Abstract: Computer-readable media, systems, and methods for building a multidimensional data cube having one or more high-cardinality attributes are described. In embodiments, data is extracted from one or more databases. It is determined that one or more instances of the data are fact data and one or more instances of the data are dimension data. Each member of the fact data is one instance of a dimension and each instance of the dimension data includes an attribute for grouping the fact data. Moreover, in embodiments it is determined that one or more instances of the dimension data are high-cardinality attributes. The one or more high-cardinality attributes are processed with fact data and stored in fact tables on a computer storage medium.

Abstract: Maintaining data used for performing “what-if” analysis is disclosed. The systems and methods of the invention define an efficient mechanism allowing a user to specify how base values from a database are to be changed. The changes can be held in a local delta cache which is only exposed to a single user, leaving the base data unchanged. The changes can also be maintained in a write-back partition, which results in the changes being exposed to all clients of the database. Values in the write-back partition can be selectively rolled back if required.

Abstract: The subject invention pertains to interaction with multidimensional data. More specifically, interactions can be constrained to a limited subset of a multidimensional data cube, namely a subcube. Subsequent to or concurrently with subcube creation, query execution or other interactions such as calculations can be consolidated or restricted to the smaller subcube query space rather than the typically enormous main cube. Multiple subcubes can also be created and nested to gradually reduce the query space. Deletion of one subcube can cause a reversion back to a previously defined or hierarchical parent subcube.

Abstract: Systems and methodologies for identification of factors that cause significant shifts in transactions in a relational store and/or OLAP environment. Transactions are grouped into significant categories defined across the whole data space, to detect interesting sub spaces transactions. Subsequently, sub spaces that show strong variance between two slices can be selected, followed by grouping the subspaces in sub reports to measure the coverage for each sub report. A final report can then be generated that contains list of sub-reports detected in the previous acts.

Abstract: Systems, clients, servers, methods, and computer-readable media of varying scope are described in which, two extensions for a multidimensional database query language extensions, AddCalculatedMembers and StripCalculatedMembers, allow an OLAP client to easily control the integration of calculated members into the results of OLAP database queries. The OLAP client need not be aware of the details of which calculated members are defined within the multidimensional database and need not explicitly request the inclusion or removal of each calculate member from the output data set of the query.

Abstract: A system and method for analytically modeling data in a data cube is disclosed. A first dimension of the data cube is modeled according to a first table having a referencing attribute. A second dimension of the data cube is modeled according to a second table having a referenced attribute. The first dimension is tied to the second dimension according to the referencing attribute and the referenced attribute.

Abstract: A system and method for analytically modeling data with related attributes is disclosed. A single dimension is used to provide data according to each of the related attributes, and, thus, may be said to play the role of each related attribute depending on a received query. The measure of the analytical data model is tied to the dimension according to both data attributes to allow the measure to be analyzed by the dimension according to both attributes.

Abstract: A system and method for analytically modeling data organized according to non-referred attributes is disclosed. Data stored in a first and a second relational data table is analytically modeled in a data cube. The first table organizes a first type according to a first attribute. The second table organizes a second type according to the first attribute and a second attribute. A first measure is modeled according to the first type of the first table. A first dimension is modeled according to the first attribute of the first and second tables. A second dimension is modeled according to the second attribute of the second table. The first measure is tied to the first dimension according to the first attribute of the first table to allow the first measure to be analyzed by the first dimension according to the first attribute. The first measure is tied to the second dimension by, for each entry of the first dimension, allocating the entry to each entry of the second dimension in a predetermined manner.

Abstract: The present invention leverages MOLAP performance for ROLAP objects (dimensions, partitions and aggregations) by building, in a background process, a MOLAP equivalent of that object. When the background processing completes, queries are switched from ROLAP queries to MOLAP queries. When changes occur to relevant relational objects (such as tables that define content of OLAP objects), an OLAP object is switched back to a ROLAP mode, and all relevant caches are dropped while, as a background process, a new MOLAP equivalent is created.

Abstract: A system and method for analytically modeling data from different measure groups onto a single cube are disclosed. The single cube preferably includes a first measure associated with a first measure group with a first set of corresponding dimensions. The single cube preferably also includes a second measure associated with a second measure group with a second set of corresponding dimensions. The single cube preferably also includes each dimension in both the first and second set of dimensions. Each measure is preferably tied to each corresponding dimension according to data in an underlying relational data table. Each measure is preferably tied to each non-corresponding dimension according to an approximation.

Abstract: According to one aspect, key performance indicators and the accompanying key performance indicator elements may be displayed in a task pane to enable a user to select one or more the key performance indicator elements for use in generating a data summary table. In one example, the key performance indicators of a dataset are identified, and each of the associated key performance indicator elements associated with that key performance indicator is also identified. A key performance indicator may be obtained from any source, including the dataset to which it pertains. Additionally, a name of the identified key performance indicator is determined. The determined name and each of the identified key performance indicator elements are displayed in an organized manner as to enable a user easy selection of the key performance indicator and/or the key performance indicator elements.

Abstract: A measure expression may include a relationship between measures defined by an arithmetic operation. A query may request a calculation of the measure expression over a selected range of attributes. The request may be processed by retrieving all rows comprising data within the selected range of attributes for each measure in the expression through a single access to an associated table.

Abstract: The present invention leverages MOLAP performance for ROLAP objects (dimensions, partitions and aggregations) by building, in a background process, a MOLAP equivalent of that object. When the background processing completes, queries are switched from ROLAP queries to MOLAP queries. When changes occur to relevant relational objects (such as tables that define content of OLAP objects), an OLAP object is switched back to a ROLAP mode, and all relevant caches are dropped while, as a background process, a new MOLAP equivalent is created.

Abstract: The present invention leverages MOLAP performance for ROLAP objects (dimensions, partitions and aggregations) by building, in a background process, a MOLAP equivalent of that object. When the background processing completes, queries are switched from ROLAP queries to MOLAP queries. When changes occur to relevant relational objects (such as tables that define content of OLAP objects), an OLAP object is switched back to a ROLAP mode, and all relevant caches are dropped while, as a background process, a new MOLAP equivalent is created.

Abstract: The present invention leverages MOLAP performance for ROLAP objects (dimensions, partitions and aggregations) by building, in a background process, a MOLAP equivalent of that object. When the background processing completes, queries are switched from ROLAP queries to MOLAP queries. When changes occur to relevant relational objects (such as tables that define content of OLAP objects), an OLAP object is switched back to a ROLAP mode, and all relevant caches are dropped while, as a background process, a new MOLAP equivalent is created.

Abstract: Maintaining data used for performing “what-if” analysis is disclosed. The systems and methods of the invention define an efficient mechanism allowing a user to specify how base values from a database are to be changed. The changes can be held in a local delta cache which is only exposed to a single user, leaving the base data unchanged. The changes can also be maintained in a write-back partition, which results in the changes being exposed to all clients of the database. Values in the write-back partition can be selectively rolled back if required.

Abstract: Maintaining data used for performing “what-if” analysis is disclosed. The systems and methods of the invention define an efficient mechanism allowing a user to specify how base values from a database are to be changed. The changes can be held in a local delta cache which is only exposed to a single user, leaving the base data unchanged. The changes can also be maintained in a write-back partition, which results in the changes being exposed to all clients of the database. Values in the write-back partition can be selectively rolled back if required.

Abstract: A method, system, and apparatus are provided for exposing and utilizing workbooks as server data sources. The system includes a client computer capable of executing a spreadsheet application program for creating a workbook including one or more worksheets. The workbook may be published to a server computer where the contents of the workbook are exposed as a multi-dimensional data source. The server computer allows client applications to discover and connect to the workbook as a multi-dimensional, data source, such as a cube.

Abstract: The subject invention pertains to systems and methods that facilitate generation of a database to support a multidimensional model. A database schema is generated in a top-down fashion. In particular, multidimensional structures and attributes such as cubes and dimensions can be defined. From such definition, a proposed database schema can be produced. This schema can subsequently be modified prior to or after populating the database. For example, a table or column could be added. Thereafter, the cubes and dimensions could be altered and a modified schema generated that preserves changes made to the schema. Accordingly, the subject systems and methods disclose an iterative approach that supports both top-down and bottom-up multidimensional database design.

Abstract: A system that facilitates one or more of querying and updating a multi-dimensional structure comprises a component that receives a statement in a declarative language relating to a typed object associated with a multi-dimensional structure. A conversion component analyzes context associated with the statement and automatically converts the object to a disparate type as a function of the analysis. For example, an execution engine can comprise the conversion component, and the execution engine can be an Online Analytical Processing (OLAP) engine.