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Learn Data Warehousing in 24 Hours

Author: Alex Nordeen

Publisher: Guru99

Published: 2020-09-15

Total Pages: 111

ISBN-13:

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?

Learn Data Warehousing in 1 Day

Author: Krishna Rungta

Publisher:

Published: 2018-02-15

Total Pages: 113

ISBN-13: 9781980299653

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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 content Chapter 1: What Is Data Warehouse? What is Data Warehouse? Types of Data Warehouse Who needs Data warehouse? Why We Need Data Warehouse? Data Warehouse Tools Chapter 2: Data Warehouse Architecture Characteristics of Data warehouse Data Warehouse Architectures Datawarehouse Components Query Tools Chapter 3: ETL Process What is ETL? Why do you need ETL? ETL Process ETL tools Chapter 4: ETL Vs ELT What is ETL? Difference between ETL vs. ELT Chapter 5: Data Modeling What is Data Modelling? Types of Data Models Characteristics of a physical data model Chapter 6: OLAP What is Online Analytical Processing? Types of OLAP systems Advantages and Disadvantages of OLAP Chapter 7: Multidimensional Olap (MOLAP) What is MOLAP? MOLAP Architecture MOLAP Tools Chapter 8: OLAP Vs OLTP What is the meaning of OLAP? What is the meaning of OLTP? Difference between OLTP and OLAP Chapter 9: Dimensional Modeling What is Dimensional Model? Elements of Dimensional Data Model Attributes Difference between Dimension table vs. Fact table Steps of Dimensional Modelling Rules for Dimensional Modelling Chapter 10: Star and SnowFlake Schema What is Multidimensional schemas? What is a Star Schema? What is a Snowflake Schema? Difference between Start Schema and Snowflake Chapter 11: Data Mart What is Data Mart? Type of Data Mart Steps in Implementing a Datamart Chapter 12: Data Mart Vs Data Warehouse What is Data Warehouse? What is Data Mart? Differences between a Data Warehouse and a Data Mart Chapter 13: Data Lake What is Data Lake? Data Lake Architecture Key Data Lake Concepts Maturity stages of Data Lake Chapter 14: Data Lake Vs Data Warehouse What is Data Warehouse? What is Data Lake? Key Difference between the Data Lake and Data Warehouse Chapter 15: What Is Business Intelligence? What is Business Intelligence Why is BI important? How Business Intelligence systems are implemented? Four types of BI users Chapter 16: Data Mining What is Data Mining? Types of Data Data Mining Process Modelling

Building the Data Warehouse

Author: W. H. Inmon

Publisher: John Wiley & Sons

Published: 2002-10-01

Total Pages: 434

ISBN-13: 0471270482

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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 Fundamentals

Author: Paulraj Ponniah

Publisher: John Wiley & Sons

Published: 2004-04-07

Total Pages: 544

ISBN-13: 0471463892

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Geared to IT professionals eager to get into the all-importantfield of data warehousing, this book explores all topics needed bythose who design and implement data warehouses. Readers will learnabout planning requirements, architecture, infrastructure, datapreparation, information delivery, implementation, and maintenance.They'll also find a wealth of industry examples garnered from theauthor's 25 years of experience in designing and implementingdatabases and data warehouse applications for majorcorporations. Market: IT Professionals, Consultants.

Data Warehousing

Author: Mark Humphries

Publisher: Prentice Hall Professional

Published: 1999

Total Pages: 384

ISBN-13: 9780130809025

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The Data Warehouse Toolkit

Author: Ralph Kimball

Publisher: John Wiley & Sons

Published: 2011-08-08

Total Pages: 464

ISBN-13: 1118082141

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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.

Data Warehousing in the Age of Big Data

Author: Krish Krishnan

Publisher: Newnes

Published: 2013-05-02

Total Pages: 371

ISBN-13: 0124059201

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Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a Big Data–ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory. Ultimately, this book will help you navigate through the complex layers of Big Data and data warehousing while providing you information on how to effectively think about using all these technologies and the architectures to design the next-generation data warehouse. Learn how to leverage Big Data by effectively integrating it into your data warehouse. Includes real-world examples and use cases that clearly demonstrate Hadoop, NoSQL, HBASE, Hive, and other Big Data technologies Understand how to optimize and tune your current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements

Data Warehousing 101

Author: Arshad Khan

Publisher: iUniverse

Published: 2003

Total Pages: 136

ISBN-13: 0595290698

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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.

Data Warehousing and Mining:

Author: ITLESL

Publisher: Pearson Education India

Published: 2012

Total Pages: 271

ISBN-13: 8131799050

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Data Warehousing and Data Mining is presented in a question-and-answer format following the examination pattern and covers all key topics in the syllabus. The book is designed to make learning fast and effective and is precise, up-to-date and will help students excel in their examinations. The book is part of the Express Learning is a series of books designed as quick reference guides to important undergraduate courses. The organized and accessible format of these books allows students to learn important concepts in an easy-to-understand, question-and-answer format. These portable learning tools have been designed as one-stop references for students to understand and master the subjects by themselves.

Data Warehousing For Dummies

Author: Thomas C. Hammergren

Publisher: John Wiley & Sons

Published: 2009-04-13

Total Pages: 511

ISBN-13: 0470482923

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Data warehousing is one of the hottest business topics, and there’s more to understanding data warehousing technologies than you might think. Find out the basics of data warehousing and how it facilitates data mining and business intelligence with Data Warehousing For Dummies, 2nd Edition. Data is probably your company’s most important asset, so your data warehouse should serve your needs. The fully updated Second Edition of Data Warehousing For Dummies helps you understand, develop, implement, and use data warehouses, and offers a sneak peek into their future. You’ll learn to: Analyze top-down and bottom-up data warehouse designs Understand the structure and technologies of data warehouses, operational data stores, and data marts Choose your project team and apply best development practices to your data warehousing projects Implement a data warehouse, step by step, and involve end-users in the process Review and upgrade existing data storage to make it serve your needs Comprehend OLAP, column-wise databases, hardware assisted databases, and middleware Use data mining intelligently and find what you need Make informed choices about consultants and data warehousing products Data Warehousing For Dummies, 2nd Edition also shows you how to involve users in the testing process and gain valuable feedback, what it takes to successfully manage a data warehouse project, and how to tell if your project is on track. You’ll find it’s the most useful source of data on the topic!