Download or read book Learn Data Warehousing in 24 Hours written by Alex Nordeen and published by Guru99. This book was released on 2020-09-15 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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?

Download or read book Learn Data Warehousing in 1 Day written by Krishna Rungta and published by . This book was released on 2018-02-15 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Data Warehousing in the Age of Big Data written by Krish Krishnan and published by Newnes. This book was released on 2013-05-02 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book The Data Warehouse Toolkit written by Ralph Kimball and published by John Wiley & Sons. This book was released on 2011-08-08 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Data Warehousing Fundamentals written by Paulraj Ponniah and published by John Wiley & Sons. This book was released on 2004-04-07 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Building the Data Warehouse written by W. H. Inmon and published by John Wiley & Sons. This book was released on 2002-10-01 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Data Warehousing 101 written by Arshad Khan and published by iUniverse. This book was released on 2003 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Data Warehousing and Analytics written by David Taniar and published by Springer Nature. This book was released on 2022-02-04 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook covers all central activities of data warehousing and analytics, including transformation, preparation, aggregation, integration, and analysis. It discusses the full spectrum of the journey of data from operational/transactional databases, to data warehouses and data analytics; as well as the role that data warehousing plays in the data processing lifecycle. It also explains in detail how data warehouses may be used by data engines, such as BI tools and analytics algorithms to produce reports, dashboards, patterns, and other useful information and knowledge. The book is divided into six parts, ranging from the basics of data warehouse design (Part I - Star Schema, Part II - Snowflake and Bridge Tables, Part III - Advanced Dimensions, and Part IV - Multi-Fact and Multi-Input), to more advanced data warehousing concepts (Part V - Data Warehousing and Evolution) and data analytics (Part VI - OLAP, BI, and Analytics). This textbook approaches data warehousing from the case study angle. Each chapter presents one or more case studies to thoroughly explain the concepts and has different levels of difficulty, hence learning is incremental. In addition, every chapter has also a section on further readings which give pointers and references to research papers related to the chapter. All these features make the book ideally suited for either introductory courses on data warehousing and data analytics, or even for self-studies by professionals. The book is accompanied by a web page that includes all the used datasets and codes as well as slides and solutions to exercises.

Download or read book Business Intelligence and Data Warehousing Simplified written by Arshad Khan and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book targets business and IT professionals who need an introduction to business intelligence and data warehousing fundamentals through a simple question / answer format. Topics include evolution and fundamentals, characteristics and process, architecture and objects, metadata, data conversion, ETL, data storage, infrastructure, data access, data marts, implementation approaches, planning, design, Inmon vs. Kimball, multi-dimensionality, OLAP, facts and dimensions, common mistakes and tips, trends, etc.

Download or read book Data Warehousing and Mining written by ITLESL and published by Pearson Education India. This book was released on 2012 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Data Warehousing For Dummies written by Thomas C. Hammergren and published by John Wiley & Sons. This book was released on 2009-04-13 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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!

Download or read book 100 Puzzles to Learn Data Warehousing written by Cristian Scutaru and published by Cristian Scutaru. This book was released on with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning how to design a data warehouse may be difficult. Ralph Kimball has some great legacy books on the dimensional modeling techniques, but they are verbose, with complicated examples. Our illustrated examples here are kept simple on purpose, to help you better understand complicated concepts like periodic snapshot fact tables, degenerate dimensions, late arriving facts or dimensions. We focus our puzzles on Ralph Kimball's dimensional modeling techniques, but we also introduce you to Extract-Transform-Load (ETL) basics, OLAP fundamentals and some other important things you must know about data warehouses in general. We dive deep into slowly changing dimensions (SCD), with other illustrated examples to help you get the ideas in no time. You need just some basic prior knowledge about Data Warehouses in general. The explanations and external references from the answers to our questions will help you learn the rest. We also assume you already have some basic background in data modeling for relational databases, and SQL. These puzzles are for Software Developers and Engineers, Database Engineers and Architects, or Data Analysts. Difficulty level is from beginner to advanced. We've split the 100 questions into 5 quizzes with 20 single and multi-choice questions each. Try solving each quiz separately, writing down on a piece of paper the answer to each question. Then go to the Answers and Explanations section, and learn more from our solutions to the puzzles. Follow the links to external references for a deep dive on the subject. An interactive version of this book has been implemented on Udemy as 100 Puzzles to Learn Data Warehousing.

Download or read book Data Mining and Data Warehousing written by Parteek Bhatia and published by Cambridge University Press. This book was released on 2019-04-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding.

Download or read book Building Using and Managing the Data Warehouse written by Ramón C. Barquín and published by Prentice Hall. This book was released on 1997 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: When it comes to making organizations smarter, faster, and more competitive, few technologies have more promise than data warehousing. This book shows you how to translate that promise into reality.

Download or read book Building a Data Warehouse written by Vincent Rainardi and published by Apress. This book was released on 2007-12-27 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book DATA WAREHOUSING written by C.S.R. PRABHU and published by PHI Learning Pvt. Ltd.. This book was released on 2008-08-25 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Third Edition of this well-received text analyses the fundamental concepts of data warehousing, data marts, and OLAP. The author discusses, in an easy-to-understand language, important topics such as data mining, how to build a data warehouse, and potential applications of data warehousing technology in government. Besides, the text compares and contrasts the currently available software tools used to design and develop data warehouses. While retaining the six existing case studies, it gives four new case studies:  HARBOR, A Highly Available Data Warehouse  A Typical Business Data Warehouse for a Trading Company  Customer Data Warehouse for the World’s First and Largest Online Bank in the United Kingdom  A German Supermarket EDEKA’s Data Warehouse The book, which is a blend of principles and real-life case studies, is intended as a text for students of B.Tech/M.Tech (Computer Science and Engineering), B.Tech/M.Tech (Information Technology), MBA, M.Sc. (Computer Science), M.Sc. (Information Technology), and MCA. It should also be of considerable utility and worth to software professionals and database practitioners.

Download or read book Data Warehouse Systems written by Alejandro Vaisman and published by Springer. This book was released on 2014-09-10 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.