Monday, 16 July 2012

Data Modeling Made Simple with CA ERwin Data Modeler r8

CA Erwin DataModeler r8 simple business data modeling concepts or computer modeling of operational data and have sufficient knowledge of best practice has been to provide a professional and how to apply these principles, r8 CA Erwin Data Modeler. CA Erwin Data Modeler with before and after control of the more advanced features, based on the book, many along the path of CA Erwin data model we build. This book is a real world experience and the earth, humor, and even cartoons to help you master the following ten goals to help assemble best practices with Down syndrome:
  1. The basic concepts of data modeling and relational theory, and how to apply these skills through CA Erwin Data Modeler
  2. When reading a book with the same confidence in any size and complexity of a data model Read
  3. Conceptual models, logical and physical layers, and how CA Erwin data modeler’s architecture designs to build these models to understand the difference between
  4. Techniques both top-down and bottom-up design, and vice versa for the engineering front and rear, and physics to effectively implement a design to convert a logical data model
  5. Naming standards, the new domain and create, CA Erwin Data Modeler and UDPS, templates and models to increase the company's quality and consistency of data, increasing to reduce the modeling time
  6. Form modeling techniques and design, reporting and exchange of Meta data model that uses a variety of information sharing with the public
  7. To create a workflow that meets your personal needs r8 CA Erwin Data Modeler, use the customization features, the new work area
  8. Communications metadata and import / export with Microsoft Excel for bulk editing r8 CA ERwin Data Modeler updated to take advantage of new features
  9. Fill Compare features CA Erwin data modelers and model comparison and merge changes
  10. Themes, plots, themes, screensavers and much more through the use of their data models and optimize the layout of the organization
Part I provides an overview of data modeling: what is needed and why. CA Erwin Data Modeler is a basic simple functionality, introduced by a set of easy to follow.

Part II entities, relationships, keys, and provides the basic components of a data model that contains more. -Using the examples of how CA Erwin Data Modeler, these building blocks and scenarios "real world" context is given for each.

Hotels with the creation of new standards in Section III, and the importance of the organization. CA Erwin data modeling as a standard, such as UDPS creates a domain-specific properties such as the creation of this section to share with the creation of models, CA Erwin data modeling examples of these standards include a step by step how to create end-user through standard reports and queries.

Section IV, conceptual models, logical and physical data, discusses, and CA Erwin architecture design layer, to show the relationships between these models using CA Erwin Data Modeler provides a complete case study. Building real-world examples of conceptual data models, logical and physical r8 CA Erwin Data Modeler and tedious details, hands, working with commercial sponsors, gathering requirements is provided.

Tom Bilcze, CA Community Technology user modeling world from the preface of the President

R8 CA Erwin Data Modeler Data modeling is an excellent resource for the community is made simple with Erwin. With liberal use of images, data, graphics data models inexperienced Modeler to create the components and how they went R8 CA Erwin. As an experienced data modeler, Steve and Donna is my art form of life to make me a new and better r8 gives a guide to effective use.

About the Author

About Donna

Donna Burbank has a unique perspective in the field of data modeling - and the main tools to help design and market modeling metadata now have a variety of products, and spent many years in as a consultant to implement these solutions. As a consultant, worked with Global 2000 companies worldwide and as a software provider, Platinum Technology, Embarcadero Technologies, CA Technologies and Development efforts have been effective. Currently, senior director of product marketing for CA technologies.

About Steve

Steve Hoberman practice data modeling instructor in the world. Steve serious time and construction of software systems with the realities of budget and human limitations, data modeling and precision balances in form. Consultation and training with minimal investment in fruit models data modeling tools, and focuses on the principles. Taught his first class in 1992, data modeling and data modeling and business intelligence since then over 10,000 people trained. Steve data modeling, design of data model challenges the group's founder and Scorecard, Â ® inventor of the author of five books.

Tuesday, 26 June 2012

Data Modeling in SAP NetWeaver BW 7.1

This book (in detail) explains the concept of development and implementation of SAP data model. It is only a model that meets the needs of the company's existing reporting and analysis, providing a solid data model is essentially related to the coverage of all concepts and offers practical technologies, and that of the model is constructed to allow business growth and adapting to changing needs and requirements. Future development and maintenance of the data model, while this book is a roadmap for SAP NetWeaver BW 7.1 and SAP BusinessObjects provides date of coverage.

Monday, 14 May 2012

Distributed Data Warehousing Using Web Technology

How to Build a More Cost-Effective and Flexible Warehouse
A "data warehouse" is? This is a structured database to support business decision making. A data warehouse, organizes, analyze and synthesize large amounts of raw data - this is understandable and useful to employees. Until recently, all data stored in central storage means monolithic. It was difficult to manage and maintain costly and slow to operate.

Internet technology has changed all that forever! This profound book, administrators and professionals in information technology to configure and use distributed data warehouses have a clear picture of the eyes - more than one computer (via Internet technology to the network) to use for storage of access and data necessary için. Kitap takes a look at:
  • Functions and benefits that are needed to establish a distributed data store
  • This type of functions and data, web information technology-enabled, object technology as residential complex technical issues, and much more
  • What you can offer a complete range of data warehousing - and how to exploit
  • Submit to create a data warehouse and how to justify a business case.

Tuesday, 24 April 2012

The Data Model Resource Book, Vol. 1: A Library of Universal Data Models for All Enterprises

Basic functions of the trade to create the database fast and reliable proven

This database is designed for basic business functions provided in a simple and inexpensive, because industry experts, the book was first published in March 1997 raved about the resources of the data model. To draw attention to more specific requirements of different companies, while adding a companion volume Len Silverston, revised and updated in the first edition a great success. Each unit comes with a CD-ROM, sold separately. Each database on CD-ROM and the need for companies and individuals will receive a portion of the cost of development time that you allow a third party, electronic address book is a ready to use templates to design offers a powerful way to build from scratch.

Updated data models in the first edition of the CD-ROM, the developers of the source databases to quickly install a basic set of data models to support a wide range of business functions and allows you to changing.

(Computer Shopper February 2002): "I thought you were well thought out and well explained in the models of books"

Say

"Data Model Resource Book, Revised Edition, Volume 1, I'm a data architecture, data architecture (Zachman Framework row one or two) is not limited to managing a high level of the best books ever seen;? . This is a common, industry-specific logic models and can be customized to meet the needs of providing data and drawings. Finally, in a model with a frame whose upper levels and below includes a rich high-level logic designs reservoir models, and SQL programs, including data architecture schemes stars. Models as a starting point for your model or data models, drawings and use scripts to check existing models and a reference to the company that will help create data architecture, the entry may not be familiar topics. Book offers several models of different levels and techniques of conversion tips and techniques to achieve appropriate levels of abstraction models. Sample tables (eg data) allow the modeling of life. I use the last twenty years and numerous projects in the year of the first edition gramlayabilir? Is a valuable resource for me? "
- Van Scott, Sonata Consulting, Inc. President

"Len Silverston typical areas of the company in question for various industries for a wide range of generic data models and a very useful summary of the volume of two (but not too generic) at one point was in all probability find a modeler Data. Clearly, well organized, written, and most of a company some of the information needs of perverse and difficult matter drops below this race is clearly a valuable resource for any assignment of one before entering a modeling shoot. Here if we did not find any evidence of a pattern very similar to the face can be used for almost any situation. "
- William G. Smith, President, William G. Smith & Associates

"In today's fast targeted e-world, it can be difficult to change the data structures is no longer acceptable to bury business constraints. Architects data and data architecture to capture the complex requirements need reformat the unpredictable vision models futures. Len novice and advanced data models to provide a flexible data provides an excellent starting point for the architects. These models position an organization for the company, old rules. Successful implementation and customization, and business enterprise management to reflect the principles and rules of the organization to transform itself provides proactive. Thus, models based on data architecture, Len and procedures, customizing them, work become the basis of design changes. "
- Barbara von Halle, founder of Knowledge Partners, Inc., co-author of the manual database design relational

"This book is a universal long and a must for any company implementing data models. Includes universal models of data and models to apply the skills and can help all companies regardless of their level of experience. Better meet the needs of many books, data models, but little in the way of practical advice offered. These books fill this gap and should be used by all companies. "
- Ron Powell, Publisher, DM Review

"Computer services companies worldwide require quality systems, built faster. This book, or even weeks before a program, the day to expand and form the basis of standards for data modelers can break the project. I LL Bean, Inc., a valuable resource for my modeling effort data collection resource model, a revised edition, Volume 1 found, and I think it is an important part of any vehicle modelers. "
- Susan T. Oliver, enterprise data architects, LL Bean, Inc.

I did not believe in saying the company is essentially the same for all companies looking for a data model of the company were hired by a company, "When I introduced three years ago, the model data source. Is a way I felt after a little analysis with Len Silverston using, we actually had the same little difference: customers, accounts, employees, benefits, and had everything you need to do in any organization, and we're all Len book has been adapted to the product component of a larger framework of all data were ready to move forward command to create a CD-ROM accompanies the book ensures that the files very quickly, the Oracle model. Then began to draw the map of all types of detailed data on the business model, and here we account number for all these different spellings and typographical errors could not find a place.

Volume 2 provides the best features of this new edition: industry specific data models. I began to see interesting designs to penetrate this volume. For example, an airline reservation, the reservation if you are a restaurant or hotel. (In fact, we have something like the oil industry -. Allowance)

Another concept of the book has changed my thinking and word by word "party". Recently, a computer online at the same time employees has a project that could function as a client and the user. Team had a disagreement with a name for this entity, but after reviewing the reference manual data model, I realized that we are a party of three documents.

Your job is to implement a data warehouse project or borrow ideas get any item to the next operational database, I also book models of data sources, revised edition, volumes 1 and 2, the Bible for guidance on the design. "
- Ted Kowalski, Equilon Enterprises LLC, author of Opening Doors: Facilitator's Guide

Friday, 13 April 2012

Mastering Data Warehouse Aggregates: Solutions for Star Schema Performance

Definition
  • The selection and design, the load from a star schema aggregates used in dimensional modeling of the first book to provide in-depth coverage and use for specific tasks and the results of demonstration projects
  • Global navigation and basic design principles of a global and covers the advantages and disadvantages of different types of business solutions
  • This development projects data storage throughout, including the growing importance of explaining development, first creates and loads the data from the iterative

Back cover

The first book that offers in-depth coverage of the star maps overview

As the most effective method for maximizing star schema performance Dubbed by Ralph Kimball aggregates of dimensions more spectacular than any other technology is a powerful and effective tool to accelerate data warehouse queries. Well structured and implemented a database after verifying that it was built, the overall performance of data storage must begin with the measures taken.

However, many companies solve performance problems, rather than turn to aggregate custom hardware and proprietary software products to ignore. This book fills a gap in knowledge has led companies to costly and risky.

A series of well-planned data warehouse expert Chris Adamson overall have a significant effect on overall performance indicates that the data store. A role in avoiding common pitfalls, or whatever the current level of star schema information, best practices in this book, we will help you get an incredible performance increase.

Collection techniques have progressed from the database schema stars, tables, and the impact of the life cycle of this book covers the entire data storage. The approach of design data, including the warehouse star schema, after establishing some key areas, the articles on shelf-life data of the main phases. Topics are:
  • The basic design principles of the global schema
  • With or without the addition of a browser, how aggregate is used in a production environment
  • Integration with ETL processing a total
  • The standard tasks of development projects and data storage products that contain additives
  • How overall existing star schema adds the ability to organize and execute a project
  • The aggregation of bridge tables, stars such heterogeneous models or the instantaneous impact and plans advanced design
  • Incorporate three-dimensional aggregates with life the views or IBM Oracle Implementation of special considerations query the tables
  • How comprehensive, including security database and archiving strategy can add value in other areas

Wiley Publishing Technology timely. Practice. Reliable.

Www.wiley.com / compbooks / visit our website at

About the Author

Christopher Adamson, data storage consultant and founder of Oakton Software LLC. Directed and implemented a variety of industries, applications star schema data warehouse, an expert in the design. Its clients Fortune 500 companies, small and large businesses, government agencies and providers of data storage devices, we have included. Dimensional Modeling and Data Warehouse Design Solutions Adamson also (also from Wiley) teaches author. O, on its website, can be reached through www.ChrisAdamson.net.

Friday, 6 April 2012

Pentaho Solutions: Business Intelligence and Data Warehousing with Pentaho and MySQL

Pentaho Business Intelligence and Data Warehousing with MySQL for a resource all-in-one for use in

Part of the cost of proprietary solutions Pentaho open source business intelligence (BI) and data warehousing solutions. Now, the benefits of Pentaho for your business in this practical guide written by the need for the two main actors in the community can take.

The book covers all components of the Pentaho BI suite. You Pentaho installation, operation and maintenance of BI and Pentaho concepts to learn and take on the back of ever fully find a lot of discussion.
  • Of all the products available open source BI, Pentaho open source product, the most comprehensive set of tools that offer the fastest growing group and a
  • Creating and data integration / ETL Pentaho Kettle for a data warehouse with a load by hand using a direct SQL queries JFree (Pentaho Reporting Services) to create services and generate reports Pentaho Mondrian (analysis) is a module Additional browser cubes and explain the Cube JPivot
  • To provide end users of BI solutions, distribution reports, cubes and examine meta Pentaho platform
  • The timetable shows how to configure automated underwriting and distribution

Companion Website, sample source code, sample data, and provides links to related resources.


Back cover

The only source of open source BI and data warehousing solutions

The cost of a custom solution for you Pentaho BI data warehouses, and part of the rich and powerful application that lets you create full-featured, open source suite. While learning the concepts and architecture of Pentaho This book from the beginning, for example, reports, dashboards and OLAP PivotTables and operation, can start with Pentaho minutes. Using a case study, how-dimensional modeling and learn what it is to implement a data warehouse design. You can create and populate the data warehouse with data integration tools will Pentaho. Finally, Pentaho reporting, analysis, dashboards and data mining tools on top of using the data warehouse will learn to create their own BI applications.
  • Understand the important concepts and action sequences Pentaho solutions, including tanks,
  • Apply the key concepts of dimensional modeling and star schemas in a data warehouse using
  • Use ETL Pentaho Data Integration for construction applications
  • Explore the advanced features, such as PDI Remote Execution and the consolidation
  • Pentaho Report Designer to design and implement together with the reports and graphs
  • Enjoy it and Pentaho Analysis Services OLAP / pivot tables in addition to creating an interactive drill
  • Panels with a content focused and compact BI for business users
  • Explore and discover data models with Pentaho Data Mining

About the Author

Roland Bouman technology open source web application developer, database development and business intelligence. He is an active member of society, and MySQL and Pentaho can follow.

Jos van Dongen is an author of Business Intelligence professional and well-known and experienced server. He regularly gives lectures and seminars.

Thursday, 29 March 2012

Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture

Make data integration: How to systematically reduce costs, improve quality and efficiency

Today, companies are investing considerable resources in data integration. Many data integration peer-to-point, thousands of undocumented expensive and difficult to maintain. Data integration is no longer a classical data warehouse and business intelligence projects, a significant cost and risk - companies increasingly rely on analytic, and the need for plan data integration is increasing more than ever.

Reduce costs, simplify management, and improve the quality and effectiveness of the identification, design and construction of components for the clear and consistent approach to data integration: This book offers a solution. Eminent specialist IBM Data Management with Tony Giordano architecture, design and methodology, best practices, and I'm disciplined work to get the right shows how the integration of data.

Mr. Giordano is a smooth integration of operational and analytical data and the integration of administrative data to create models to show how the "model" begins with an explanation. After each phase, activity, task, and delivered through a full case study, explaining Walk along the life cycle of the project. Finally, knowledge management with other disciplines how to integrate metadata and integrated data management. Annexed to the book, but the basic principles, detailed models and data integration provides a comprehensive dictionary.

Included in the coverage
  • The implementation of efficient processes and a well documented reproducible data integration
  • Integration costs and improves quality by eliminating unnecessary or duplicate data
  • High complexity, associated with data integration of business management and technical
  • Integration of process models and data in a more efficient use of graphic design, intuitive techniques
  • Meet the many complex data sources to the end of construction at the end of data integration applications

About the Author

Anthony Giordano partner of IBM Business Analytics and Optimization consulting and service company is currently online information management, data modeling, data integration, data management and data management, conduit. His areas of business intelligence storage, data and information management focusing on information technology have over 20 years experience in the field. In his spare time, he with several local universities, undergraduate and graduate students trained in data warehousing and project management.

Tuesday, 20 March 2012

Data Analysis Using SQL and Excel

Knowledge into effective action is required for business analysis tools. This book and business information extracted from relational databases to store data to identify aspects of business transactions and offer customers more to use it to help you use SQL and Excel. When and why do the design and analysis using SQL and Excel to obtain useful results, and results should be similar to how the company to perform some type of analysis are described in each chapter.

Back cover

Harness the power of SQL and Excel to perform business analysis

Three major efforts are required for efficient conversion of knowledge to action: Import data from Excel data with SQL, the presentation and understanding of statistics as the basis for data analysis. Data mining expert Gordon Linoff focuses on these issues, SQL and shows you how to use Excel to extract business information from relational databases. Start taking a look at the amount of data, customers, products and markets is central to the task of understanding the dimensions of business relationships to customers and then the store will show you how to use these data to identify and summarize important data to produce results. On the way, it aims to improve understanding of why some things work and others' stories based on personal experience in the field, to share.

When and why to design and how to perform the analysis using SQL and Excel to obtain useful results and outcomes for what they can expect to look like some type of business to conduct the analysis described in each section. Throughout the book, the essential features of Excel are highlighted, interesting uses of Excel graphics are explained, and processing of data streams and graphical representation of data in SQL Server is used to show you how.

SQL and Excel, SQL, and advice to share data analysis / mining on the Excel Data Analysis Using Alerts and technical asides. The book discusses:
  • How to describe the structure of an entity-relationship diagrams, data
  • Ways to use SQL to create SQL queries
  • This means, as the descriptive statistics and chi-square p-values
  • How to analyze data, including geographic information
  • The basic ideas of risk and the probability of survival
  • Data structures, how to summarize what he looks like a client at some point in
  • Several variants of linear regression
  • Companion Website, data sets, Excel spreadsheets and provides examples in the book.

About the Author

Gordon S. Linoff data miners, Inc., a consulting firm specializing in data mining is one of the founders. Data mining techniques that bestseller, Second Edition, and Mastering Data Mining (Wiley both) is co-author. This, customer relations, marketing and managing the implementation of data mining techniques to business problems that have more than a decade.

Wednesday, 14 March 2012

Oracle Data Warehousing and Business Intelligence Solutions

On the Oracle database and business intelligence tools, comprehensive coverage

Written by a team familiar with Oracle, the authoritarian end of the book, as well as coverage of the platform for Oracle Business Intelligence data storage tools. You offer a complete range of Oracle somuremiyorlar and learn how these features can be used to provide solutions to a variety of needs and requirements. Furthermore, the authors of their applications on the basis of real world experience and get advice and valuable information. Avoid many common pitfalls while learning best practices for:
  • The Oracle technologies, data warehousing, design, build and manage your savings
  • The integration of custom database and business intelligence solutions from other vendors
  • Marketing, sales and more new set of tools to analyze the data using Oracle Business Intelligence
  • The typical operation of the management challenges of data storage
  • To explore initiatives in the business, security business promoter, risk management and project team

About the Author

Vice President Robert Stackowiak Oracle Business Intelligence Unit, Business Technology. O, Oracle, IBM, Harris Corporation, and intelligence for U.S. firms Army, data warehousing and Corps of Engineers has worked for over 20 years of related functions. His work on intelligence technologies and business information and software, magazines, publications, databases and Data Warehousing Institute, appeared in publications as President and CEO of trends and applications. Furthermore, the authors of the book Oracle Essentials: Oracle Database 10g (now the third edition, February 2004, O'Reilly), Oracle Application Server 10g Essentials (first edition, August 2004, O'Reilly) and Professional Oracle Programming (first edition, June 2005, Wrox).

Joseph Rayman financial services, manufacturing, telecommunications, retail health care, and a wide range of industries, including the federal government over 20 years of business experience in North America leads the Oracle Business Intelligence Consulting practice. Technical and commercial leadership in the design of enterprise architecture, data applications for quality assurance, enterprise data modeling, VLDB fixing systems, data warehouse design, data mining and warehouse covering activities. Joe the definition and methodology to create the Oracle Data Warehouse Consulting is an important factor. Before joining Oracle, Joe designing and implementing business intelligence solutions, for a statistical analysis for a food manufacturer and a major international financial institution to discuss and analyze real-time solutions.

Rick Greenwald Oracle, Gupta Technologies, Cognos, and the general data, including the IT field for 20 years worked for major suppliers. Oracle Database 10g (now the third edition, February 2004, O'Reilly), Oracle Application Server 10g Essentials (first edition, August: It is more than a dozen books, including Oracle Essentials, co-wrote in 2004, O'Reilly) and the Professional Oracle Programming (first edition, June 2005, Wrox). Mr. Greenwald now works for Ingres Corporation.

Sunday, 11 March 2012

Data Warehousing, Data Mining, and OLAP (Data Warehousing/Data Management)

This reference, three visions for managing information technology strategy, provides the theory and practice: data mining, warehousing, online analytical processing (OLAP) and data. Factory Information: The information technology of the distribution system to work together shows how to create a new class. The book includes patterns and indexing techniques, and discusses the development of applications using OLAP tools. Alex Berson author of "client / server" and co-writer (George Anderson) and "Computer and Sybase Client / Server" "database client / server, Sybase and Design" is.

Back cover

Optimize the distribution system to organize data! Today's business environment is a priority to improve presentation of data in the field of computing. This comprehensive guide and higher effective data mining and how strong is to integrate other data storage technologies can help to illustrate. You will learn: data storage (SMP and MPP parallel to assess the various solutions, including systems, online analytical processing (OLAP) is a competitive advantage by leveraging business problems faster, use the databases for establish a system for managing data storage, metadata, OLAP, etc..) through the Internet, the use of leverage data warehousing, client / server, and various data mining tools. 

And a detailed description of available data storage technologies and provide strategic analysis, databases, books, data warehousing, star schema and approaches snowflake, multidimensional models as a practical guide for the design and mutirelational, advanced indexing and data mining. Also, learn to compare different technologies and data mining products and how they fit into your overall business processes and understand the data. HIPS and is designed for strategic planners, this fascinating book, standards, tools, technologies and data storage capacity can be relied upon as a basic reference for today.

Tuesday, 6 March 2012

MASTER DATA MANAGEMENT AND DATA GOVERNANCE, 2/E

Customer-focused technology company to create an environment

"The authors noted that MDM is a complex space and multi-dimensional and provide practical advice for the proper implementation of MDM for everyone in sufficient detail to cover all these dimensions proposed. It really stimulates the longest book that the authors of a comprehensive treatment of MDM, so that previous studies, missing "-. Malcolm Chisholm, Ph.D., President, AskGet.com Consulting, Inc.

The data control again, and this authoritative guide for head teachers is also included in the data of the company to maintain detailed information. Master Data Management and Data Management, Second Edition, the current architecture and system development and management methods and technology vision coverage provides up to date. , MDM Business Case and create a roadmap to create accurate models, data centers, to implement and learn to implement security policies in layers. Older systems, the cross-industry, this comprehensive volume also includes the integration and adaptation challenges.
  • Plan and implement at the level of MDM and data governance solutions
  • Improve the model data
  • Define the match and the records of active links executives from different regions with a resolution of
  • Improved efficiency and integration of SOA and Web services to maximize
  • Local, state, federal and international regulations to ensure compliance
  • On authentication, authorization, roles, rights and security by using encryption Manage
  • Protect yourself against identity theft, data compromise, and spyware and worm attacks
  • Components and the test data synchronization quality and system performance.

About the Author

Alex Berson, thought actually an internationally recognized expert in information management, information security, advanced databases, SOA, CRM, data warehousing, mobile computing and leaders in the fields, the writer and consultant treatment, complex financial services, manufacturing, innovative solutions to the pharmaceutical and technology focuses on the establishment.

Dr. Larry Dubov recognized scientific, professional, and expert and I thought the company products and financial services, banking, telecommunications, pharmaceuticals and vertical drive of the implementation of technology solutions leader complex. Its main objective MDM, Master Data Management, CRM, data warehouses, operational data stores and that the SOA.

Friday, 2 March 2012

Data Warehousing: Architecture and Implementation

This book offers what you need most too each participant's data warehouse project: a comprehensive overview of current and best solutions to meet their objectives in a reliable, step-by-step in creating stores. Everyone, including a data warehouse initiative answers the fundamental questions raised by. And, with 75 prominent figures which indicated that just tell you how to do business. In practice, migration strategies and scenarios, including 12 major steps on foot. Technical troubleshooting, capacity planning, security and support, including management and support for the examination of important issues. Explore the techniques of art design and development programs in the state of Meta. The best hardware, software and platforms to choose - and as a data warehouse to develop new technologies mature. The Metadata Exchange Standard Preview and Web solutions in the futur.Enterprise Computing Institute Series section.

From the Inside

Foreword

This book, information technology (IT) is to hear, or data storage technologies, has been commissioned to assess the learning and applying. Far from being a fad, even if the subject of data storage technology, products, suppliers, organizations, and yes, the book shows an increase in the number, size and reputation has grown in recent years. Companies successfully implemented data warehouses, strategic, and often wonder how they ever survived without it in the past. Already in 1995, Fortune 500 Gartner Research, IT managers, all organizations planning to implement the data warehouse in 1998 revealed that 90 per cent. Almost all of the top-100 in the U.S. in 1998, Using a data warehouse based on the profitability of the asset. In about 30 percent of companies in the technology, create a plan to protect, promote and implement a data warehouse continues to support a permanent unit or semi-permanent. If you are a computer professional who was responsible for planning, managing, designing, organizing the data warehouse implementation, support or maintenance, then this book is for you. In the first part of enterprise architecture and data warehousing concepts, is presented as a reason for writing this book. The project proponent, the IOC and the Project Manager: This is the second part of the book in any initiative of the data warehouse focuses on three key people. This section is divided into the major concerns of these people. 

The third section presents a data warehouse and store designs and implementation for developers, for the first time will be extremely helpful in providing advice to both the experience. The fourth section of this book focuses on the management of data storage technology. If you can use to create components of data warehouse technology lends itself to a series of vertigineux.Ce book also includes a CD-ROM contains two software products. For any last minute changes and updates, see the readme.txt on the CD-ROM. Software included in the following: R / olapXL - R / olapXL dimensions users the data warehouse to any workstation or to obtain data directly from Microsoft Excel spreadsheet is a powerful query and reporting tool that allows data to an ODBC-compliant database.

When data from Microsoft Excel, analyze, report, or one of the standard features of Excel charts are free to use the data. Designer Depot - Warehouse Designer dimensional data warehouse and data mart is a tool to generate DDL to create tables. Specify the data structure required by a graphical interface for end users. Tool, primary keys, foreign keys, indexes, constraints, and creates states to create structures table.Avant to use software provided, including whether to accept your disk, is a license agreement. The guides are included in both products are added to the book. The latest information on these products URL intranetsys Intranet Business Systems, Inc. is available on the site.

About the Author

Mark Humphries Intranet Business Systems, Inc., the Philippines, President / CEO. O, in Europe, North America and Asia-wide management and consulting with 13 years experience, and to store the two utilities in the United States was the major projects.

Thursday, 1 March 2012

The Microsoft Data Warehouse Toolkit: With SQL Server 2008 R2 and the Microsoft Business Intelligence Toolset

Valuable best practices and expert advice from world-renowned data storage

In this book, from Kimball the best group of leading experts in data storage applications, SQL Server called SQL Server 2008 R2, the next "liberation Business Intelligence," to use. This new edition, writers, SQL Server 2008 R2, Excel and SharePoint users with powerful new tools for the collection and increases the power of BI tools to build a warehouse to show you how to use SQL Server to explain how the data provided to meet the needs of business intelligence that are common to most organizations. R2, SQL Server 2008 data warehouse and BI tools that are part of a complete suite of Microsoft Office, including the design of the authors, development, installation and maintenance, including the project cycle, full life, walk.
  • Equipment with over 50 percent of the new and the new Office 2010 version of SQL Server 2008 R2 and revised to cover the rich feature set
  • Excel and SharePoint, Master Data Services and SQL Server to include new content focusing on Analysis Services, Integration and Information Power Pivot examines the capabilities of the updated
  • Actions to implement the techniques described in the book clearly show how the detailed case studies
  • The accompanying code examples and case studies are used throughout the entire site containing the database

Microsoft Data Warehouse Toolkit, Second Edition, when and how to perform basic tasks of data storage such as Analysis Services and Integration Services provides information on the use of BI tools.
Back cover
To create a data warehouse Learn to use SQL Server 2008 R2

Data warehousing and business intelligence industry that the most effective leaders Kimball Group DW / BI systems design, development and management industry has developed standards of service as pioneer techniques. SQL Server 2008 R2: With this new version of his bestseller, experts in the use of veterans group Kimball catch up with the version of SQL Server Business Intelligence. Data warehouse and BI tools that are part of SQL Server 2008 R2, covering the full set, the authors design, development, implementation and maintenance, including monitoring the lifecycle of the project.

A major update to the previous edition and the new features and content and master data services such as eyes Power Pivot in addition to the functionality of SQL Server 2008 R2, this new version includes detailed examples showing how to apply best available techniques described in the book. The authors, trial, and a system of DW / BI with Microsoft tools can benefit their own challenges and successes gain share of the error of their own experiences. DW / BI lifecycle of the system to build Kimball discover how to use incentives to focus on four main principles: focus on your business, an information infrastructure, buildings and all meaningful increments delivered solution. With these principles in the hands of a successful DW / BI system supports the common needs of business intelligence to build the institutions will be well on your way.

DW / BI Data Warehouse Toolkit, Microsoft, Second Edition shows you how your role in the process of working on a project, no matter what:
  • Concentrate your efforts on best opportunities
  • Choose 2008 R2 and other Microsoft products, you can install and configure the components of SQL Server available
  • A three-dimensional model to design and create a relational database structures and database Analysis Services
  • Establish databases Integration Services ETL system to fill a DW / BI
  • BI applications to deliver value to your organization and create data mining models
  • Manage; maintain the system long-term success, and DW / BI growth
  • Microsoft SQL Server 2008 R2 and all business intelligence tools

DW 2.0: The Architecture for the Next Generation of Data Warehousing (Morgan Kaufman Series in Data Management Systems)

Data warehousing has been around for 20 years and became part of the IT infrastructure. Non-data - data storage for the original information was developed in response to business needs and integrated data, provides granular institutions, and history.

Development paths and stores data in large part to different types of providers of software and hardware, there are many types. But in numerous speeches, articles, and reached its 65,000 professional b-eye Network-months notice, as defined by the author DW 2.0, well identified and defined next generation data storage.

The book takes this theme and the future of data storage and the level of the architecture and the level of technology, says it is now technologically possible. The book was a top-down perspective: looking at the overall architecture and then dive into the issues underlying the components. Building a data warehouse for people who use or see this advantage and can determine what the future: what to buy the new technology, data warehouse, how to plan extensions to warrant expenditure and how you can save the current system - in practice.

This data warehouse professional everything and gives full experience of what it takes to implement a new generation DW 2.0.
  • The first book is a new generation of data warehouse architecture, DW 2.0.
  • "Father of the data warehouse", Bill INMO, a newspaper columnist and editor of Channel INMO the bill written by the Business Intelligence Network.
  • A technology that provides the next generation of vehicles and the overall implementation long delay coverage DW: metadata, temporal data, unstructured data ETL, quality control data.

Tuesday, 28 February 2012

Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing (Agile Software Development Series)

Agile methods, the use of a data warehouse (DW), Business Intelligence (BI), or analysis for the project much more innovation, value and quality can bring. However, traditional methods of Agile carefully DW / BI projects must conform to the unique properties. Agile Analytics, a pioneer Ken Collier shows how agile.

Collier, the oldest operating systems and a variety of commercial law and private offers special joint platform independent solutions for the integration of an agile infrastructure. Using examples of his work, skills development, and how different analyzes to support the rapid growth of large volumes of data and shows how to manage teams. Projects "back end" data management "front end" business analysis, contains, or both Collier provides optimal techniques.

Ben equipment delivery, community agile DW / BI project, the basic practices that determine the path of introducing agile techniques, focusing on project management and coordination.  You can cooperate for the success of the section

The second part of superior design, test DW-oriented development, version control, and automation projects, including the quality of the production value of the company to ensure a continuous delivery provides the technical methods

Collier, an IT decision makers, professional data storage, database administrator, specializing in business intelligence, or if you are a developer of database, now provides proven solutions can be applied. With your help, reduce project risk, improve business compliance, achieve better results and you can have fun along the way.

Say

"This book explains why and how to do Agile Analytics did a great job in the real world. Implementation of Ken and refinement of this approach are many lessons learned. Business Intelligence is an area certainly benefit from this type of discipline."

Zinkgraf Dale, Business Intelligence Architect Sr.

"The evidence of an important aspect of Agile Analytics, agile project management, design applications, the scope of the evolution of self-organizing teams, products and technical control of the management books width and automated management and continuous integration build. They plan an analysis, even if you a flavor of a large data-driven processing issues and products useful to society and will be beyond this general analysis of Ken. "

  • Jim Highsmith, Senior Consultant, Thought Works, Inc. and author of Agile Project Management

"Agile methods of software development have changed and now it's time to convert the scan. Analytics Agile methods of analysis to the next delivery of the project provide the necessary knowledge to perform the conversion."

  • Pramod Sadalage, author of Refactoring Databases: Design of scalable database

"This book is for the next ten years brings together the key strategies for successful business projects intelligence analysis. Ken Collier raised the bar for professional analysis is the challenge?"

Scott Ambler, IBM Rational Methodist president and founder of Lean Agile, Agile Data

"The teams that will help you deliver high-quality presentations in a scan, high value systems, and development of business intelligence software faster and more cost effective than traditional ways of working."

Ralph Hughes, author of Agile Data Warehousing


About the Author

Ken Collier worked with agile methods since 2003, and data warehousing, business intelligence and analysis to create a style with vivid that Google Analytics is an integrated agile methods pioneered. Several agile project teams, DW / BI project manager, technical director and continues to develop these ideas. Collier teams often DW / BI Analytics Agile in trains and Hedw speakers on the subject (Higher Education Data Warehouse), 2011, and some TDWI (The Data Warehousing Institute) was the global conferences. He is founder and KWC Technologies, Inc. President and Business Intelligence applications and consulting areas Cutter Consortium Senior Agile development.

Friday, 24 February 2012

Agile Data Warehousing: Delivering World-Class Business Intelligence Systems Using Scrum and XP

As a consulting firm, fast data storage is valuable information on the subject, especially the very small number of sheep and a book to gather information. This volume of development teams can develop quickly and effectively to create business intelligence applications, Ceregenics, Inc. is distilled from ten years to research. Since the creation and implementation of data warehouses can cost millions, agile data storage registers financial professionals, but also shortens the time and better quality application only. Agile movement in software engineering "to maximize the job done," produced for interesting news. 

In general, however, the movement of data management, agile systems of data collection for data storage provides only applications. With focused on high-level approaches, Ceregenics the bride and groom, to store data in a single method adapts generic Scrum and XP, in good faith, development and results of such a watch SEI maturity capacity Model. Featured such as those for the six-step plan to pass formal evaluations methodological Agile project development team to become a world-class applications professionals, data warehouse, step by step guide launched. 

In Furthermore, the introduction of a method of resistance and radical skepticism and even some systems project management information based on traditional techniques with the Department for a Fortune 500 company, may explain the repairs to avoid chaos.

About the Author

Ralph Hughes, MA, chief architect Ceregenics systems, Certified Scrum Master (CSM) and the PMI Project Management Professional (PMP) since 1982 and has built data warehouses. Fortune agile projects, aviation, telecommunications and pharmaceutical companies, 500 run, is fluent in French international literature. O in Denver, Colorado skiing and fly fishing among the living, and projects.

Wednesday, 22 February 2012

Building the Data Warehouse

Description of Building the Data Warehouse

  • The data storage industry, has launched a new edition of the classic bestseller, new approaches and technologies, many of which were developed by INMO
  • In addition to explaining the basics of data storage systems, the book as a data warehouse to store unstructured data processing and data across multiple storage media covers issues such as methods for
  • The advantages and disadvantages of multi-dimensional design projects just relational data warehouses and how to measure return on investment analysis
  • Includes improved monitoring and test data includes son
  • Although the book contains valuable content worth 100 extra pages, the price is actually reduced to $ 65 $ 55 

Say

"... A thoughtful and clear text? I consider the establishment of a data warehouse, data management, study or recommend it to everyone ..." (Information Management, October 9, 2002)

"Overall, this text is clear and well thought out. I consider the establishment of a data warehouse, data management, and study or recommend it to everyone? "(General Information, December 2002) - This text refers to the issue of consolidation.

Through Back cover

The basic concepts and methods, more comprehensive data storage

Data warehouses collect data from a large amount of business organizations, analyze, store and deliver much-needed strategy. And both online and brick and mortar companies to expand their activity, the area of?? Data storage has become increasingly important. Since the first publication in 1990, WH INMO data warehouse data storage data storage industry bible book was launched and remains the ultimate building entrance. This new version has been encouraged by him INMO includes many of the latest developments in this technology.

Data warehouse design, migration of data storage technologies can be applied to a variety of strategies and provides an overview of methods used for data storage systems, an overview of all the building blocks of management loading, indexing and data. To update in more detail below, this guide offers the latest developments in data storage.

New sections:
  • The basic methods for handling unstructured data in a data warehouse
  • The data storage across multiple storage media
  • Examine the pros and cons of relational vs. dimensional design
  • Measure the profitability of investment projects data warehouse
  • And test data, including surveillance issues advances in research