Abstract: In accordance with an embodiment, described herein is a system and method for providing query acceleration with a computing environment such as, for example, a business intelligence environment, database, data warehouse, or other type of environment that supports data analytics. A middle layer is provided as a long-term table data storage format; and one more acceleration formats, or acceleration tables, can be periodically regenerated from the middle layer, wherein a determination can be made as to whether an accelerated table exists for a dataset table, and if so, then the accelerated table is used to process the query.

Abstract: Techniques for managing real-time business event analysis and monitoring are provided. In some examples, a logical request may be received at a business intelligence server configured with a continuous query service. Additionally, the continuous query service may be configured to translate the logical request into a physical request. Further, business intelligence information may be provided based at least in part on querying against an event data stream with a continuous query configured based at least in part on the physical request translated by the continuous query service.

Abstract: Techniques for managing real-time business event analysis and monitoring are provided. In some examples, a logical request may be received at a business intelligence server configured with a continuous query service. Additionally, the continuous query service may be configured to translate the logical request into a physical request. Further, business intelligence information may be provided based at least in part on querying against an event data stream with a continuous query configured based at least in part on the physical request translated by the continuous query service.

Abstract: Techniques for managing real-time business event analysis and monitoring are provided. In some examples, a logical request may be received at a business intelligence server configured with a continuous query service. Additionally, the continuous query service may be configured to translate the logical request into a physical request. Further, business intelligence information may be provided based at least in part on querying against an event data stream with a continuous query configured based at least in part on the physical request translated by the continuous query service.

Abstract: A business intelligence (BI) server is described that supports data and schemas stored in multiple languages. The BI server implements a lookup table and lookup function that allows users to work with queries in different languages. When the user logs in, a session object is created for the user, which maintains the state information. A session variable specifies the language currently being used by the user. The BI server can inspect this session variable to determine the language of the user and perform the lookup translations as necessary. For example, if the language used by the session is different from the language of the base table storing the necessary information, the BI server can perform a translation by invoking a lookup function. The execution of the lookup can include performing a join operation of the base table with the lookup table to yield a translated value requested by the query.

Abstract: Techniques for managing real-time business event analysis and monitoring are provided. In some examples, a logical request may be received at a business intelligence server configured with a continuous query service. Additionally, the continuous query service may be configured to translate the logical request into a physical request. Further, business intelligence information may be provided based at least in part on querying against an event data stream with a continuous query configured based at least in part on the physical request translated by the continuous query service.

Abstract: A business intelligence (BI) server maintains a plurality of metadata objects to support the extract, transform and load (ETL) processes. These metadata objects includes a transparent view object, which takes a joined set of source tables and represents a data shape of the joined set of source tables using a transformation, and a ETL mapping association object that maps the transformation contained in the transparent view object to a target table. The BI server can then orchestrate the movement of data from source systems into the target data warehouses in a source and target system agnostic way.

Abstract: An administration tool can be used to provide data flexibility in a business intelligence (BI) server that is associated with a data warehouse. The administration tool can display one or more data objects that are adapted to be imported from an application framework into a physical model maintained on the BI server. The administration tool can further map the one or more data objects in the physical model into a logical model, also maintained on the BI server, which corresponds to at least one target table in the data warehouse. Additionally, the administration tool can publish an extension input to an extender associated with the data warehouse based on the logical model, wherein the extender operates to generate one or more metadata extensions based on the extension input.

Abstract: Embodiments implement a plug-in architecture supporting adding new data sources to a legacy federated database without the need to recode a federated database manager software module. The federated database manager software module includes an administrative tool and a plug-in framework for interfacing with a data source cartridge. The data source cartridge supplies metadata including a feature table of a newly added data source to the framework and creates a physical query for the newly added data source based on an execution plan generated by the federated database manager software module. The administrative tool generates presentation panes including new data sources added to the legacy federated database.

Abstract: Embodiments implement a plug-in architecture supporting adding new data sources to a federated database without the need to recode a federated database manager software module. The federated database manager software module includes a plug-in framework for interfacing with a data source cartridge. The data source cartridge supplies metadata including a feature table of a newly added data source to the framework and creates a physical query for the newly added data source based on an execution plan generated by the federated database manager software module. The data source cartridge returns the result set of the query of the new added data source to the federated database manager software module.

Abstract: An input extension specification can be generated, via an administration tool on a business intelligence (BI) server, for an extender associated with a data warehouse in order to extend the data warehouse. The administration tool can request for data flow information of the data warehouse from the extender. The data flow information indicates the mapping relationship between one or more source data objects and one or more target tables in the data warehouse. The administration tool further allows a user to select said one or more target tables in the data warehouse to be extended based on the data flow information, and builds the input extension specification for the extender.

Abstract: Embodiments implement a plug-in architecture supporting adding new data sources to a legacy federated database without the need to recode a federated database manager software module. The federated database manager software module includes an administrative tool and a plug-in framework for interfacing with a data source cartridge. The data source cartridge supplies metadata including a feature table of a newly added data source to the framework and creates a physical query for the newly added data source based on an execution plan generated by the federated database manager software module. The administrative tool generates presentation panes including new data sources added to the legacy federated database.

Abstract: Embodiments implement a plug-in architecture supporting adding new data sources to a federated database without the need to recode a federated database manager software module. The federated database manager software module includes a plug-in framework for interfacing with a data source cartridge. The data source cartridge supplies metadata including a feature table of a newly added data source to the framework and creates a physical query for the newly added data source based on an execution plan generated by the federated database manager software module. The data source cartridge returns the result set of the query of the new added data source to the federated database manager software module.

Abstract: Systems and methods are described for performing a SQL bypass in a business intelligence (BI) server environment. The BI server initially receives a SQL query and constructs an extensible markup language (XML) representation of the SQL query. The XML representation is sent to an application server that hosts an application developer framework (ADF). The ADF receives the XML representation of the SQL query and constructs a composite view object at runtime, to access the appropriate data. It then generates a database-specific query based on the composite view object and returns it to the BI server. The BI server replans the database-specific query and sends it to a database storing the data.

Abstract: Techniques for managing real-time business event analysis and monitoring are provided. In some examples, a logical request may be received at a business intelligence server configured with a continuous query service. Additionally, the continuous query service may be configured to translate the logical request into a physical request. Further, business intelligence information may be provided based at least in part on querying against an event data stream with a continuous query configured based at least in part on the physical request translated by the continuous query service.

Abstract: A business intelligence (BI) server and repository are described which support a set of customized and/or calculated data members. In accordance with an embodiment, the BI server maintains a connection to a plurality of data sources which may store a set of dimension members. The data source can be relational, file storage based, multidimensional and other types. In accordance with an embodiment, the BI server can accept queries from the user that contain calculated members as a parameter. The calculated member is defined by an expression including multiple dimension members and one or more arithmetic operators. The BI server can parse and validate the query and rewrite the query for the data source. After the query is rewritten and optimized, it is executed against the data source and a set of results is received.

Abstract: An extender associated with a data warehouse can support metadata extension for the data warehouse. The extender can create an ETL extension plan for extending the data warehouse. The ETL extension plan includes one or more ETL plan elements that indicate extensions on ETL metadata objects. The one or more ETL plan elements within the ETL extension plan can be ordered, and ETL metadata extension can be performed based on the ETL extension plan.

Abstract: A business intelligence (BI) server and repository are described which support a set of hierarchical relationships among the data. The BI server receives user input specifying a set of parent-child or other ancestral relationship among a set of data in a data source. The BI server generates a set of SQL queries and executes the queries to pre-populate a set of tables which specify the parent child relationships among the data in the data source. One such table is a parent-child relationship closure table that defines the inter-member relationships among the data members. Once the tables are populated, the BI server uses the closure tables to answer queries that require knowledge of the ancestral relationships among data.

Abstract: A business intelligence (BI) server and repository are described which support a set of hierarchical relationships among the data. The BI server receives user input specifying a set of parent-child or other ancestral relationship among a set of data in a data source. The BI server generates a set of SQL queries and executes the queries to pre-populate a set of tables which specify the parent child relationships among the data in the data source. One such table is a parent-child relationship closure table that defines the inter-member relationships among the data members. Once the tables are populated, the BI server uses the closure tables to answer queries that require knowledge of the ancestral relationships among data.

Abstract: Systems and methods are described for performing a SQL bypass in a business intelligence (BI) server environment. The BI server initially receives a SQL query and constructs an extensible markup language (XML) representation of the SQL query. The XML representation is sent to an application server that hosts an application developer framework (ADF). The ADF receives the XML representation of the SQL query and constructs a composite view object at runtime, to access the appropriate data. It then generates a database-specific query based on the composite view object and returns it to the BI server. The BI server replans the database-specific query and sends it to a database storing the data.