with special emphasis on cross-platform heterogeneous information architecture and design. He haspublished eight books on Oracle and related technologies, all published in the United States, as well as four books on English poetry. He serves on the development team of qteria.com and Qteria Big Data Analytics. Bulusu is OCPcertified and holds an Oracle Masters credential. He was selected as a FOCUS Expert for his research briefs titled "Raising your SIQ (Social Intelligence Quotient): 5 Key Business Indicators," "Raising your BIQ (Business Intelligence Quotient): 5 Things Your Company Can Do NOW," and "High- Fives for an Innovative HR Strategy" on FOCUS.com. He has written a host of technical articles and spoken at major Oracle conferences in the United States and abroad.
