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16 Business Intelligence → This chapter describes some of the basic ideas in business intelligence. This chapter contains the … following topics: Introduction to Data Warehousing and Business Intelligence Overview of Extraction
24 Advanced Business Intelligence Queries → This chapter illustrates techniques for handling advanced business intelligence queries. We hope to … makes a business intelligence query \"advanced\"? The label is best applied to multistep queries … . This chapter includes: Examples of Business Intelligence Queries
Examples of Business Intelligence Queries → The queries in this chapter illustrate various business intelligence tasks. The topics of the
Overview of Business Intelligence Features → This section describes the following business intelligence features: Data Warehousing Materialized … entire spectrum of business intelligence and advanced analytical applications. Oracle OLAP is fully … Also: Chapter 16, \"Business Intelligence\" for more information about Oracle Data
Data Warehouse Architecture → systems designed for a particular line of business. Figure 16-3 illustrates an example where
Transportable Tablespaces → Transportable tablespaces are the fastest way for moving large volumes of data between two Oracle databases. You can transport tablespaces between different computer architectures and operating systems. Previously, the most scalable data transportation mechanisms relied on moving flat files containing raw data. These mechanisms required that data be unloaded or exported into files from the source
SQL for Aggregation → Aggregation is a fundamental part of data warehousing. To improve aggregation performance in your warehouse, Oracle Database provides extensions to the GROUP BY clause to make querying and reporting easier and faster. Some of these extensions enable you to: Aggregate at increasing levels of aggregation, from the most detailed up to a grand total Calculate all possible combinations of aggregations
Overview of Data Mining → , and business planning. As of Oracle Database 11 g, Oracle Data Mining models are implemented as data
External Tables → External tables let you use external data as a virtual table that can be queried and joined directly and in parallel without requiring the external data to be first loaded in the database. You can then use SQL, PL/SQL, and Java to access the external data. External tables enable the pipelining of the loading phase with the transformation phase. The transformation process can be merged with the loading
Security → Because Oracle OLAP is completely embedded in Oracle Database, there is no administration learning curve as is typically associated with standalone OLAP servers. You can leverage your existing DBA staff, rather than invest in specialized administration skills. One major administrative advantage of Oracle's embedded OLAP technology is automated cube maintenance. With standalone OLAP servers, the burden
Reduced Costs → Business intelligence and analytical applications are dominated by actions such as drilling up and … delivers unmatched performance for typical business intelligence applications. Oracle OLAP queries
Introduction to Data Warehousing and Business Intelligence → business users. This section includes the following topics: Characteristics of Data Warehousing
Differences Between Data Warehouse and OLTP Systems → current state of each business transaction. Schema Design Data warehouses often use denormalized or
Overview of Materialized Views for Data Warehouses → One technique employed in data warehouses to improve performance is the creation of summaries. Summaries are special kinds of aggregate views that improve query execution times by precalculating expensive joins and aggregation operations prior to execution and storing the results in a table in the database. For example, you can create a table to contain the sums of sales by region and by product.
How Parallel Execution Works → When parallel execution is not used, a single server process performs all necessary processing for the sequential execution of a SQL statement. For example, to perform a full table scan (such as SELECT * FROM emp ), one process performs the entire operation, as illustrated in Figure 16-5. Figure 16-5 Serial Full Table Scan Description of \"Figure 16-5 Serial Full Table Scan \" Figure 16-6 illustrates
Characteristics of Data Warehousing → analyze what has occurred. Time Variant In order to discover trends in business, analysts need large
Change Data Capture → efficiently identifies and captures data that has been added to, updated, or removed from Oracle Database relational tables, and makes the change data available for use by applications. Oftentimes, data warehousing involves the extraction and transportation of relational data from one or more source databases into the data warehouse for analysis. Change Data Ca pture quickly identifies and processes
Overview of Bitmap Indexes in Data Warehousing → Bitmap indexes are widely used in data warehousing environments. The environments typically have large amounts of data and ad hoc queries, but a low level of concurrent DML transactions. For such applications, bitmap indexing provides: Reduced response time for large classes of ad hoc queries Reduced storage requirements compared to other indexing techniques Dramatic performance gains even on hardware
Unmatched Performance and Scalability → With Oracle OLAP, standard Oracle Database security features are used to secure your multidimensional data. In contrast, with a standalone OLAP server, administrators must manage security twice: once on the relational source system and again on the OLAP server system. Additionally, they must manage the security of data in transit from the relational system to the standalone OLAP system. Unmatched
Overview of Extraction, Transformation, and Loading (ETL) → unified information base for business intelligence. Additionally, the data volume in data warehouse … business analysis. To perform this operation, data from one or more operational systems must be extracted … business situation. The same is true for the time delta between two (logically) identical extractions