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.
A comprehensive guide from Oracle experts, that will act as your single point of reference for building an Oracle BI 12c system that turns data in actionable insight. About This Book Come, start your first Oracle Business intelligence system and excel in BI with this exhaustive guide An all-encompassing guide for your Oracle business intelligence needs Learn from the self-paced professional guidance and implement Oracle business intelligence using this easy-to-follow guide by our experts Who This Book Is For If your job includes working on data, improving the financial or operational performance of your organization or you are a consultant for the above, then this book is for you. If you have been placed on a business intelligence project, then this book is for you. If you are the Project Manager, Business Analyst or Data Scientist then this book is for you. If you are an end user of Oracle Business Intelligence, then this book is for you too. Having a basic understanding of databases and the use of Business Intelligence is expected, but no knowledge of Oracle BI is required. What You Will Learn Install OBIEE in Windows, including how to create the underlying Weblogic Application server and the required database Build the BI system repository, the vital engine connecting your data to the front end of Oracle BI Develop effective analysis, draw out meaning from the data, and present it to end users on interactive dashboards Build pixel-perfect, printable reports using the embedded BI Publisher feature Build agents for actionable insight and enable your users to act on Business Intelligence at their desktop or on the move Understand the various aspects of securing the Oracle BI system, from data restrictions to whole dashboard access rights Get acquainted with the system management tools and methods available for the continuous improvement of your system In Detail Oracle Business Intelligence Enterprise Edition (OBIEE) 12c is packed full of features and has a fresh approach to information presentation, system management, and security. OBIEE can help any organization to understand its data, to make useful information from data, and to ensure decision-making is supported by facts. OBIEE can focus on information that needs action, alerting users when conditions are met. OBIEE can be used for data analysis, form production, dashoarding, and workflow processes. We will introduce you to OBIEE features and provide a step-by-step guide to build a complete system from scratch. With this guide, you will be equipped with a good basic understanding of what the product contains, how to install and configure it, and how to create effective Business Intelligence. This book contains the necessary information for a beginner to create a high-performance OBIEE 12c system. This book is also a guide that explains how to use an existing OBIEE 12c system, and shows end users how to create. Style and approach This book will take you from one feature to another in a step-by-step manner and will teach how you can create effective business intelligence using Oracle Business Intelligence Enterprise Edition. You will be taught how to create BI solutions and dashboards from scratch. There will be multiple modules in the book, each module spread in chapters, that will cover one aspect of business intelligence in a systematic manner.
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. You will: 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.
Master Oracle Business Intelligence 11g Reports and Dashboards Deliver meaningful business information to users anytime, anywhere, on any device, using Oracle Business Intelligence 11g. Written by Oracle ACE Director Mark Rittman, Oracle Business Intelligence 11g Developers Guide fully covers the latest BI report design and distribution techniques. Find out how to execute effective queries, build accurate models, use scorecards and KPIs, create dynamic reports, set up dashboards, and publish to smartphones and wireless devices. This Oracle Press guide contains comprehensive details on Oracle Exalytics In-Memory Machine, the best-in-class, preintegrated BI platform. Install or upgrade to Oracle Business Intelligence 11g Develop and manage custom Oracle Business Intelligence repositories Access relational, file, and multidimensional data sources Design print-quality reports with Oracle Business Intelligence Publisher Create web-enabled analyses, dashboards, and visualizations Integrate with other applications using Oracle Business Intelligence 11g Action Framework Employ authentication, authorization, and row-level security Configure and deploy Oracle Exalytics In-Memory Machine
The next big area within the information and communication technology field is Artificial Intelligence (AI). The industry is moving to automate networks, cloud-based systems (e.g., Salesforce), databases (e.g., Oracle), AWS machine learning (e.g., Amazon Lex), and creating infrastructure that has the ability to adapt in real-time to changes and learn what to anticipate in the future. It is an area of technology that is coming faster and penetrating more areas of business than any other in our history. AI will be used from the C-suite to the distribution warehouse floor. Replete with case studies, this book provides a working knowledge of AI’s current and future capabilities and the impact it will have on every business. It covers everything from healthcare to warehousing, banking, finance and education. It is essential reading for anyone involved in industry.
This book highlights the practical aspects of using Oracle Essbase and Oracle Business Intelligence Enterprise Edition (OBIEE) as a comprehensive BI solution. It explains the key steps involved in Oracle Essbase and OBIEE implementations. Using case studies, the book covers Oracle Essbase for analytical BI and data integration, using OBIEE for operational BI including presentation services and BI Publisher for real-time reporting services, Self-service BI– in terms of VLDB, scalability, high performance, stability, long-lasting and ease of use that saves time, effort, and costs, while maximizing ROI.
Build Next-Generation In-Database Predictive Analytics Applications with Oracle Data Miner “If you have an Oracle Database and want to leverage that data to discover new insights, make predictions, and generate actionable insights, this book is a must read for you! In Predictive Analytics Using Oracle Data Miner: Develop & Use Oracle Data Mining Models in Oracle Data Miner, SQL & PL/SQL, Brendan Tierney, Oracle ACE Director and data mining expert, guides you through the basic concepts of data mining and offers step-by-step instructions for solving data-driven problems using SQL Developer’s Oracle Data Mining extension. Brendan takes it full circle by showing you how to deploy advanced analytical methodologies and predictive models immediately into enterprise-wide production environments using the in-database SQL and PL/SQL functionality. Definitely a must read for any Oracle data professional!” --Charlie Berger, Senior Director Product Management, Oracle Data Mining and Advanced Analytics Perform in-database data mining to unlock hidden insights in data. Written by an Oracle ACE Director, Predictive Analytics Using Oracle Data Miner shows you how to use this powerful tool to create and deploy advanced data mining models. Covering topics for the data scientist, Oracle developer, and Oracle database administrator, this Oracle Press guide shows you how to get started with Oracle Data Miner and build Oracle Data Miner models using SQL and PL/SQL packages. You'll get best practices for integrating your Oracle Data Miner models into applications to automate the discovery and distribution of business intelligence predictions throughout the enterprise. Install and configure Oracle Data Miner for Oracle Database 11g Release 11.2 and Oracle Database 12c Create Oracle Data Miner projects and workflows Prepare data for data mining Develop data mining models using association rule analysis, classification, clustering, regression, and anomaly detection Use data dictionary views and prepare your data using in-database transformations Build and use data mining models using SQL and PL/SQL packages Migrate your Oracle Data Miner models, integrate them into dashboards and applications, and run them in parallel Build transient data mining models with the Predictive Queries feature in Oracle Database 12c
With exponentially increasing amounts of data accumulating in real-time, there is no reason why one should not turn data into a competitive advantage. While machine learning, driven by advancements in artificial intelligence, has made great strides, it has not been able to surpass a number of challenges that still prevail in the way of better success. Such limitations as the lack of better methods, deeper understanding of problems, and advanced tools are hindering progress. Challenges and Applications of Data Analytics in Social Perspectives provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The content within this publication examines topics that include collaborative filtering, data visualization, and edge computing. It provides research ideal for data scientists, data analysts, IT specialists, website designers, e-commerce professionals, government officials, software engineers, social media analysts, industry professionals, academicians, researchers, and students.
With the emergence of Artificial Intelligence (AI) in the business world, a new era of Business Intelligence (BI) has been ushered in to create real-world business solutions using analytics. BI developers and practitioners now have tools and technologies to create systems and solutions to guide effective decision making. Decisions can be made on the basis of more reliable and accurate information and intelligence, which can lead to valuable, actionable insights for business. Previously, BI professionals were stymied by bad or incomplete data, poorly architected solutions, or even just outright incapable systems or resources. With the advent of AI, BI has new possibilities for effectiveness. This is a long-awaited phase for practitioners and developers and, moreover, for executives and leaders relying on knowledgeable and intelligent decision making for their organizations. Beginning with an outline of the traditional methods for implementing BI in the enterprise and how BI has evolved into using self-service analytics, data discovery, and most recently AI, AI Meets BI first lays out the three typical architectures of the first, second, and third generations of BI. It then takes an in-depth look at various types of analytics and highlights how each of these can be implemented using AI-enabled algorithms and deep learning models. The crux of the book is four industry use cases. They describe how an enterprise can access, assess, and perform analytics on data by way of discovering data, defining key metrics that enable the same, defining governance rules, and activating metadata for AI/ML recommendations. Explaining the implementation specifics of each of these four use cases by way of using various AI-enabled machine learning and deep learning algorithms, this book provides complete code for each of the implementations, along with the output of the code, supplemented by visuals that aid in BI-enabled decision making. Concluding with a brief discussion of the cognitive computing aspects of AI, the book looks at future trends, including augmented analytics, automated and autonomous BI, and security and governance of AI-powered BI.
Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions
