Author: Mark Humphries
Publisher: Prentice Hall Professional
ISBN: 9780130809025
Category : Computers
Languages : en
Pages : 384

Get Book Here

Book Description
PLEASE PROVIDE COURSE INFORMATION PLEASE PROVIDE

Author: Jose Chinchilla
Publisher: Microsoft Press
ISBN: 1509304509
Category : Computers
Languages : en
Pages : 360

Get Book Here

Book Description
Prepare for Microsoft Exam 70-767–and help demonstrate your real-world mastery of skills for managing data warehouses. This exam is intended for Extract, Transform, Load (ETL) data warehouse developers who create business intelligence (BI) solutions. Their responsibilities include data cleansing as well as ETL and data warehouse implementation. The reader should have experience installing and implementing a Master Data Services (MDS) model, using MDS tools, and creating a Master Data Manager database and web application. The reader should understand how to design and implement ETL control flow elements and work with a SQL Service Integration Services package. Focus on the expertise measured by these objectives: • Design, and implement, and maintain a data warehouse • Extract, transform, and load data • Build data quality solutionsThis Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you have working knowledge of relational database technology and incremental database extraction, as well as experience with designing ETL control flows, using and debugging SSIS packages, accessing and importing or exporting data from multiple sources, and managing a SQL data warehouse. Implementing a SQL Data Warehouse About the Exam Exam 70-767 focuses on skills and knowledge required for working with relational database technology. About Microsoft Certification Passing this exam earns you credit toward a Microsoft Certified Professional (MCP) or Microsoft Certified Solutions Associate (MCSA) certification that demonstrates your mastery of data warehouse management Passing this exam as well as Exam 70-768 (Developing SQL Data Models) earns you credit toward a Microsoft Certified Solutions Associate (MCSA) SQL 2016 Business Intelligence (BI) Development certification. See full details at: microsoft.com/learning

Author: Arshad Khan
Publisher: iUniverse
ISBN: 0595290698
Category : Computers
Languages : en
Pages : 136

Get Book Here

Book Description
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.

Author: Bruce Russell Ullrey
Publisher: AuthorHouse
ISBN: 142599167X
Category : Data warehousing
Languages : en
Pages : 228

Get Book Here

Book Description
The purpose of this book is to document the methodology and chronology of work activity used by the author to successfully implement a Data Warehouse. Each of the eleven steps of the methodology is reviewed in the book, often using actual working documents as examples. The book contains lessons learned (both good and bad) as well as measures of success for each step. An essential aspect of DW project implementation (and other IT projects as well) is using established business practices to manage development and implementation. Discussion of use of these "due diligence" practices in Step 1 establishes the foundation for starting the DW project with the proper levels of management oversight. Step 2 presents examples of business models necessary for the DW developer to understand the needs of the business that the DW will serve. Other DW books describe the data modeling process but neglect to provide modeling instruction and actual examples to insure that the DW is properly aligned with business needs. An elegant data warehouse that doesn't meet the needs of the business is wasted effort. Step 3 documents and displays the level of detail needed to define CSF's (Critical Success Factors) and KPI's (Key Performance Indicators). If calculations for these important metrics are not defined in detail, and consensus to use them is not reached, then again, the most elegant data warehouse implementation is a wasted effort. In addition, developing and documenting functional requirements is essential in identifying legacy system reporting deficiencies. Step 4 describes how to access and display field level information on the iSeries platform. Actual shots of the resulting screens are shown. Step 5 presents the functional contents of an RFP for a Data Warehousing tool-set. Step 6 presents the progression of work required to build a data warehouse. Step 6 also: · Describes and displays a hybrid dimensional to flat file data model that may be, in reality, the best data organizational model for a typical data warehouse. Also, a table is included showing examples of data file field cryptic names and their corresponding metadata name. · &nb

Author: Alejandro Vaisman
Publisher: Springer Nature
ISBN: 366265167X
Category : Computers
Languages : en
Pages : 696

Get Book Here

Book Description
With this textbook, Vaisman and Zimányi deliver excellent coverage of data warehousing and business intelligence technologies ranging from the most basic principles to recent findings and applications. To this end, their work is structured into three parts. Part I describes “Fundamental Concepts” including conceptual and logical data warehouse design, as well as querying using MDX, DAX and SQL/OLAP. This part also covers data analytics using Power BI and Analysis Services. Part II details “Implementation and Deployment,” including physical design, ETL and data warehouse design methodologies. Part III covers “Advanced Topics” and it is almost completely new in this second edition. This part includes chapters with an in-depth coverage of temporal, spatial, and mobility data warehousing. Graph data warehouses are also covered in detail using Neo4j. The last chapter extensively studies big data management and the usage of Hadoop, Spark, distributed, in-memory, columnar, NoSQL and NewSQL database systems, and data lakes in the context of analytical data processing. As a key characteristic of the book, most of the topics are presented and illustrated using application tools. Specifically, a case study based on the well-known Northwind database illustrates how the concepts presented in the book can be implemented using Microsoft Analysis Services and Power BI. All chapters have been revised and updated to the latest versions of the software tools used. KPIs and Dashboards are now also developed using DAX and Power BI, and the chapter on ETL has been expanded with the implementation of ETL processes in PostgreSQL. Review questions and exercises complement each chapter to support comprehensive student learning. Supplemental material to assist instructors using this book as a course text is available online and includes electronic versions of the figures, solutions to all exercises, and a set of slides accompanying each chapter. Overall, students, practitioners and researchers alike will find this book the most comprehensive reference work on data warehouses, with key topics described in a clear and educational style. “I can only invite you to dive into the contents of the book, feeling certain that once you have completed its reading (or maybe, targeted parts of it), you will join me in expressing our gratitude to Alejandro and Esteban, for providing such a comprehensive textbook for the field of data warehousing in the first place, and for keeping it up to date with the recent developments, in this current second edition.” From the foreword by Panos Vassiliadis, University of Ioannina, Greece.

Author: Vincent Rainardi
Publisher: Apress
ISBN: 1430205288
Category : Computers
Languages : en
Pages : 526

Get Book Here

Book Description
Here is the ideal field guide for data warehousing implementation. This book first teaches you how to build a data warehouse, including defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Coverage then explains how to populate the data warehouse and explores how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes. It also details testing and how to administer data warehouse operation.

Author: Barry Devlin
Publisher: Addison-Wesley Professional
ISBN:
Category : Computers
Languages : en
Pages : 456

Get Book Here

Book Description
Data warehousing is one of the hottest topics in the computing industry. Written by Barry Devlin, one of the world's leading experts on data warehousing, this book gives you the insights and experiences gained over 10 years and offers the most comprehensive, practical guide to designing, building, and implementing a successful data warehouse. Included in this vital information is an explanation of the optimal three-tiered architecture for the data warehouse, with a clear division between data and information. Information systems managers will appreciate the full description of the functions needed to implement such an architecture, including reconciling existing, diverse data and deriving consistent, valuable business information.

Author: Ramón C. Barquín
Publisher: Prentice Hall
ISBN:
Category : Computers
Languages : en
Pages : 346

Get Book Here

Book Description
This is a comprehensive survey of key issues associated with planning and designing enterprise data warehouses.Covers the process of implementing a data warehouse end-to-end, from planning a data warehouse, to achieving management support, to implementing metadata repositories that make it easier to access real information, rather than mere data. One chapter is dedicated to helping managers avoid mistakes that can limit the effectiveness of a data warehouse. Once the data warehouse is in place, this book provides guidance on helping end users make the most of it. Two detailed case studies are also included.Information technology managers, and database professionals, including administrators, programmers and designers.

Author: Ralph Kimball
Publisher: John Wiley & Sons
ISBN: 1118082141
Category : Computers
Languages : en
Pages : 464

Get Book Here

Book Description
This old edition was published in 2002. The current and final edition of this book is The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition which was published in 2013 under ISBN: 9781118530801. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: Retail sales and e-commerce Inventory management Procurement Order management Customer relationship management (CRM) Human resources management Accounting Financial services Telecommunications and utilities Education Transportation Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.

Author: Daniel Linstedt
Publisher: Morgan Kaufmann
ISBN: 0128026480
Category : Computers
Languages : en
Pages : 684

Get Book Here

Book Description
The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. "Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes. Important data warehouse technologies and practices. Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture. Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouse Demystifies data vault modeling with beginning, intermediate, and advanced techniques Discusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0