Data Mapping For Data Warehouse Design

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Data Mapping for Data Warehouse Design

Qamar Shahbaz
Data Mapping for Data Warehouse Design Book PDF

Author : Qamar Shahbaz
Publisher : Elsevier
Page : 180 pages
File Size : 50,8 Mb
Release : 2015-12-08
Category : Computers
ISBN : 9780128053355

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Data Mapping for Data Warehouse Design by Qamar Shahbaz Pdf

Data mapping in a data warehouse is the process of creating a link between two distinct data models’ (source and target) tables/attributes. Data mapping is required at many stages of DW life-cycle to help save processor overhead; every stage has its own unique requirements and challenges. Therefore, many data warehouse professionals want to learn data mapping in order to move from an ETL (extract, transform, and load data between databases) developer to a data modeler role. Data Mapping for Data Warehouse Design provides basic and advanced knowledge about business intelligence and data warehouse concepts including real life scenarios that apply the standard techniques to projects across various domains. After reading this book, readers will understand the importance of data mapping across the data warehouse life cycle. Covers all stages of data warehousing and the role of data mapping in each Includes a data mapping strategy and techniques that can be applied to many situations Based on the author’s years of real-world experience designing solutions

Advanced Data Warehouse Design

Elzbieta Malinowski,Esteban Zimányi
Advanced Data Warehouse Design Book PDF

Author : Elzbieta Malinowski,Esteban Zimányi
Publisher : Springer Science & Business Media
Page : 435 pages
File Size : 45,8 Mb
Release : 2008-01-22
Category : Computers
ISBN : 9783540744054

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Advanced Data Warehouse Design by Elzbieta Malinowski,Esteban Zimányi Pdf

This exceptional work provides readers with an introduction to the state-of-the-art research on data warehouse design, with many references to more detailed sources. It offers a clear and a concise presentation of the major concepts and results in the subject area. Malinowski and Zimányi explain conventional data warehouse design in detail, and additionally address two innovative domains recently introduced to extend the capabilities of data warehouse systems: namely, the management of spatial and temporal information.

Data Warehouse Systems

Alejandro Vaisman,Esteban Zimányi
Data Warehouse Systems Book PDF

Author : Alejandro Vaisman,Esteban Zimányi
Publisher : Springer
Page : 625 pages
File Size : 51,8 Mb
Release : 2014-09-10
Category : Computers
ISBN : 9783642546556

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Data Warehouse Systems by Alejandro Vaisman,Esteban Zimányi Pdf

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 multi-dimensional models; conceptual and logical data warehouse design and MDX and SQL/OLAP. Subsequently, Part II details “Implementation and Deployment,” which includes physical data warehouse design; data extraction, transformation, and loading (ETL) and data analytics. Lastly, Part III covers “Advanced Topics” such as spatial data warehouses; trajectory data warehouses; semantic technologies in data warehouses and novel technologies like Map Reduce, column-store databases and in-memory databases. 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 Pentaho Business Analytics. All chapters are summarized using review questions and exercises to support comprehensive student learning. Supplemental material to assist instructors using this book as a course text is available at http://cs.ulb.ac.be/DWSDIbook/, including 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.

Agile Data Warehouse Design

Lawrence Corr,Jim Stagnitto
Agile Data Warehouse Design Book PDF

Author : Lawrence Corr,Jim Stagnitto
Publisher : DecisionOne Consulting
Page : 330 pages
File Size : 54,8 Mb
Release : 2011-11
Category : Business & Economics
ISBN : 9780956817204

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Agile Data Warehouse Design by Lawrence Corr,Jim Stagnitto Pdf

Agile Data Warehouse Design is a step-by-step guide for capturing data warehousing/business intelligence (DW/BI) requirements and turning them into high performance dimensional models in the most direct way: by modelstorming (data modeling + brainstorming) with BI stakeholders. This book describes BEAM✲, an agile approach to dimensional modeling, for improving communication between data warehouse designers, BI stakeholders and the whole DW/BI development team. BEAM✲ provides tools and techniques that will encourage DW/BI designers and developers to move away from their keyboards and entity relationship based tools and model interactively with their colleagues. The result is everyone thinks dimensionally from the outset! Developers understand how to efficiently implement dimensional modeling solutions. Business stakeholders feel ownership of the data warehouse they have created, and can already imagine how they will use it to answer their business questions. Within this book, you will learn: ✲ Agile dimensional modeling using Business Event Analysis & Modeling (BEAM✲) ✲ Modelstorming: data modeling that is quicker, more inclusive, more productive, and frankly more fun! ✲ Telling dimensional data stories using the 7Ws (who, what, when, where, how many, why and how) ✲ Modeling by example not abstraction; using data story themes, not crow's feet, to describe detail ✲ Storyboarding the data warehouse to discover conformed dimensions and plan iterative development ✲ Visual modeling: sketching timelines, charts and grids to model complex process measurement - simply ✲ Agile design documentation: enhancing star schemas with BEAM✲ dimensional shorthand notation ✲ Solving difficult DW/BI performance and usability problems with proven dimensional design patterns Lawrence Corr is a data warehouse designer and educator. As Principal of DecisionOne Consulting, he helps clients to review and simplify their data warehouse designs, and advises vendors on visual data modeling techniques. He regularly teaches agile dimensional modeling courses worldwide and has taught dimensional DW/BI skills to thousands of students. Jim Stagnitto is a data warehouse and master data management architect specializing in the healthcare, financial services, and information service industries. He is the founder of the data warehousing and data mining consulting firm Llumino.

Conceptual Modeling - ER 2004

Paolo Atzeni,Wesley Chu,Hongjun Lu,Shuigeng Zhou,Tok Wang Ling
Conceptual Modeling ER 2004 Book PDF

Author : Paolo Atzeni,Wesley Chu,Hongjun Lu,Shuigeng Zhou,Tok Wang Ling
Publisher : Springer
Page : 874 pages
File Size : 55,8 Mb
Release : 2005-01-17
Category : Computers
ISBN : 9783540304647

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Conceptual Modeling - ER 2004 by Paolo Atzeni,Wesley Chu,Hongjun Lu,Shuigeng Zhou,Tok Wang Ling Pdf

On behalf of the Organizing Committee, we would like to welcome you to the proccedings of the 23rd International Conference on Conceptual Modeling (ER 2004). This conference provided an international forum for technical discussion on conceptual modeling of information systems among researchers, developers and users. This was the third time that this conference was held in Asia; the?rst time was in Singapore in 1998 and the second time was in Yokohama, Japan in 2001. China is the third largest nation with the largest population in the world. Shanghai, the largest city in China and a great metropolis, famous in Asia and throughout the world, is therefore a most appropriate location to host this conference. This volume contains papers selected for presentation and includes the two keynote talks by Prof. Hector Garcia-Molina and Prof. Gerhard Weikum, and an invited talk by Dr. Xiao Ji. This volume also contains industrial papers and demo/poster papers. An additional volume contains papers from 6 workshops. The conference also featured three tutorials: (1) Web Change Management andDelta Mining: Opportunities andSolutions, by SanjayMadria, (2)A Survey of Data Quality Issues in Cooperative Information Systems, by Carlo Batini, and (3) Visual SQL - An ER-Based Introduction to Database Programming, by Bernhard Thalheim.

Data Warehouse Design: Modern Principles and Methodologies

Matteo Golfarelli,Stefano Rizzi
Data Warehouse Design Modern Principles and Methodologies Book PDF

Author : Matteo Golfarelli,Stefano Rizzi
Publisher : McGraw Hill Professional
Page : 481 pages
File Size : 51,9 Mb
Release : 2009-03-03
Category : Computers
ISBN : 9780071610407

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Data Warehouse Design: Modern Principles and Methodologies by Matteo Golfarelli,Stefano Rizzi Pdf

Foreword by Mark Stephen LaRow, Vice President of Products, MicroStrategy "A unique and authoritative book that blends recent research developments with industry-level practices for researchers, students, and industry practitioners." Il-Yeol Song, Professor, College of Information Science and Technology, Drexel University

Data Warehousing 101

Arshad Khan
Data Warehousing 101 Book PDF

Author : Arshad Khan
Publisher : iUniverse
Page : 136 pages
File Size : 55,6 Mb
Release : 2003
Category : Computers
ISBN : 9780595290697

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Data Warehousing 101 by Arshad Khan Pdf

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.

Object-oriented Data Warehouse Design

William A. Giovinazzo
Object oriented Data Warehouse Design Book PDF

Author : William A. Giovinazzo
Publisher : Prentice Hall
Page : 376 pages
File Size : 47,7 Mb
Release : 2000
Category : Computers
ISBN : UOM:39015042597404

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Object-oriented Data Warehouse Design by William A. Giovinazzo Pdf

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Building a Data Warehouse

Vincent Rainardi
Building a Data Warehouse Book PDF

Author : Vincent Rainardi
Publisher : Apress
Page : 546 pages
File Size : 49,5 Mb
Release : 2007-12-27
Category : Computers
ISBN : 1590599314

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Building a Data Warehouse by Vincent Rainardi Pdf

Building a Data Warehouse: With Examples in SQL Server describes how to build a data warehouse completely from scratch and shows practical examples on how to do it. Author Vincent Rainardi also describes some practical issues he has experienced that developers are likely to encounter in their first data warehousing project, along with solutions and advice. The relational database management system (RDBMS) used in the examples is SQL Server; the version will not be an issue as long as the user has SQL Server 2005 or later. The book is organized as follows. In the beginning of this book (chapters 1 through 6), you learn how to build a data warehouse, for example, defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Then in chapters 7 through 10, you learn how to populate the data warehouse, for example, extracting from source systems, loading the data stores, maintaining data quality, and utilizing the metadata. After you populate the data warehouse, in chapters 11 through 15, you explore 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. Chapters 16 and 17 wrap up the book: After you have built your data warehouse, before it can be released to production, you need to test it thoroughly. After your application is in production, you need to understand how to administer data warehouse operation. What you’ll learn A detailed understanding of what it takes to build a data warehouse The implementation code in SQL Server to build the data warehouse Dimensional modeling, data extraction methods, data warehouse loading, populating dimension and fact tables, data quality, data warehouse architecture, and database design Practical data warehousing applications such as business intelligence reports, analytics applications, and customer relationship management Who this book is for There are three audiences for the book. The first are the people who implement the data warehouse. This could be considered a field guide for them. The second is database users/admins who want to get a good understanding of what it would take to build a data warehouse. Finally, the third audience is managers who must make decisions about aspects of the data warehousing task before them and use the book to learn about these issues.

Building the Data Warehouse

W. H. Inmon
Building the Data Warehouse Book PDF

Author : W. H. Inmon
Publisher : John Wiley & Sons
Page : 576 pages
File Size : 53,9 Mb
Release : 2005-10-03
Category : Computers
ISBN : 9780471774235

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Building the Data Warehouse by W. H. Inmon Pdf

The new edition of the classic bestseller that launched thedata warehousing industry covers new approaches and technologies,many of which have been pioneered by Inmon himself In addition to explaining the fundamentals of data warehousesystems, the book covers new topics such as methods for handlingunstructured data in a data warehouse and storing data acrossmultiple storage media Discusses the pros and cons of relational versusmultidimensional design and how to measure return on investment inplanning data warehouse projects Covers advanced topics, including data monitoring andtesting Although the book includes an extra 100 pages worth of valuablecontent, the price has actually been reduced from $65 to $55

Learn Data Warehousing in 24 Hours

Alex Nordeen
Learn Data Warehousing in 24 Hours Book PDF

Author : Alex Nordeen
Publisher : Guru99
Page : 111 pages
File Size : 45,6 Mb
Release : 2020-09-15
Category : Computers
ISBN : 8210379456XXX

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Learn Data Warehousing in 24 Hours by Alex Nordeen Pdf

Unlike popular belief, Data Warehouse is not a single tool but a collection of software tools. A data warehouse will collect data from diverse sources into a single database. Using Business Intelligence tools, meaningful insights are drawn from this data. The best thing about “Learn Data Warehousing in 1 Day" is that it is small and can be completed in a day. With this e-book, you will be enough knowledge to contribute and participate in a Data warehouse implementation project. The book covers upcoming and promising technologies like Data Lakes, Data Mart, ELT (Extract Load Transform) amongst others. Following are detailed topics included in the book Table Of Content Chapter 1: What Is Data Warehouse? 1. What is Data Warehouse? 2. Types of Data Warehouse 3. Who needs Data warehouse? 4. Why We Need Data Warehouse? 5. Data Warehouse Tools Chapter 2: Data Warehouse Architecture 1. Characteristics of Data warehouse 2. Data Warehouse Architectures 3. Datawarehouse Components 4. Query Tools Chapter 3: ETL Process 1. What is ETL? 2. Why do you need ETL? 3. ETL Process 4. ETL tools Chapter 4: ETL Vs ELT 1. What is ETL? 2. Difference between ETL vs. ELT Chapter 5: Data Modeling 1. What is Data Modelling? 2. Types of Data Models 3. Characteristics of a physical data model Chapter 6: OLAP 1. What is Online Analytical Processing? 2. Types of OLAP systems 3. Advantages and Disadvantages of OLAP Chapter 7: Multidimensional Olap (MOLAP) 1. What is MOLAP? 2. MOLAP Architecture 3. MOLAP Tools Chapter 8: OLAP Vs OLTP 1. What is the meaning of OLAP? 2. What is the meaning of OLTP? 3. Difference between OLTP and OLAP Chapter 9: Dimensional Modeling 1. What is Dimensional Model? 2. Elements of Dimensional Data Model 3. Attributes 4. Difference between Dimension table vs. Fact table 5. Steps of Dimensional Modelling 6. Rules for Dimensional Modelling Chapter 10: Star and SnowFlake Schema 1. What is Multidimensional schemas? 2. What is a Star Schema? 3. What is a Snowflake Schema? 4. Difference between Start Schema and Snowflake Chapter 11: Data Mart 1. What is Data Mart? 2. Type of Data Mart 3. Steps in Implementing a Datamart Chapter 12: Data Mart Vs Data Warehouse 1. What is Data Warehouse? 2. What is Data Mart? 3. Differences between a Data Warehouse and a Data Mart Chapter 13: Data Lake 1. What is Data Lake? 2. Data Lake Architecture 3. Key Data Lake Concepts 4. Maturity stages of Data Lake Chapter 14: Data Lake Vs Data Warehouse 1. What is Data Warehouse? 2. What is Data Lake? 3. Key Difference between the Data Lake and Data Warehouse Chapter 15: What Is Business Intelligence? 1. What is Business Intelligence 2. Why is BI important? 3. How Business Intelligence systems are implemented? 4. Four types of BI users Chapter 16: Data Mining 1. What is Data Mining? 2. Types of Data 3. Data Mining Process 4. Modelling 5. Data Mining Techniques Chapter 17: Data Warehousing Vs Data Mining 1. What is Data warehouse? 2. What Is Data Mining? 3. Difference between Data mining and Data Warehousing?

Mastering Data Warehouse Design

Claudia Imhoff,Nicholas Galemmo,Jonathan G. Geiger
Mastering Data Warehouse Design Book PDF

Author : Claudia Imhoff,Nicholas Galemmo,Jonathan G. Geiger
Publisher : Wiley
Page : 460 pages
File Size : 54,7 Mb
Release : 2003
Category : Computers
ISBN : 0471324213

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Mastering Data Warehouse Design by Claudia Imhoff,Nicholas Galemmo,Jonathan G. Geiger Pdf

A cutting-edge response to Ralph Kimball's challenge to the data warehouse community that answers some tough questions about the effectiveness of the relational approach to data warehousing Written by one of the best-known exponents of the Bill Inmon approach to data warehousing Addresses head-on the tough issues raised by Kimball and explains how to choose the best modeling technique for solving common data warehouse design problems Weighs the pros and cons of relational vs. dimensional modeling techniques Focuses on tough modeling problems, including creating and maintaining keys and modeling calendars, hierarchies, transactions, and data quality

Data Architecture: A Primer for the Data Scientist

W.H. Inmon,Daniel Linstedt
Data Architecture A Primer for the Data Scientist Book PDF

Author : W.H. Inmon,Daniel Linstedt
Publisher : Morgan Kaufmann
Page : 378 pages
File Size : 48,7 Mb
Release : 2014-11-26
Category : Computers
ISBN : 9780128020913

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Data Architecture: A Primer for the Data Scientist by W.H. Inmon,Daniel Linstedt Pdf

Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can’t be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You’ll be able to: Turn textual information into a form that can be analyzed by standard tools. Make the connection between analytics and Big Data Understand how Big Data fits within an existing systems environment Conduct analytics on repetitive and non-repetitive data Discusses the value in Big Data that is often overlooked, non-repetitive data, and why there is significant business value in using it Shows how to turn textual information into a form that can be analyzed by standard tools Explains how Big Data fits within an existing systems environment Presents new opportunities that are afforded by the advent of Big Data Demystifies the murky waters of repetitive and non-repetitive data in Big Data

Data Warehousing and Knowledge Discovery

Alfredo Cuzzocrea,Umeshwar Dayal
Data Warehousing and Knowledge Discovery Book PDF

Author : Alfredo Cuzzocrea,Umeshwar Dayal
Publisher : Springer
Page : 454 pages
File Size : 52,5 Mb
Release : 2012-08-29
Category : Computers
ISBN : 9783642325847

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Data Warehousing and Knowledge Discovery by Alfredo Cuzzocrea,Umeshwar Dayal Pdf

This book constitutes the refereed proceedings of the 14th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2012 held in Vienna, Austria, in September 2012. The 36 revised full papers presented were carefully reviewed and selected from 99 submissions. The papers are organized in topical sections on data warehouse design methodologies, ETL methodologies and tools, multidimensional data processing and management, data warehouse and OLAP extensions, data warehouse performance and optimization, data mining and knowledge discovery techniques, data mining and knowledge discovery applications, pattern mining, data stream mining, data warehouse confidentiality and security, and distributed paradigms and algorithms.

Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications

Wang, John
Data Warehousing and Mining Concepts Methodologies Tools and Applications Book PDF

Author : Wang, John
Publisher : IGI Global
Page : 4092 pages
File Size : 49,5 Mb
Release : 2008-05-31
Category : Technology & Engineering
ISBN : 9781599049526

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Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications by Wang, John Pdf

In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.