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Data Warehousing Olap And Data Mining

Data Warehousing Olap And Data Mining
Author: S. Nagabhushana
Publisher: New Age International
Total Pages: 22
Release: 2006
Genre: Data mining
ISBN: 8122417647

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This Book Is Mainly Intended For It Students And Professionals To Learn Or Implement Data Warehousing Technologies. It Experiences The Real-Time Environment And Promotes Planning, Managing, Designing, Implementing, Supporting, Maintaining And Analyzing Data Warehouse In Organizations And It Also Provides Various Mining Techniques As Well As Issues In Practical Use Of Data Mining Tools.The Book Is Designed For The Target Audience Such As Specialists, Trainers And It Users. It Does Not Assume Any Special Knowledge As Background. Understanding Of Computer Use, Databases And Statistics Will Be Helpful.


Data Warehouses and OLAP

Data Warehouses and OLAP
Author: Robert Wrembel
Publisher: IGI Global
Total Pages: 361
Release: 2007-01-01
Genre: Computers
ISBN: 1599043645

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Data warehouses and online analytical processing (OLAP) are emerging key technologies for enterprise decision support systems. They provide sophisticated technologies from data integration, data collection and retrieval, query optimization, and data analysis to advanced user interfaces. New research and technological achievements in the area of data warehousing are implemented in commercial database management systems, and organizations are developing data warehouse systems into their information system infrastructures. Data Warehouses and OLAP: Concepts, Architectures and Solutions covers a wide range of technical, technological, and research issues. It provides theoretical frameworks, presents challenges and their possible solutions, and examines the latest empirical research findings in the area. It is a resource of possible solutions and technologies that can be applied when designing, implementing, and deploying a data warehouse, and assists in the dissemination of knowledge in this field.


Data Warehousing, Data Mining, and OLAP

Data Warehousing, Data Mining, and OLAP
Author: Alex Berson
Publisher: McGraw-Hill Companies
Total Pages: 648
Release: 1997
Genre: Computers
ISBN:

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"Data Warehousing" is the nuts-and-bolts guide to designing a data management system using data warehousing, data mining, and online analytical processing (OLAP) and how successfully integrating these three technologies can give business a competitive edge.


Learn Data Warehousing in 24 Hours

Learn Data Warehousing in 24 Hours
Author: Alex Nordeen
Publisher: Guru99
Total Pages: 111
Release: 2020-09-15
Genre: Computers
ISBN:

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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 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?


Data Warehousing.

Data Warehousing.
Author: Wolfgang Martin
Publisher:
Total Pages: 447
Release: 1998
Genre:
ISBN: 9783826640223

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Data Warehousing and Mining:

Data Warehousing and Mining:
Author: ITLESL
Publisher: Pearson Education India
Total Pages: 271
Release: 2012
Genre:
ISBN: 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 Mining and Reverse Engineering

Data Mining and Reverse Engineering
Author: Stefano Spaccapietra
Publisher: Springer
Total Pages: 0
Release: 1998-04-30
Genre: Computers
ISBN: 9780412822506

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Searching for Semantics: Data Mining, Reverse Engineering Stefano Spaccapietra Fred M aryanski Swiss Federal Institute of Technology University of Connecticut Lausanne, Switzerland Storrs, CT, USA REVIEW AND FUTURE DIRECTIONS In the last few years, database semantics research has turned sharply from a highly theoretical domain to one with more focus on practical aspects. The DS- 7 Working Conference held in October 1997 in Leysin, Switzerland, demon strated the more pragmatic orientation of the current generation of leading researchers. The papers presented at the meeting emphasized the two major areas: the discovery of semantics and semantic data modeling. The work in the latter category indicates that although object-oriented database management systems have emerged as commercially viable prod ucts, many fundamental modeling issues require further investigation. Today's object-oriented systems provide the capability to describe complex objects and include techniques for mapping from a relational database to objects. However, we must further explore the expression of information regarding the dimensions of time and space. Semantic models possess the richness to describe systems containing spatial and temporal data. The challenge of in corporating these features in a manner that promotes efficient manipulation by the subject specialist still requires extensive development.


Data Warehousing, Data Mining, & Olap

Data Warehousing, Data Mining, & Olap
Author: Berson
Publisher: Tata McGraw-Hill Education
Total Pages: 0
Release: 2004-03
Genre:
ISBN: 9780070587410

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Data Warehouse and Data Mining

Data Warehouse and Data Mining
Author: Dr. Jugnesh Kumar
Publisher: BPB Publications
Total Pages: 261
Release: 2024-01-25
Genre: Computers
ISBN: 9355517343

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Unveiling insights, unleashing potential: Navigating the depths of data warehousing and mining for a data-driven tomorrow KEY FEATURES ● Explore concepts ranging from fundamentals to advanced techniques of data warehouses and data mining. ● Translate business questions into actionable strategies to make informed decisions. ● Gain practical implementation guidance for hands-on learning. DESCRIPTION Data warehouse and data mining are essential technologies in the field of data analysis and business intelligence. Data warehouse provides a centralized repository of structured data and facilitates data storage and retrieval. Data mining, on the other hand, utilizes various algorithms and techniques to extract valuable patterns, trends, and insights from large datasets. The book explains the ins and outs of data warehousing by discussing its principles, benefits, and components, differentiating it from traditional databases. The readers will explore warehouse architecture, learn to navigate OLTP and OLAP systems, grasping the crux of the difference between ROLAP and MOLAP. The book is designed to help you discover data mining secrets with techniques like classification and clustering. You will be able to advance your skills by handling multimedia, time series, and text, staying ahead in the evolving data mining landscape. By the end of this book, you will be equipped with the skills and knowledge to confidently translate business questions into actionable strategies, extracting valuable insights for informed decisions. WHAT YOU WILL LEARN ● Designing and building efficient data warehouses. ● Handling diverse data types for comprehensive insights. ● Mastering various data mining techniques. ● Translating business questions into mining strategies. ● Techniques for pattern discovery and knowledge extraction. WHO THIS BOOK IS FOR From aspiring data analysts, data professionals, IT managers, to business intelligence practitioners, this book caters to a diverse audience. TABLE OF CONTENTS 1. Introduction to Data Warehousing 2. Data Warehouse Process and Architecture 3. Data Warehouse Implementation 4. Data Mining Definition and Task 5. Data Mining Query Languages 6. Data Mining Techniques 7. Mining Complex Data Objects


New Trends in Data Warehousing and Data Analysis

New Trends in Data Warehousing and Data Analysis
Author: Stanisław Kozielski
Publisher: Springer Science & Business Media
Total Pages: 365
Release: 2008-11-21
Genre: Business & Economics
ISBN: 9780387874302

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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.