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Author | : Alex Nordeen |
Publisher | : Guru99 |
Total Pages | : 111 |
Release | : 2020-09-15 |
Genre | : Computers |
ISBN | : |
Download Learn Data Warehousing in 24 Hours Book in PDF, ePub and Kindle
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?
Author | : Krishna Rungta |
Publisher | : |
Total Pages | : 113 |
Release | : 2018-02-15 |
Genre | : |
ISBN | : 9781980299653 |
Download Learn Data Warehousing in 1 Day Book in PDF, ePub and Kindle
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
Author | : Paulraj Ponniah |
Publisher | : John Wiley & Sons |
Total Pages | : 544 |
Release | : 2004-04-07 |
Genre | : Computers |
ISBN | : 0471463892 |
Download Data Warehousing Fundamentals Book in PDF, ePub and Kindle
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.
Author | : Lawrence Corr |
Publisher | : DecisionOne Consulting |
Total Pages | : 330 |
Release | : 2011-11 |
Genre | : Business & Economics |
ISBN | : 0956817203 |
Download Agile Data Warehouse Design Book in PDF, ePub and Kindle
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.
Author | : Parteek Bhatia |
Publisher | : Cambridge University Press |
Total Pages | : |
Release | : 2019-04-30 |
Genre | : Computers |
ISBN | : 110858585X |
Download Data Mining and Data Warehousing Book in PDF, ePub and Kindle
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.
Author | : Ralph Kimball |
Publisher | : John Wiley & Sons |
Total Pages | : 464 |
Release | : 2011-08-08 |
Genre | : Computers |
ISBN | : 1118082141 |
Download The Data Warehouse Toolkit Book in PDF, ePub and Kindle
This old edition was published in 2002. The current and final edition of this book is The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition which was published in 2013 under ISBN: 9781118530801. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: Retail sales and e-commerce Inventory management Procurement Order management Customer relationship management (CRM) Human resources management Accounting Financial services Telecommunications and utilities Education Transportation Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.
Author | : Mark Humphries |
Publisher | : Prentice Hall Professional |
Total Pages | : 384 |
Release | : 1999 |
Genre | : Computers |
ISBN | : 9780130809025 |
Download Data Warehousing Book in PDF, ePub and Kindle
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Author | : Arshad Khan |
Publisher | : iUniverse |
Total Pages | : 136 |
Release | : 2003 |
Genre | : Computers |
ISBN | : 0595290698 |
Download Data Warehousing 101 Book in PDF, ePub and Kindle
Data Warehousing 101: Concepts and Implementation will appeal to those planning data warehouse projects, senior executives, project managers, and project implementation team members. It will also be useful to functional managers, business analysts, developers, power users, and end-users. Data Warehousing 101: Concepts and Implementation, which can be used as a textbook in an introductory data warehouse course, can also be used as a supplemental text in IT courses that cover the subject of data warehousing. Data Warehousing 101: Concepts and Implementation reviews the evolution of data warehousing and its growth drivers, process and architecture, data warehouse characteristics and design, data marts, multi-dimensionality, and OLAP. It also shows how to plan a data warehouse project as well as build and operate data warehouses. Data Warehousing 101: Concepts and Implementation also covers, in depth, common failure causes and mistakes and provides useful guidelines and tips for avoiding common mistakes.
Author | : W. H. Inmon |
Publisher | : John Wiley & Sons |
Total Pages | : 434 |
Release | : 2002-10-01 |
Genre | : Computers |
ISBN | : 0471270482 |
Download Building the Data Warehouse Book in PDF, ePub and Kindle
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.
Author | : Thomas C. Hammergren |
Publisher | : John Wiley & Sons |
Total Pages | : 511 |
Release | : 2009-04-13 |
Genre | : Computers |
ISBN | : 0470482923 |
Download Data Warehousing For Dummies Book in PDF, ePub and Kindle
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!