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There are many limitations with which a view must comply to be converted to an indexed view: The view must be created using the With Schemabinding option. The view must reference only tables not other views, derived tables, rowset functions, or subqueries. All base tables must have the same owner as the view. The view cannot join tables from more than one database. The view cannot contain an outer or self-join. The view cannot have a Union clause, Top clause, Order By clause, or Distinct keyword. Some aggregate functions are not allowed: Count(*) [use Count_Big(*) instead], Avg(), Max(), Min(), Stdev(), Stdevp(), Var(), or Varp(). But all of these aggregate functions can be reengineered using valid functions [such as Sum() and Count_Big(*)]. If a query contains a Group By clause, it must contain Count_Big(*) in the Select list. The view and all base tables must be created with Set Ansi_Nulls On. All tables and user-defined functions in the view must be referenced using two-part names (owner.dbobject).

1

un s most advanced certification program in Java technology is the Sun Certified Enterprise Architect (SCEA) for Java 2 Platform. This book provides information that you will need to prepare for the SCEA exam. To pass the certification exam, you should be familiar with the fundamentals of applications programming and should have some proficiency in Java programming. Additionally, you should know specific enterprise technologies. All of these topics are covered in the book s chapters and on the CD accompanying the book:

n Basic principles of enterprise architectures n Object-oriented design using (UML) n Two-tier, three-tier, and n-tier common architectures n Legacy connectivity n EJB and container models n Protocols (HTTP, HTTPS, IIOP, JRMP) n Applicability of JEE n Design patterns n Messaging n Internationalization n Security n Enterprise architecture case study (using UML)

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Analytic Databases and Dimensional Design 3 Dimensional Design 3 Purpose 3 Measurement and Context 5 Facts and Dimensions 6 Grouping Dimensions and Facts 8 The Star Schema 10 Dimension Tables 10 Keys and History 11 Fact Tables 12 Using a Star Schema 12 Querying Facts 13 Browsing Dimensions 14 Guiding Principles 15 Summary 16 Further Reading 16 Data Warehouse Architectures 17 Inmon s Corporate Information Factory 18 Kimball s Dimensional Data Warehouse 20 Stand-Alone Data Marts 22 Architecture and Dimensional Design 24 Contrasting the Approaches 24 The Common Element 26 Terms Used in This Book 27 Summary 28 Further Reading 28 Stars and Cubes 29 Dimension Table Features 29 Surrogate Keys and Natural Keys 30 Rich Set of Dimensions 32 Grouping Dimensions into Dimension Tables 35.

Eleven-plus years into its life, Java is now the mature technology most commonly used behind the strategic scenes for an enterprise. After years in which Java development seemed to be reserved primarily for Internet applications, larger firms in the corporate world are using Java as the language of choice over C and COBOL for most of their new development, including but not limited to messaging, back-end night cycle functions such as database repair and warehousing, and data capture from external data feeds. Java s appeal lies not only in its affinity for network and distributed computing (although Intranet, Extranet, and Internet applications remain the major focus of Java development) but also in Java s other qualities, such as ease of programming and cross-platform capabilities the write once, run anywhere promise.

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