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Data Mapping For Data Warehouse Design

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Data Mapping for Data Warehouse Design

Data Mapping for Data Warehouse Design Book
Author : Qamar Shahbaz
Publisher : Morgan Kaufmann Publishers
Release : 2015-12-10
ISBN : 9780128051856
Language : En, Es, Fr & De

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Book Description :

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

Data Mapping for Data Warehouse Design

Data Mapping for Data Warehouse Design Book
Author : Qamar Shahbaz
Publisher : Elsevier
Release : 2015-12-08
ISBN : 0128053356
Language : En, Es, Fr & De

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Book Description :

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

Data Warehouse Systems

Data Warehouse Systems Book
Author : Alejandro Vaisman,Esteban Zimányi
Publisher : Springer
Release : 2014-09-10
ISBN : 3642546552
Language : En, Es, Fr & De

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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 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.

Conceptual Modeling ER 2004

Conceptual Modeling   ER 2004 Book
Author : International Conference on Conceptual Modeling (23 : 2004 : Shanghai)
Publisher : Springer Science & Business Media
Release : 2004-10-27
ISBN : 3540237232
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the 23rd International Conference on Conceptual Modeling, ER 2004, held in Shanghai, China, in November 2004. The 57 revised full papers presented together with three invited contributions and 8 demonstration and poster papers were carefully reviewed and selected from 295 submissions. The papers are organized in topical sections on conceptual modeling, datawarehouses, schema integration, data classification and mining, web-based information systems, query processing, web services, schema evolution, conceptual modeling applications, UML, XML modeling, and industrial presentations.

Advanced Data Warehouse Design

Advanced Data Warehouse Design Book
Author : Elzbieta Malinowski,Esteban Zimányi
Publisher : Springer Science & Business Media
Release : 2008-01-22
ISBN : 9783540744054
Language : En, Es, Fr & De

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Book Description :

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.

Learn Data Warehousing in 24 Hours

Learn Data Warehousing in 24 Hours Book
Author : Alex Nordeen
Publisher : Guru99
Release : 2020-09-15
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

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?

The Data Warehouse ETL Toolkit

The Data Warehouse ETL Toolkit Book
Author : Ralph Kimball,Joe Caserta
Publisher : John Wiley & Sons
Release : 2011-04-27
ISBN : 111807968X
Language : En, Es, Fr & De

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Book Description :

Cowritten by Ralph Kimball, the world's leading data warehousing authority, whose previous books have sold more than 150,000 copies Delivers real-world solutions for the most time- and labor-intensive portion of data warehousing-data staging, or the extract, transform, load (ETL) process Delineates best practices for extracting data from scattered sources, removing redundant and inaccurate data, transforming the remaining data into correctly formatted data structures, and then loading the end product into the data warehouse Offers proven time-saving ETL techniques, comprehensive guidance on building dimensional structures, and crucial advice on ensuring data quality

Building the Data Warehouse

Building the Data Warehouse Book
Author : W. H. Inmon
Publisher : John Wiley & Sons
Release : 2002-10-15
ISBN : 0471270482
Language : En, Es, Fr & De

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Book Description :

The data warehousing bible updated for the new millennium Updated and expanded to reflect the many technological advances occurring since the previous edition, this latest edition of the data warehousing "bible" provides a comprehensive introduction to building data marts, operational data stores, the Corporate Information Factory, exploration warehouses, and Web-enabled warehouses. Written by the father of the data warehouse concept, the book also reviews the unique requirements for supporting e-business and explores various ways in which the traditional data warehouse can be integrated with new technologies to provide enhanced customer service, sales, and support-both online and offline-including near-line data storage techniques.

Data Warehousing and Knowledge Discovery

Data Warehousing and Knowledge Discovery Book
Author : Alfredo Cuzzocrea,Umeshwar Dayal
Publisher : Springer
Release : 2012-08-29
ISBN : 364232584X
Language : En, Es, Fr & De

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Book Description :

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 Architecture A Primer for the Data Scientist

Data Architecture  A Primer for the Data Scientist Book
Author : W.H. Inmon,Daniel Linstedt
Publisher : Morgan Kaufmann
Release : 2014-11-26
ISBN : 0128020911
Language : En, Es, Fr & De

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Book Description :

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 Mining Concepts Methodologies Tools and Applications

Data Warehousing and Mining  Concepts  Methodologies  Tools  and Applications Book
Author : Wang, John
Publisher : IGI Global
Release : 2008-05-31
ISBN : 159904952X
Language : En, Es, Fr & De

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Book Description :

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.

Building a Data Warehouse

Building a Data Warehouse Book
Author : Vincent Rainardi
Publisher : Apress
Release : 2007-12-26
ISBN : 1590599314
Language : En, Es, Fr & De

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Book Description :

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.

New Trends in Data Warehousing and Data Analysis

New Trends in Data Warehousing and Data Analysis Book
Author : Stanislaw Kozielski,Robert Wrembel
Publisher : Springer Science & Business Media
Release : 2008-10-23
ISBN : 0387874313
Language : En, Es, Fr & De

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Book Description :

Most of modern enterprises, institutions, and organizations rely on knowledge-based management systems. In these systems, knowledge is gained from data analysis. Today, knowledge-based management systems include data warehouses as their core components. Data integrated in a data warehouse are analyzed by the so-called On-Line Analytical Processing (OLAP) applications designed to discover trends, patterns of behavior, and anomalies as well as finding dependencies between data. Massive amounts of integrated data and the complexity of integrated data coming from many different sources make data integration and processing challenging. New Trends in Data Warehousing and Data Analysis brings together the most recent research and practical achievements in the DW and OLAP technologies. It provides an up-to-date bibliography of published works and the resource of research achievements. Finally, the book assists in the dissemination of knowledge in the field of advanced DW and OLAP.

Data Warehousing and Knowledge Discovery

Data Warehousing and Knowledge Discovery Book
Author : A Min Tjoa
Publisher : Springer
Release : 2006-09-21
ISBN : 3540377379
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the 8th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2006, held in conjunction with DEXA 2006. The book presents 53 revised full papers, organized in topical sections on ETL processing, materialized view, multidimensional design, OLAP and multidimensional model, cubes processing, data warehouse applications, mining techniques, frequent itemsets, mining data streams, ontology-based mining, clustering, advanced mining techniques, association rules, miscellaneous applications, and classification.

Mastering Data Warehouse Design

Mastering Data Warehouse Design Book
Author : Claudia Imhoff,Nicholas Galemmo,Jonathan G. Geiger
Publisher : John Wiley & Sons
Release : 2003-08-19
ISBN : 0471480924
Language : En, Es, Fr & De

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Book Description :

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

Encyclopedia of Data Warehousing and Mining Second Edition

Encyclopedia of Data Warehousing and Mining  Second Edition Book
Author : Wang, John
Publisher : IGI Global
Release : 2008-08-31
ISBN : 1605660116
Language : En, Es, Fr & De

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Book Description :

There are more than one billion documents on the Web, with the count continually rising at a pace of over one million new documents per day. As information increases, the motivation and interest in data warehousing and mining research and practice remains high in organizational interest. The Encyclopedia of Data Warehousing and Mining, Second Edition, offers thorough exposure to the issues of importance in the rapidly changing field of data warehousing and mining. This essential reference source informs decision makers, problem solvers, and data mining specialists in business, academia, government, and other settings with over 300 entries on theories, methodologies, functionalities, and applications.

Emerging Perspectives in Big Data Warehousing

Emerging Perspectives in Big Data Warehousing Book
Author : Taniar, David,Rahayu, Wenny
Publisher : IGI Global
Release : 2019-06-28
ISBN : 152255517X
Language : En, Es, Fr & De

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Book Description :

The concept of a big data warehouse appeared in order to store moving data objects and temporal data information. Moving objects are geometries that change their position and shape continuously over time. In order to support spatio-temporal data, a data model and associated query language is needed for supporting moving objects. Emerging Perspectives in Big Data Warehousing is an essential research publication that explores current innovative activities focusing on the integration between data warehousing and data mining with an emphasis on the applicability to real-world problems. Featuring a wide range of topics such as index structures, ontology, and user behavior, this book is ideally designed for IT consultants, researchers, professionals, computer scientists, academicians, and managers.

Agile Data Warehousing for the Enterprise

Agile Data Warehousing for the Enterprise Book
Author : Ralph Hughes
Publisher : Newnes
Release : 2015-09-19
ISBN : 0123965187
Language : En, Es, Fr & De

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Book Description :

Building upon his earlier book that detailed agile data warehousing programming techniques for the Scrum master, Ralph's latest work illustrates the agile interpretations of the remaining software engineering disciplines: Requirements management benefits from streamlined templates that not only define projects quickly, but ensure nothing essential is overlooked. Data engineering receives two new "hyper modeling" techniques, yielding data warehouses that can be easily adapted when requirements change without having to invest in ruinously expensive data-conversion programs. Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but also the incorporation of the latest in automated test engines. Use this step-by-step guide to deepen your own application development skills through self-study, show your teammates the world's fastest and most reliable techniques for creating business intelligence systems, or ensure that the IT department working for you is building your next decision support system the right way. Learn how to quickly define scope and architecture before programming starts Includes techniques of process and data engineering that enable iterative and incremental delivery Demonstrates how to plan and execute quality assurance plans and includes a guide to continuous integration and automated regression testing Presents program management strategies for coordinating multiple agile data mart projects so that over time an enterprise data warehouse emerges Use the provided 120-day road map to establish a robust, agile data warehousing program

Conceptual Modeling ER 2004

Conceptual Modeling   ER 2004 Book
Author : Paolo Atzeni,Wesley Chu,Hongjun Lu,Shuigeng Zhou,Tok Wang Ling
Publisher : Springer
Release : 2005-01-17
ISBN : 3540304649
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the 23rd International Conference on Conceptual Modeling, ER 2004, held in Shanghai, China, in November 2004. The 57 revised full papers presented together with three invited contributions and 8 demonstration and poster papers were carefully reviewed and selected from 295 submissions. The papers are organized in topical sections on conceptual modeling, datawarehouses, schema integration, data classification and mining, web-based information systems, query processing, web services, schema evolution, conceptual modeling applications, UML, XML modeling, and industrial presentations.

Contemporary Issues in Database Design and Information Systems Development

Contemporary Issues in Database Design and Information Systems Development Book
Author : Siau, Keng
Publisher : IGI Global
Release : 2007-04-30
ISBN : 1599042916
Language : En, Es, Fr & De

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Book Description :

"This book presents the latest research ideas and topics on databases and software development. It provides a representation of top notch research in all areas of database and information systems development"--Provided by publisher.