This book is a step-by-step tutorial filled with practical examples which will show readers how to configure and manage IaaS and DBaaS with Oracle Enterprise Manager. If you are a cloud administrator or a user of self-service provisioning systems offered by Enterprise Manager, this book is ideal for you. It will also help administrators who want to understand the chargeback mechanism offered by Enterprise Manager.An understanding of the basic building blocks of cloud computing such as networking, virtualization, storage, and so on, is needed by those of you interested in this book

This book focuses on teaching you by example. The book walks you through every aspect of Pentaho Data Integration, giving systematic instructions in a friendly style, allowing you to learn in front of your computer, playing with the tool. The extensive use of drawings and screenshots make the process of learning Pentaho Data Integration easy. Throughout the book, numerous tips and helpful hints are provided that you will not find anywhere else.This book is a must-have for software developers, database administrators, IT students, and everyone involved or interested in developing ETL solutions, or, more generally, doing any kind of data manipulation. Those who have never used Pentaho Data Integration will benefit most from the book, but those who have, they will also find it useful.This book is also a good starting point for database administrators, data warehouse designers, architects, or anyone who is responsible for data warehouse projects and needs to load data into them.

This book is a step-by-step tutorial filled with practical examples which will show you how to build and manage a Hadoop cluster along with its intricacies. This book is ideal for database administrators, data engineers, and system administrators, and it will act as an invaluable reference if you are planning to use the Hadoop platform in your organization. It is expected that you have basic Linux skills since all the examples in this book use this operating system. It is also useful if you have access to test hardware or virtual machines to be able to follow the examples in the book.

It is in the context of maturity that one needs to read the book - Master Data Management and Enterprise Engineering by Dr. M. Naoulo. The world of technology has several related yet distinct approaches - Martin's and Finklestein's information engineering, Ted Codd's relational technology, Inmon's data warehouse, and others. This book takes these approaches and others and does two important things - it blends them together and it takes the bodies of thought and turns them into an engineering approach. As such this book is another important step in the evolution of computer science. This is a next step in the maturation of computer science. I recommend it to any serious student of computer science or to any serious practitioner. =========== W.H. (Bill) Inmon. May 21, 2012. =========== The book establishes the Fundamentals of design, modeling, architecture, and management of Master, Transactional, and Process Data and the Principles of Enterprise Engineering. The book comprises innovative techniques and elegant approach and design to address: > Master Data Management thru grouping and classifying the Master Data in an innovative way that can be implemented across the Enterprise Data Architecture: Central Data Repository and Business and Enterprise Intelligence (BI & EI) Data Marts. This data classification is based on the questions: Why, How, Who, What, Where and When. > Separating the Master Data, Transactional Data, and Process Data. This separation enables the easiness in dealing with MDM, BI, and EI. The separation approach enormously facilitates the mapping and propagation between the Central Data Repository and the Business and Enterprise Data Marts. >The basics and techniques of the design of the Enterprise Engineering Model. This model supports the Transactional Systems, Business Intelligence, Business Process Management, Enterprise Intelligence, and Enterprise Engineering. > Synchronization and Integration of Master, Transactional, and Process Data across the enterprise: Legacy Systems, Central Data Repository, and Business and Intelligence Data Marts. > Assessing the different Enterprise Data Architectures. The first part encompasses the Enterprise Data Framework and its new Modeling Techniques. The Enterprise Data Framework illustrates and depicts the Data Architecture across the enterprise covering the integration and consolidation of the data of the Legacy Systems in a Central Data Repository and the propagation of this data into the Business and Enterprise Intelligence Data Marts. The Enterprise Engineering Model presents a clear and concise illustration depicting the Operational aspects of the Enterprise and their relations to the Enterprise's needs. It includes: > Master Data representing the main objects of an enterprise, > Transactional Data detailing the results of transactions occurring in an enterprise, and > Process Data capturing the data pertinent to the activities of the functioning of an enterprise. The second part encompasses the Enterprise Engineering Framework, Methodology, Guidelines, Deliverables, and Techniques. It bestows the blueprint of the functioning of enterprises. This part details the basics of Enterprise Engineering and its implementation thru the processing of the Enterprise Engineering Model. It provides the cost data (materiel cost, labor cost, time) reflecting the functioning of the Enterprise and point out the efficiency, performance, strengths, and weaknesses of its operation. Detailed Case Studies are presented supporting the theoretical aspect of Enterprise Engineering. These Case Studies provide clear and practical hands-on exercises reflecting the functioning of the Enterprises and illustrating the implementation of Enterprise Engineering.

This easy-to-understand tutorial covers Oracle Warehouse Builder from the ground up, and taps into the author's wide experience as a software and database engineer. Written in a relaxed style with step-by-step explanations, lots of screenshots are provided throughout the book. There are numerous tips and helpful hints throughout that are not found in the original documentation. By following this book, you can use Oracle Warehouse Builder in the best possible way and maximize your learning potential. This book is an update of Oracle Warehouse Builder 11g: Getting Started. This book is a good starting point for database engineers, administrators, and architects who are responsible for data warehouse projects and need to design them and load data into them. If you are someone who wants to learn Oracle Warehouse Builder and expand your knowledge of the tool and data warehousing, this is an ideal book for you. No prior data warehouse or database experience is presumed. All new database and data warehouse technical terms and concepts explained in clear easy-to-understand language.

Are you struggling with a disparate data resource? Are there multiple existences of the same business fact scattered throughout the data resource? Are those multiple existences out of synch with each other? Do you have difficulty finding the data you need to support business activities? Do the data you find have poor quality? If the answer to any of these questions is Yes, then you need this book to guide you toward creating an integrated data resource. Most public and private sector organisations have a disparate data resource that was created over many years. That disparate data resource contains multiple existences of business facts that are out of synch with each other, are of poor quality, and are difficult to locate. The traditional approach to dealing with a disparate data resource is to perform periodic and temporary data integration to support a specific application or business activity. Those piecemeal data integration efforts may meet a current need, but seldom solve the underlying problems with a disparate data resource, and sometimes make the situation worse. This book explains how to go about understanding and resolving a disparate data resource and creating a comparate data resource that fully meets an organisation's current and future business information demand. It builds on "Data Resource Simplexity", which described how to stop the burgeoning data disparity. It explains the concepts, principles, and techniques for understanding a disparate data resource within the context of a common data architecture, and resolving that disparity with minimum impact on the business. Like "Data Resource Simplexity", Michael Brackett draws on five decades of data management experience building and managing data resources, and resolving disparate data resources in both public and private sector organisations. He leverages theories, concepts, principles, and techniques from a wide variety of disciplines, such as human dynamics, mathematics, physics, chemistry, and biology, and applies them to the process of understanding and resolving a disparate data resource. He shows you how to approach and resolve a disparate data resource, and build a comparate data resource that fully supports the business.

This book has step-by-step instructions to solve data manipulation problems using PDI in the form of recipes. It has plenty of well-organized tips, screenshots, tables, and examples to aid quick and easy understanding. If you are a software developer or anyone involved or interested in developing ETL solutions, or in general, doing any kind of data manipulation, this book is for you. It does not cover PDI basics, SQL basics, or database concepts. You are expected to have a basic understanding of the PDI tool, SQL language, and databases.

Business intelligence is a huge segment of the software world. Gartner Group estimates that sales in this area surpassed $10 billion in 2010, with Oracle as the second largest vendor in the category. At the heart of these analytical-oriented applications are dimensional data models with OLAP as a critical component for achieving high-performance.

If you want to do development work in this area or understand how to maximize its value, read this book. A professional in the world of analytics and business intelligence needs an understanding of OLAP's specific data modeling principles, its analysis capabilities, and its relationship to other analytical approaches. All are presented here in a systematic fashion written in an easy-to-follow style.

"The Multidimensional Data Modeling Toolkit" takes you on an instructional journey into the world of OLAP. It provides a comprehensive examination of data modeling and analytical techniques for the native multi-dimensional information storage framework that Oracle OLAP provides. You will get an in-depth look at OLAP's analytical possibilities as well as comparison with the approaches used in data mining and statistics. You will learn the design issues and get step-by-step programming instructions for solving real-world problems. Written by an expert with over 15 years experience using Oracle OLAP and its predecessors, the book explains critical techniques rarely taught in university or technical training programs.

"The Multidimensional Data Modeling Toolkit" takes you under the covers and shows you what happens inside of Oracle's Analytic Workspaces where the multidimensional magic occurs. Programming instruction is based on the Oracle 10g database, but most of the statements shown will work with other editions of the database, such as Oracle 9i and 11g, and even earlier editions of the technology found in stand-alone products such Oracle Financial Analyzer and Oracle Sales Analyzer

The data analysis principles presented are universal and can be applied to application that uses OLAP, for example OBIEE, Essbase, Cognos, Business Objects, and Microsoft Analysis Services (SSAS). Whether you are new to business intelligence or a seasoned practitioner, you should find The Multi-dimensional Data Modeling Toolkit with plenty of valuable insights to offer.

According to leading analysts, Business Intelligence (BI) has been a top priority for worldwide organizations within the past five years, and it will continue to be a priority in the near future. With a global user base of millions, Cognos is known as a leading provider of Business Intelligence tools. Cognos' latest release is Cognos 8 BI, a powerful suite of modules that share one common infrastructure for the creation, management and deployment of queries, reports, analyses, scorecards, dashboards and alerts--all designed to support an organization's Business Intelligence objectives. As a consultant with over 10 years of Cognos BI experience, Juan A. Padilla is an expert in helping organizations develop and implement Business Intelligence solutions. As the first in a series of books on Cognos products, with Cognos 8 BI for Consumers, Padilla provides a step-by-step introductory guide for the key component of the Cognos infrastructure: Cognos Connection. This book walks the reader through the fundamentals of Cognos Connection, the powerful web portal that is the foundation for all users of Cognos 8 BI, from end users to administrators. The guide relies heavily on screen images that demonstrate product workflow and available features; even readers who do not have "live" access to Cognos software can learn about it This guide has been designed for: - companies evaluating Cognos as a potential BI solution and need to know the capabilities before purchasing; - those planning to use Cognos products professionally, e.g. job-seekers or consultants; - organizations using previous versions of Cognos who need to evaluate the latest version before upgrading or migrating; and - novice "hands-on" users of Cognos, for whom this guide will be an "anytime, anywhere" tutorial and reference source. In this book, you will discover: - how Cognos Connection functions; - how to work with reports, including scheduling, setting parameters and changing formats; - how to customize the look and feel of the interface to your preferences; - a simulation of Cognos' security features; and - report samples that show the powerful reporting capabilities of Cognos 8 BI.

Data Warehousing 101: Concepts and Implementation will appeal to those planning data warehouse projects, senior executives, project managers, and project implementation team members. It will also be useful to functional managers, business analysts, developers, power users, and end-users. Data Warehousing 101: Concepts and Implementation, which can be used as a textbook in an introductory data warehouse course, can also be used as a supplemental text in IT courses that cover the subject of data warehousing. Data Warehousing 101: Concepts and Implementation reviews the evolution of data warehousing and its growth drivers, process and architecture, data warehouse characteristics and design, data marts, multi-dimensionality, and OLAP. It also shows how to plan a data warehouse project as well as build and operate data warehouses. Data Warehousing 101: Concepts and Implementation also covers, in depth, common failure causes and mistakes and provides useful guidelines and tips for avoiding common mistakes.

Data Warehousing ist seit einigen Jahren in vielen Branchen ein zentrales Thema. Die anfangliche Euphorie tauschte jedoch daruber hinweg, dass zur praktischen Umsetzung gesicherte Methoden und Vorgehensmodelle fehlten. Dieses Buch stellt einen Beitrag zur UEberwindung dieser Lucke zwischen Anspruch und Wirklichkeit dar. Es gibt im ersten Teil einen UEberblick uber aktuelle Ergebnisse im Bereich des Data Warehousing mit einem Fokus auf methodischen und betriebswirtschaftlichen Aspekten. Es finden sich u.a. Beitrage zur Wirtschaftlichkeitsanalyse, zur organisatorischen Einbettung des Data Warehousing, zum Datenqualitatsmanagement, zum integrierten Metadatenmanagement und zu datenschutzrechtlichen Aspekten sowie ein Beitrag zu moeglichen zukunftigen Entwicklungsrichtungen des Data Warehousing. Im zweiten Teil berichten Projektleiter umfangreicher Data Warehousing-Projekte uber Erfahrungen und Best Practices.

Data Storage: Systems, Management and Security Issues begins with a chapter comparing digital or electronic storage systems, such as magnetic, optical, and flash, with biological data storage systems, like DNA and human brain memory. In the main part of the chapter, the following quantitative storage traits are discussed: data organisation, functionality, data density, capacity, power consumption, redundancy, integrity, access time, data transfer rate. Afterwards, various facets of data warehouses as well as the necessity for security measures are reviewed. Because the significance of security tools is greater than ever before, the pertinent strategies and economics are discussed. The final chapter supplements this by discussing media and storage systems reliability and confidentiality in order to make a greater claim about storage security. Confidentiality, integrity and availability are three aspects of security identified as ones that should be preserved during data transmission, processing and storage.