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Data Virtualization for Business Intelligence Systems: Revolutionizing Data Integration for Data Warehouses (Morgan Kaufmann Series on Business
86% of respondents would recommend this to a friend
HKD 360
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Data virtualization can help you accomplish your goals with more flexibility and agility.
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產品詳情
| Publisher | Morgan Kaufmann |
| Publication date | August 8, 2012 |
| Edition | 1st |
| Language | English |
| Print length | 296 pages |
| ISBN-10 | 0123944252 |
| ISBN-13 | 978-0123944252 |
| Item Weight | 1.4 pounds (640 grams) |
| Dimensions | 7.5 x 0.67 x 9.25 inches (19.1 x 1.7 x 23.5 cm) |
| Part of series | The Morgan Kaufmann Series on Business Intelligence |
Who Should Buy?
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Data Analysts
Data analysts seeking efficient ways to integrate and analyze data from multiple sources will benefit greatly from this book.
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Business Intelligence Teams
Teams working on business intelligence projects can utilize the insights on data virtualization to improve their data integration efforts.
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IT Professionals
IT professionals tasked with maintaining data warehouses will find valuable strategies for implementing data virtualization effectively.
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Beginners in Data
Complete newcomers to data management may struggle with advanced concepts presented without foundational knowledge in data systems.
產品敘述
Data Virtualization for Business Intelligence Systems: Revolutionizing Data Integration for Data Warehouses (Morgan Kaufmann Series on Business Intelligence)
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Storage & Retrieval Editorial Review
**** *Data Virtualization for Business Intelligence Systems: Revolutionizing Data Integration for Data Warehouses* by Rick van der Lans has garnered a positive reception from readers, particularly those new to or exploring data virtualization. The book is praised for its comprehensive and clearly articulated introduction to data virtualization, skillfully framing it within the context of Business Intelligence (BI) architecture. Readers appreciate how it employs practical examples and screenshots from various data virtualization vendors like Composite, Denodo, and Informatica, providing insight into the industry's landscape. The author is commended for adopting a vendor-neutral stance, which resonates well with professionals seeking an unbiased understanding of data virtualization technologies rather than a sales pitch. Such an approach aids readers in evaluating different platforms and planning their own data virtualization architectures effectively. Critics note the book's clear writing style and engaging narrative, making complex topics accessible while still delving into the technical particulars of data virtualization. Furthermore, readers value the forward-looking perspectives included, which feature insights from CTOs of leading data virtualization companies, thereby enhancing the book’s relevance to future developments in the field. Some reviewers suggest that while the book is currently an excellent resource, the rapidly evolving nature of the data virtualization landscape may lead it to age quickly, implying a need for readers to seek updated information in a few years. Overall, *Data Virtualization for Business Intelligence Systems* serves as a vital resource for professionals aiming to understand the principles and applications of data virtualization in the context of BI, affirming its place on recommended reading lists. **
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優點
- Clear and engaging writing style
- Comprehensive introduction to data virtualization
- Vendor-neutral perspective, avoiding sales bias
- Practical examples and screenshots from various vendors
- Effective resource for evaluating data virtualization platforms
- Insightful future projections from industry experts
缺點
- May age quickly due to fast-changing technologies
Product Price History
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HKD 360
現在訂購,約可在下列時間收貨: 星期五, 十月 16
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特色和優勢
- Learn how data virtualization servers work
- Optimize access to various data sources
- Understand the advantages and disadvantages of data virtualization
- Gain a comprehensive understanding of how data virtualization will make data warehouse environments more flexible
- Solve common data integration challenges using practical guidelines
- Gain insight into the relationship between data virtualization and data governance and information management
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