Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN). Store large datasets with the Hadoop Distributed File System (HDFS) Run distributed computations with MapReduce Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud Load data from relational databases into HDFS, using Sqoop Perform large-scale data processing with the Pig query language Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems

Get up to speed on the extensive changes to the newest release of Microsoft SQL Server The 2012 release of Microsoft SQL Server changes how you develop applications for SQL Server. With this comprehensive resource, SQL Server authority Robert Vieira presents the fundamentals of database design and SQL concepts, and then shows you how to apply these concepts using the updated SQL Server. Publishing time and date with the 2012 release, Beginning Microsoft SQL Server 2012 Programming begins with a quick overview of database design basics and the SQL query language and then quickly proceeds to show you how to implement the fundamental concepts of Microsoft SQL Server 2012. You'll explore the key additions and changes to this newest version, including conditional action constructs, enhanced controls for results paging, application integration with SharePoint and Excel, and development of BI applications. Covers new features such as SQL Azure for cloud computing, client-connectivity enhancements, security and compliance, data replication, and data warehouse performance improvements Addresses essential topics including managing keys, writing scripts, and working with store procedures Shares helpful techniques for creating and changing tables, programming with XML, and using SQL Server Reporting and Integration Services Beginning Microsoft SQL Server 2012 Programming demystifies even the most difficult challenges you may face with the new version of Microsoft SQL Server.

An essential how-to guide for experienced DBAs on the most significant product release since 2005! Microsoft SQL Server 2012 will have major changes throughout the SQL Server and will impact how DBAs administer the database. With this book, a team of well-known SQL Server experts introduces the many new features of the most recent version of SQL Server and deciphers how these changes will affect the methods that administrators have been using for years. Loaded with unique tips, tricks, and workarounds for handling the most difficult SQL Server admin issues, this how-to guide deciphers topics such as performance tuning, backup and recovery, scaling and replication, clustering, and security. Serves as a must-have how-to guide on the new features of the 2012 release of Microsoft SQL Server Walks you through ways to manage and monitor SQL Server and automate administration Guides you through SQL Azure for cloud computing, data replication, and data warehouse performance improvements Addresses client-connectivity enhancements, new features that ensure high availability of mission-critical applications, and tighter integration with Excel and SharePoint for data analysis and reporting Highlights major changes to the suite of SQL Server BI tools, including integration, reporting, and analysis services Includes real-world case examples and best practices from Microsoft insiders If you're a database administrator eager to get started with the newest version of SQL Server, then this book is essential reading.

This book presents two data warehouse solutions that deliver significant ROI; market basket analysis, approached as a database design issue rather than a data model issue; and time variance or temporal data, which present past events in their historical context. The former is available to any enterprise with a data warehouse, while the latter provides a simple design that accommodates large data volumes. The text combines these two database designs into one design, which performs market basket analysis of transactions in their historical context.

Using Agile methods, you can bring far greater innovation, value, and quality to any data warehouse, business intelligence, or analytics project. However, conventional Agile methodologies must be carefully adapted to address the unique characteristics of DW/BI projects. In , Agile pioneer Ken Collier shows how to do just that. Agile Analytics Collier introduces platform-agnostic Agile solutions for integrating infrastructures consisting of diverse operational, legacy, and specialty systems that mix commercial and custom code. Using working examples, he shows how to manage analytics development teams with widely diverse skill sets; support enormous and fast-growing data volumes; and more. Collier's techniques offer equal value whether your projects involve "back-end" data management, "front-end" business analysis, or both. Part I focuses on Agile project management techniques and delivery team coordination, introducing core practices that shape the way your agile DW/BI project community works together towards success Part II presents technical methods for enabling continuous delivery of business value at production-quality levels, including evolving superior designs; test-driven DW development; version control; and project automation Collier brings together proven solutions you can apply right now--whether you're an IT decision-maker, data warehouse professional, DBA, business intelligence specialist, or database developer. With his help, you can mitigate project risk, improve business alignment, achieve better results--and have fun along the way.

Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with organizations, and the challenges organizations face in structuring and managing their data. Using a holistic approach to the field of data architecture, the book describes proven methods and technologies to solve the complex issues dealing with data. It covers the various applied areas of data, including data modelling and data model management, data quality, data governance, enterprise information management, database design, data warehousing, and warehouse design. This text is a core resource for anyone customizing or aligning data management systems, taking the Zen-like idea of data architecture to an attainable reality. The book presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios. It teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions. It includes the detail needed to illustrate how the fundamental principles are used in current business practice. The book is divided into five sections, one of which addresses the software-application development process, defining tools, techniques, and methods that ensure repeatable results. Data Architecture is intended for people in business management involved with corporate data issues and information technology decisions, ranging from data architects to IT consultants, IT auditors, and data administrators. It is also an ideal reference tool for those in a higher-level education process involved in data or information technology management. Presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios Teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions Includes the detail needed to illustrate how the fundamental principles are used in current business practice

Oracle 10g Data Warehousing is a guide to using the Data Warehouse features in the latest version of Oracle —Oracle Database 10g. Written by people on the Oracle development team that designed and implemented the code and by people with industry experience implementing warehouses using Oracle technology, this thoroughly updated and extended edition provides an insider’s view of how the Oracle Database 10g software is best used for your application. It provides a detailed look at the new features of Oracle Database 10g and other Oracle products and how these are used in the data warehouse. This book will show you how to deploy the Oracle database and correctly use the new Oracle Database 10g features for your data warehouse. It contains walkthroughs and examples on how to use tools such as Oracle Discoverer and Reports to query the warehouse and generate reports that can be deployed over the web and gain better insight into your business. This how-to guide provides step by step instructions including screen captures to make it easier to design, build and optimize performance of the data warehouse or data mart. It is a ‘must have’ reference for database developers, administrators and IT professionals who want to get to work now with all of the newest features of Oracle Database 10g. It provides a detailed look at the new features of Oracle Database 10g and other Oracle products and how these are used in the data warehouse, including: * How to use the Summary Management features, including Materialized Views and query rewrite, to best effect to radically improve query performance * How to deploy business intelligence to the Web to satisfy today's changing and demanding business requirements * Using Oracle OLAP and Data Mining options * How to understand the warehouse hardware environment and how it is used by new features in the database including how to implement a high availability warehouse environment * Using the new management infrastructure in Oracle Database 10g and how this helps you to manage your warehouse environment

The IBM® Smart Analytics System 9600 is a single, end-to-end business analytics solution to accelerate data warehousing and business intelligence initiatives. It provides integrated hardware, software, and services that enable enterprise customers to quickly and cost-effectively deploy business-changing analytics across their organizations. As a workload-optimized system for business analytics, it leverages the strengths of the System z® platform to drive: Significant savings in hardware, software, operating, and people costs to deliver a complete range of data warehouse and BI capabilities Faster time to value with a reduction in the time and speed associated with deploying Business Intelligence Industry-leading scalability, reliability, availability, and security Simplified and faster access to the data on System z

“This book should satisfy those who want a different perspective than the official Oracle documentation. It will cover all important aspects of a data warehouse while giving the necessary examples to make the reading a lively experience.”

Maximize Oracle Exadata Capabilities Leverage all of the powerful features available in the Oracle Exadata Database Machine using the proven techniques inside this Oracle Press guide. Written by Oracle experts, Achieving Extreme Performance with Oracle Exadata shows you how to take full advantage of this complete, optimized package of software, servers, and storage. Best practices for enterprise deployments, high availability, administration, backup and recovery, data warehousing, online transaction processing, consolidation, and migration are included in this authoritative resource. Take advantage of the tightly integrated hardware and software in the Oracle Exadata Database Machine Work with Oracle Exadata software features, including Smart Scans, Oracle Exadata Hybrid Columnar Compression, storage indexes, Oracle Exadata Smart Flash Cache, and I/O Resource Manager Understand Oracle Exadata Database Machine balanced hardware architecture Architect, administer, and monitor Oracle Exadata Storage Servers Deploy data warehouses on the Oracle Exadata Database Machine Run online transaction processing (OLTP) workloads on the Oracle Exadata Database Machine Consolidate databases with and migrate databases to the Oracle Exadata Database Machine

Best practices and invaluable advice from world-renowned data warehouse experts In this book, leading data warehouse experts from the Kimball Group share best practices for using the upcoming "Business Intelligence release" of SQL Server, referred to as SQL Server 2008 R2. In this new edition, the authors explain how SQL Server 2008 R2 provides a collection of powerful new tools that extend the power of its BI toolset to Excel and SharePoint users and they show how to use SQL Server to build a successful data warehouse that supports the business intelligence requirements that are common to most organizations. Covering the complete suite of data warehousing and BI tools that are part of SQL Server 2008 R2, as well as Microsoft Office, the authors walk you through a full project lifecycle, including design, development, deployment and maintenance. Features more than 50 percent new and revised material that covers the rich new feature set of the SQL Server 2008 R2 release, as well as the Office 2010 release Includes brand new content that focuses on PowerPivot for Excel and SharePoint, Master Data Services, and discusses updated capabilities of SQL Server Analysis, Integration, and Reporting Services Shares detailed case examples that clearly illustrate how to best apply the techniques described in the book The accompanying Web site contains all code samples as well as the sample database used throughout the case studies The Microsoft Data Warehouse Toolkit, Second Edition provides you with the knowledge of how and when to use BI tools such as Analysis Services and Integration Services to accomplish your most essential data warehousing tasks.

This book is about using business intelligence as a management information system for supporting managerial decision making. It concentrates primarily on practical business issues and demonstrates how to apply data warehousing and data analytics to support business decision making. This book progresses through a logical sequence, starting with data model infrastructure, then data preparation, followed by data analysis, integration, knowledge discovery, and finally the actual use of discovered knowledge. All examples are based on the most recent achievements in business intelligence. Finally this book outlines an overview of a methodology that takes into account the complexity of developing applications in an integrated business intelligence environment. This book is written for managers, business consultants, and undergraduate and postgraduates students in business administration.

Making Data Integration Work: How to Systematically Reduce Cost, Improve Quality, and Enhance Effectiveness Today’s enterprises are investing massive resources in data integration. Many possess thousands of point-to-point data integration applications that are costly, undocumented, and difficult to maintain. Data integration now accounts for a major part of the expense and risk of typical data warehousing and business intelligence projects--and, as businesses increasingly rely on analytics, the need for a blueprint for data integration is increasing now more than ever. This book presents the solution: a clear, consistent approach to defining, designing, and building data integration components to reduce cost, simplify management, enhance quality, and improve effectiveness. Leading IBM data management expert Tony Giordano brings together best practices for architecture, design, and methodology, and shows how to do the disciplined work of getting data integration right. Mr. Giordano begins with an overview of the “patterns” of data integration, showing how to build blueprints that smoothly handle both operational and analytic data integration. Next, he walks through the entire project lifecycle, explaining each phase, activity, task, and deliverable through a complete case study. Finally, he shows how to integrate data integration with other information management disciplines, from data governance to metadata. The book’s appendices bring together key principles, detailed models, and a complete data integration glossary. Coverage includes Implementing repeatable, efficient, and well-documented processes for integrating data Lowering costs and improving quality by eliminating unnecessary or duplicative data integrations Managing the high levels of complexity associated with integrating business and technical data Using intuitive graphical design techniques for more effective process and data integration modeling Building end-to-end data integration applications that bring together many complex data sources

This book examines decision making in general, the translation of knowledge about decision making into a DSS model, and the actual programming of a DSS. In addition, it combines the theoretical underpinnings of the topic with practical application using tools and technology currently available. Topics are discussed on three levels: general theory, implications for DSS design, and code development. This approach provides readers with practical examples than can be adopted into systems design. The Second Edition has been completely updated to reflect new technologies as well as the demands upon technology that have evolved since the publication of the First Edition in 1996. The book utilizes a combination of Dreamweaver and Cold Fusion, which are both popular software products that follow industry standards. (The First Edition utilized Level 5 Object, but all references to the software have been removed as it is not deemed a viable tool any longer.) In light of the numerous advances in the field of DSS over the years, there are many topics throughout the book that have updated and revised. For example, data warehousing has increased substantially in importance since the First Edition, and this section has been completely revised. The topic of business intelligence has been added, and similarly, data mining coverage has been increased via additional discussion and examples. In addition, transnational corporations have become more prevalent and are addressed accordingly.

Master the Combined Analysis Tools in Oracle CRM on Demand Drive better decision-making across your enterprise using the reporting and analysis techniques in this Oracle Press guide. Through clear explanations and detailed case studies, Oracle CRM on Demand Combined Analyses shows you how to deliver real-time insightful business intelligence to end users. Learn how to perform multiple queries, join tables, format result columns, and add interactivity to your reports. Methods for filtering the results of a combined analysis are also covered in this practical resource. Create, edit, and join reports with set operators in Oracle Answers On Demand Configure roles and privileges to allow access to development tools Use negative reporting methods to compensate for null data Analyze records from the transactional databases and data warehouse in federated reports Add advanced views such as gauges, view selectors, funnel charts, and narrative views to your combined reports Integrate ad hoc analysis using Oracle Answers on Demand Consolidate information from disparate sources with pivot tables Perform calculations across multiple reports using result columns

Tips, techniques, and trends on harnessing dashboard technology to optimize business performance In Performance Dashboards, Second Edition, author Wayne Eckerson explains what dashboards are, where they can be used, and why they are important to measuring and managing performance. As Director of Research for The Data Warehousing Institute, a worldwide association of business intelligence professionals, Eckerson interviewed dozens of organizations that have built various types of performance dashboards in different industries and lines of business. Their practical insights explore how you can effectively turbo-charge performance–management initiatives with dashboard technology. Includes all-new case studies, industry research, news chapters on "Architecting Performance Dashboards" and "Launching and Managing the Project" and updated information on designing KPIs, designing dashboard displays, integrating dashboards, and types of dashboards. Provides a solid foundation for understanding performance dashboards, business intelligence, and performance management Addresses the next generation of performance dashboards, such as Mashboards and Visual Discovery tools, and including new techniques for designing dashboards and developing key performance indicators Offers guidance on how to incorporate predictive analytics, what-if modeling, collaboration, and advanced visualization techniques This updated book, which is 75% rewritten, provides a foundation for understanding performance dashboards, business intelligence, and performance management to optimize performance and accelerate results.

Discover how Apache Hadoop can unleash the power of your data. This comprehensive resource shows you how to build and maintain reliable, scalable, distributed systems with the Hadoop framework -- an open source implementation of MapReduce, the algorithm on which Google built its empire. Programmers will find details for analyzing datasets of any size, and administrators will learn how to set up and run Hadoop clusters. This revised edition covers recent changes to Hadoop, including new features such as Hive, Sqoop, and Avro. It also provides illuminating case studies that illustrate how Hadoop is used to solve specific problems. Looking to get the most out of your data? This is your book. Use the Hadoop Distributed File System (HDFS) for storing large datasets, then run distributed computations over those datasets with MapReduce Become familiar with Hadoop’s data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase, Hadoop’s database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems "Now you have the opportunity to learn about Hadoop from a master -- not only of the technology, but also of common sense and plain talk." --Doug Cutting, Cloudera

A complete guide to Pentaho Kettle, the Pentaho Data lntegration toolset for ETL This practical book is a complete guide to installing, configuring, and managing Pentaho Kettle. If you're a database administrator or developer, you'll first get up to speed on Kettle basics and how to apply Kettle to create ETL solutions—before progressing to specialized concepts such as clustering, extensibility, and data vault models. Learn how to design and build every phase of an ETL solution. Shows developers and database administrators how to use the open-source Pentaho Kettle for enterprise-level ETL processes (Extracting, Transforming, and Loading data) Assumes no prior knowledge of Kettle or ETL, and brings beginners thoroughly up to speed at their own pace Explains how to get Kettle solutions up and running, then follows the 34 ETL subsystems model, as created by the Kimball Group, to explore the entire ETL lifecycle, including all aspects of data warehousing with Kettle Goes beyond routine tasks to explore how to extend Kettle and scale Kettle solutions using a distributed "cloud" Get the most out of Pentaho Kettle and your data warehousing with this detailed guide—from simple single table data migration to complex multisystem clustered data integration tasks.

Database Modeling and Design, Fourth Edition, the extensively revised edition of the classic logical database design reference, explains how you can model and design your database application in consideration of new technology or new business needs. It is an ideal text for a stand-alone data management course focused on logical database design, or a supplement to an introductory text for introductory database management. This book features clear explanations, lots of terrific examples and an illustrative case, and practical advice, with design rules that are applicable to any SQL-based system. The common examples are based on real-life experiences and have been thoroughly class-tested. The text takes a detailed look at the Unified Modeling Language (UML-2) as well as the entity-relationship (ER) approach for data requirements specification and conceptual modeling - complemented with examples for both approaches. It also discusses the use of data modeling concepts in logical database design; the transformation of the conceptual model to the relational model and to SQL syntax; the fundamentals of database normalization through the fifth normal form; and the major issues in business intelligence such as data warehousing, OLAP for decision support systems, and data mining. There are examples for how to use the most popular CASE tools to handle complex data modeling problems, along with exercises that test understanding of all material, plus solutions for many exercises. Lecture notes and a solutions manual are also available. This edition will appeal to professional data modelers and database design professionals, including database application designers, and database administrators (DBAs); new/novice data management professionals, such as those working on object oriented database design; and students in second courses in database focusing on design.+ a detailed look at the Unified Modeling Language (UML-2) as well as the entity-relationship (ER) approach for data requirements specification and conceptual modeling--with examples throughout the book in both approaches! + the details and examples of how to use data modeling concepts in logical database design, and the transformation of the conceptual model to the relational model and to SQL syntax; + the fundamentals of database normalization through the fifth normal form; + practical coverage of the major issues in business intelligence--data warehousing, OLAP for decision support systems, and data mining; + examples for how to use the most popular CASE tools to handle complex data modeling problems. + Exercises that test understanding of all material, plus solutions for many exercises.

Business Metadata: Capturing Enterprise Knowledge is the first book that helps businesses capture corporate (human) knowledge and unstructured data, and offer solutions for codifying it for use in IT and management. Written by Bill Inmon, one of the fathers of the data warehouse and well-known author, the book is filled with war stories, examples, and cases from current projects. It includes a complete metadata acquisition methodology and project plan to guide readers every step of the way, and sample unstructured metadata for use in self-testing and developing skills. This book is recommended for IT professionals, including those in consulting, working on systems that will deliver better knowledge management capability. This includes people in these positions: data architects, data analysts, SOA architects, metadata analysts, repository (metadata data warehouse) managers as well as vendors that have a metadata component as part of their systems or tools. First book that helps businesses capture corporate (human) knowledge and unstructured data, and offer solutions for codifying it for use in IT and management Written by Bill Inmon, one of the fathers of the data warehouse and well-known author, and filled with war stories, examples, and cases from current projects Very practical, includes a complete metadata acquisition methodology and project plan to guide readers every step of the way Includes sample unstructured metadata for use in self-testing and developing skills