Generally, the two authors, Arun Sen and Atish P. Sinha are concerned about the growing use of data in every day business operations especially in the making of both of long-term and short-term decisions. In doing their analysis, the two authors realize that the best way to give a deeper insight on data integration technologies is by looking at the data warehousing technologies which by their standard serves as the nerve center of data management.
One of the outstanding issues in this book is the definition of technology warehousing which is explicitly done using several variables such as subject oriented, integration and time variant among others. All these subsets when joined together give the concept of warehousing technologies a complete meaning. Of these variables, the authors sought to induce to readers something very important which might have been illusive to many people in the technology world. That is, they realized that time variance and non-volatility are the two single most ingredients that are essential for the overall effectiveness of any technology warehousing.
In order to make their study more concrete and extensive, Sen and Sinha began by showing some of the usual tasks performed by warehousing technologies where they equivocally realize that all warehousing methodologies have four common tasks of architecture design, business requirements analysis, data design, implementation and deployment. The book further disintegrates the tasks and talks of what is embedded in each one. For instance, they divided data into two useful apparatus of data modeling and normalization. Further, data modeling which is a subset of data design is further refined into relational entry and dimensional modeling. The subdivisions does not end data modeling but continues through to dimensional modeling which is categorized into two units of fact table and several chains of tables. It is important o underscore the fact that Sen and Sinha are providing a critical, well thought and researched work that breaks down warehousing technology which is a mega topic into smaller particles that cane be easily digested even with the least students are readers.
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I should say that the focal point of this book is found in the comparison the scholars have put on the different types of warehousing technologies. They have identified fifteen different kinds of warehousing technologies which conceptually I find convincing and appropriate for proper analysis. Most importantly, the book does not only look at the fifteen types of warehousing individually, but gives them more weight by studying them within a confine of three fronts. These fronts are core technology vendors, infrastructure vendors and information modeling companies. What all these development mean is that they have the capacity of giving exclusive knowledge that allows for total analysis of the different types of warehousing technologies. I say kudos to the authors for offering a more simplistic analysis of the various typologies of warehousing technologies in a manner that even a non technology guru can understand and be able to make a decision on which kind of typology is best suited for his her needs.
Reading throughout the book, it becomes evident that even the two authors are aware that the filed of data warehousing technologies is still a young filed that is continually growing day by day. As such, they make it clear that there is no universal methodology that resonates throughout the world.