Data warehousing and knowledge discovery
Mukesh Mohania
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at 250 WPM7h 18m
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Data warehousing and knowledge discovery
by Mukesh Mohania, A Min Tjoa, Yahiko Kambayashi
Published
October 2, 2000
Publisher
Springer
Pages
438
ISBN-13
9783540679806
ISBN-10
3540679804
Description
Data Warehousing and Knowledge Discovery: Second International Conference, DaWaK 2000 London, UK, September 4–6, 2000 Proceedings<br />Author: Yahiko Kambayashi, Mukesh Mohania, A. Min Tjoa<br /> Published by Springer Berlin Heidelberg<br /> ISBN: 978-3-540-67980-6<br /> DOI: 10.1007/3-540-44466-1<br /><br />Table of Contents:<p></p><ul><li>The Design and Development of a Logical System for OLAP </li><li>Applying Vertical Fragmentation Techniques in Logical Design of Multidimensional Databases </li><li>Space-Efficient Data Cubes for Dynamic Environments </li><li>On Making Data Warehouses Active </li><li>Supporting Hot Spots with Materialized Views </li><li>Evaluation of Materialized View Indexing in Data Warehousing Environments </li><li>View Derivation Graph with Edge Fitting for Adaptive Data Warehousing </li><li>On the Importance of Tuning in Incremental View Maintenance: An Experience Case Study </li><li>BEDAWA - A Tool for Generating Sample Data for Data Warehouses </li><li>DyDa: Dynamic Data Warehouse Maintenance in a Fully Concurrent Environment </li><li>Scalable Maintenance of Multiple Interrelated Data Warehousing Systems </li><li>View Maintenance for Hierarchical Semistructured Data </li><li>Maintaining Horizontally Partitioned Warehouse Views </li><li>Funding Research in Data Warehousing and Knowledge Discovery EPROS: The European Plan for Research in Official Statistics </li><li>Elimination of Redundant Views in Multidimensional Aggregates </li><li>Data Cube Compression with QuantiCubes </li><li>History-Driven View Synchronization </li><li>A Logical Model for Data Warehouse Design and Evolution </li><li>An Alternative Relational OLAP Modeling Approach </li><li>Functional Dependencies in Controlling Sparsity of OLAP Cubes</li></ul>
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Frequently Asked Questions
How many pages are in Data warehousing and knowledge discovery?
This edition of Data warehousing and knowledge discovery has approximately 438 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.
How long does it take to read Data warehousing and knowledge discovery?
For most readers, Data warehousing and knowledge discovery typically takes between 9h 8m and 6h 5m to complete. This is based on the book's length of approximately 109,500 words and common reading speeds.
Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 7h 18m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 15 days • Estimated word count: 109,500 words
Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.
What is the word count of Data warehousing and knowledge discovery?
The estimated word count for Data warehousing and knowledge discovery is approximately 109,500 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.
This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.
Who is the author of Data warehousing and knowledge discovery?
Data warehousing and knowledge discovery was written by Mukesh Mohania, A Min Tjoa, Yahiko Kambayashi.
When was Data warehousing and knowledge discovery published?
The publication date for this specific edition is October 2, 2000. The original work may have been published on a different date.