Oracle Business Intelligence with Machine Learning

Artificial Intelligence Techniques in OBIEE for Actionable BI
1. Auflage 2017
ISBN: 978-1-4842-3254-5
Verlag: Apress

Buch, Englisch, 199 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 335 g

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.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Bulusu, Lakshman

Abellera, Rosendo

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik
• Mathematik | Informatik EDV | Informatik Betriebssysteme Linux Betriebssysteme, Open Source Betriebssysteme
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Chapter 1:  Overview of Machine LearningChapter Goal: Introduce Machine Learning concepts and explain the evolution of machine learning u the realm of artificial intelligence.No of pages: 50-60Sub -Topics1. Overview of Machine Learning2. Evolution of Artificial Intelligence and Machine Learning 3. Introduction of Machine Learning and components in OBIEEChapter 2:  Business Intelligence, Big Data, and Cloud Computing Chapter Goal: Introduce emerging scalable computing platforms and how machine learning can be fully utilized in cloud computing architectures. Introduction to the Oracle Cloud as it pertains to machine learningNo of pages: 50-60Sub - Topics 1. Overview of Business Intelligence and Big Data2. Overview of emerging cloud computing architectures and their components  3. Oracle Cloud architectures, virtualization and leveraging hardware capabilities.4. Scaling specific machine learning algorithms on the cloud.Chapter 3: The Oracle R Technologies and R EnterpriseChapter Goal: Provide an overview of R technologies for the enterprise. It will explain how to perform Big Data advanced analytics with machine learning with the R ecosystem. This chapter will also discuss the expansive set of open source R packages in solutions as well as leveraging R scripts. Also briefly explain how Oracle R Enterprise can be used with OBIEE. No of pages : 80-90Chapter 4:  Why Machine Learning with OBIEE NowChapter Goal: Provide the practical reasons and explanation of why machine learning utilizing OBIEE can now be successfully utilized. Include an overview of providing businesses with a competitive advantage using predictive analytics.No of pages : 70-80Sub - Topics:  1. The marriage of artificial intelligence and business intelligence 2. Evolution of OBIEE to its current version3. The birth and history of machine learning for OBIEE4. OBIEE on the Oracle Cloud as an optimal platform5. Oracle Business Intelligence Cloud Service (BICS)6. The future of artificial intelligence, in particular machine learning, as it pertain to business intelligence in the corporate enterprise
Chapter 5: Use Case: Machine Learning in OBIEE 12cChapter Goal: Provide a real world use case for leveraging machine learning in OBIEE to build an advanced decision-making solution.No of pages: 50-60Chapter 6: Implementing Machine Learning in OBIEE 12cChapter Goal: Provide a step-by-step guide for implementing machine learning utilizing OBIEE for an advanced decision-making solution No of pages: 80-90

Über Autor(innen)

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 was then 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 has published 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.