48 results about "Star schema" patented technology

Disclosed is a system, method, and apparatus for calculating metrics by using hierarchical level metadata to describe the various structures within the database. The hierarchical level metadata permit calculation of complex metrics by an analytical server which would otherwise be difficult or impossible. As a result of the way that the analytical server calculates the metrics, slicing and drilling are supported. Additionally, dimension and fact level security are also supported.

Disclosed is a data collection and analysis system that is capable of extracting data from various disparate sources, i.e., contact channels, storing the data and analyzing the data to show trends in the business operation. The data is stored in a data model that uses a star schema approach to providing a unified data source. Analyzed data can be made available to users on a nearly real time basis that allows the users to view trends in business operation and plan accordingly.

A method, computer program product, and data processing system for computer-aided design of multidimensional data warehouse schemas are disclosed. A preferred embodiment of the present invention provides a software tool for identifying a latent star schema structure within an existing database. This software tool performs a heuristic analysis of the existing database schema to locate potential keys and measurement fields. Database tables within the existing schema are scored heuristically as to their suitability as fact tables based on the key candidates and measurement fields. For each fact table, other tables from the existing schema are identified as possible dimension tables. Data from the database is then used to test the suitability of the fact tables and dimension tables. The identified fact tables and their associated dimension tables are then reported to the user to reveal a basic star schema structure, which can be used as a basis for further design.

A multi-dimensional business information accounting software engine accepts input of user defined business specific textual or numeric information and conventional financial accounting data and converts them to indexed star schema multi-dimensional computer data as a journal entry. Upon user request the journal entry is analyzed by relational or other database methodology to generate conventional accounting statements such as general ledger, balance sheet, cash flow statements, profit and loss statements and earned income statements for user specified time periods. The multi-dimensional business information accounting software engine can also generate accounting statements of sliced data according to a range of business specific numeric information or accounting statements pertinent to a textual business specific information for a specified time period, providing the user sensitivity of different business specific information on accounting statements, so that the user can modify his business practices on real time.

A database facility supports database join queries in a database environment having at least one database table divided into multiple partitions based on a partition key value. The facility determines whether the values in a table joined to the partitioned table place an implicit limitation on the partition key, and eliminates from query evaluation any partitions which do not satisfy the implicit limitation. Preferably, the database uses a star schema organization, in which implicit limitations in a relatively small dimension table are used to eliminate partitions in a relatively large fact table.

Disclosed is a data collection and analysis system that is capable of extracting data from various disparate sources, i.e., contact channels, storing the data and analyzing the data to show trends in the business operation. The data is stored in a data model that uses a star schema approach to providing a unified data source. Analyzed data can be made available to users on a nearly real time basis that allows the users to view trends in business operation and plan accordingly.

Techniques are described for optimizing a multi-fact star schema query to retrieve data from two or more fact tables of a database. The optimization techniques may include internally transforming a received multi-fact star schema query into a group of single-fact sub-queries, thereby reducing or eliminating certain constraints during query processing. The group of sub-queries may be enumerated to determine a query execution plan. The multi-fact star schema query may be executed according to the query execution plan to retrieve the data from the two or more fact tables of the database.

A method and system for optimizing a query in a snow flake schema (60) within a relational database. The schema (60) includes a fact table (12) and multiple dimension tables and a plurality of dimension levels, with at least one dimension table at each level. A logical node (310) comprised of a level one child dimension table (32) and all dimension tables (62) rooted at this level one child dimension table is created based upon the cumulative selectivity calculation for all of the dimension tables at each level of the database (210). Creation of the logical node reduces a snow flake schema to a star schema, thereby mitigating search space traversal.

A method, computer program product, and data processing system for computer-aided design of multidimensional data warehouse schemas are disclosed. A preferred embodiment of the present invention provides a software tool for identifying a latent star schema structure within an existing database. This software tool performs a heuristic analysis of the existing database schema to locate potential keys and measurement fields. Database tables within the existing schema are scored heuristically as to their suitability as fact tables based on the key candidates and measurement fields. For each fact table, other tables from the existing schema are identified as possible dimension tables. Data from the database is then used to test the suitability of the fact tables and dimension tables. The identified fact tables and their associated dimension tables are then reported to the user to reveal a basic star schema structure, which can be used as a basis for further design.

Disclosed embodiments of the present invention relate to a system and method for automatic generation of a star schema. The system and method may comprise categorizing a data field into one of a plurality of data field types, one of the data field types being an enumeration type data field. The system and method may further comprise developing dimensions for a table that represents an initial star schema design using the categorization of the data, detecting functional dependencies between the data field and other data fields, and refining the initial star schema design by modifying the table based on detected functional dependencies.

A system and method for ensuring large and frequent updates to a data warehouse. The process leverages a set of temporary staging tables to track the updates. A set of intermediate steps are performed to accomplish bulk deletions of the outdated changed records, and perform modifications to the map tables for models such as snowflake. Finally, bulk load operations load the updates and insert them into the final dimension tables. The process ensures performance comparable to insertion-only schemes with at most only slight performance degradation. Furthermore, a modified process is applied on the newfact data warehouse dimension model. The process can be readily adapted to handle star schema and other hierarchical data warehouse models.

The invention discloses methods and devices for generating cube metadata and query statements on the basis of an enhanced star schema. The method for generating the cube metadata on the basis of the enhanced star schema includes extracting dimensional reference from non-factual fact tables of the enhanced star schema comprising fact tables, a plurality of dimension tables of the fact tables and the non-factual fact tables; constructing hierarchical structure reference according to the dimension reference; combining the hierarchical structure reference with measure and hierarchical structures to generate the cube metadata. The measure is acquired from the fact tables and the dimension tables. The methods and the devices have the advantage that the non-factual fact tables are directly used with the fact tables and the dimension tables without being converted when the metadata are generated, and accordingly manual operation, storage spaces, dependency on knowledge of IT (information technology) / business modeling personnel and the like which are required when non-factual fact tables are converted in the prior art can be omitted.

An approach to processing data streams includes a new type dynamic database of stream star schema to accommodate high data stream rates for giga bits per second by reducing the insert time to a constant and a new type of data cube as nested binary tree to supports both data aggregates and data values.

The present invention provides a dimension table processing apparatus that efficiently derives a dimension hierarchy for a denormalized dimension table. The first information presenting means presents information on a plurality of fact tables included in a multidimensional database to an administrator as first information. The second information presenting means receives a fact table selected by the administrator from among the fact tables related to the first information, and presents information on dimension tables associated with the selected fact table in a star schema to the administrator as second information. The dimension hierarchy deriving means receives a dimension table selected by the administrator from among the dimension tables related to the second information as the one to be processed, calculates a predetermined evaluation value for each column in the dimension table to be processed based on data in each cell belonging to that column, and derives a dimension hierarchy of the columns, which consists of a plurality of hierarchical levels of the respective columns, based on the evaluation values thereof. The third information presenting means presents the dimension hierarchy for the dimension table to be processed derived by the dimension hierarchy deriving means to the administrator as third information. The approval receiving means receives a dimension hierarchy approved by the administrator based on the third information as an approved dimension hierarchy.

Describes the technology of automatically generating report templates based on the relational database storing multidimensional data according to the relational database schema. For example, a template generator may generate a base report template from a database schema, and then generate a user report template by importing the base report template. The template generator updates the user report template in response to modifications requested by the user and maintains an activity log to record the modifications. If the database schema has changed, the template generator automatically updates the user report templates by regenerating the base and user report templates and reapplying modifications from the activity log to the user report templates. As described here, the database schema can be a relational star schema.

Disclosed is a data collection and analysis system that is capable of extracting data from various disparate sources, i.e., contact channels, storing the data and analyzing the data to show trends in the business operation. The data is stored in a data model that uses a star schema approach to providing a unified data source. Analyzed data can be made available to users on a nearly real time basis that allows the users to view trends in business operation and plan accordingly.

A computer-implemented method is provided for defining interesting portions of a workflow of a business or other type of process. Using a tracking profile editor, a portion of a given workflow is selected and associated with a named process part. Items of payload data to be used in reports are selected from a message schema associated with the given workflow. A profile is generated based on the given workflow and the selected items of payload data. A tracking profile compiler receives the created tracking profile and generates a star schema, a flattened view and OLAP cube based on the tracking profile. An interceptor extracts monitored workflow events and stores event information to a tracking stream, based on the tracking profile. A tracking service extracts information pertaining to the monitored events from the tracking stream and stores the information in the queryable database. The OLAP cube and the flattened view are updated based on the information written to the queryable database.

An automated system for validating and refining a template warehouse star schema for a customized data source. The system based on automatically gathered information from the data source such as custom entities and constituent columns, data type and length of custom columns, custom entity keys, relationships of custom entities with other entities, relationships within custom entities, contribution of custom entities to specialized entities, update frequency of custom entities and columns including grouping of updates, frequently used expressions on custom columns and contribution of custom entities and columns to workflow and correlated attributes automatically determines facts, dimensions, dimension hierarchies, measures, workflow specific measures (if data source has workflows) and workflow correlated attribute specific measures (if data source has temporal, priority, ownership and progress tracking workflow correlated attributes) to validate and refine the star schema of the template warehouse to accommodate customizations of the data source.

The invention discloses a data exchange adapter and a system and a method for synchronizing data among heterogeneous systems, and relates to the technical field of mass data processing. With a star-like mode design principle, a set of data exchange adapter device located between different types of databases or file systems is established, then the mass data are synchronized effectively among different heterogeneous systems, and the original net-shaped data synchronization mode formed by maintaining and managing a series of complicated data import and export tools is replaced. In addition, the embodiment of the invention provides a set of unified open framework to support secondary development, a DataIn plug-in and a DataOut plug-in provided by the scheme can be used or required DataIn plug-in and DataOut plug-in are self-defined, so that the task of synchronizing any mass data among the different types of databases or file systems is rapidly executed.

A system and method for ensuring large and frequent updates to a data warehouse. The process leverages a set of temporary staging tables to track the updates. A set of intermediate steps are performed to accomplish bulk deletions of the outdated changed records, and perform modifications to the map tables for models such as snowflake. Finally, bulk load operations load the updates and insert them into the final dimension tables. The process ensures performance comparable to insertion-only schemes with at most only slight performance degradation. Furthermore, a modified process is applied on the newfact data warehouse dimension model. The process can be readily adapted to handle star schema and other hierarchical data warehouse models.

The present invention provides a dimension table processing apparatus that efficiently derives a dimension hierarchy for a denormalized dimension table. The first information presenting means presents information on a plurality of fact tables included in a multidimensional database to an administrator as first information. The second information presenting means receives a fact table selected by the administrator from among the fact tables related to the first information, and presents information on dimension tables associated with the selected fact table in a star schema to the administrator as second information. The dimension hierarchy deriving means receives a dimension table selected by the administrator from among the dimension tables related to the second information as the one to be processed, calculates a predetermined evaluation value for each column in the dimension table to be processed based on data in each cell belonging to that column, and derives a dimension hierarchy of the columns, which consists of a plurality of hierarchical levels of the respective columns, based on the evaluation values thereof. The third information presenting means presents the dimension hierarchy for the dimension table to be processed derived by the dimension hierarchy deriving means to the administrator as third information. The approval receiving means receives a dimension hierarchy approved by the administrator based on the third information as an approved dimension hierarchy.

A computer implemented method for data mining and providing business intelligence data including generating by an analytics server one or more dimensions from source data imported from a computer readable medium, wherein the one or more dimensions define categories into which portions of the normalized data can be grouped; generating by the analytics server one or more measures from the source data linked to the one or more dimensions; storing by the analytics server the one or more dimensions and the one or more measures in a plurality of tables arranged in one of a snowflake and a star schema; determining by the analytics server relationship information between one or more measures and one or more dimensions in each of the plurality of tables; storing by the analytics server the relationship information on the computer readable medium; calculating by the analytics server a total cost of at least one product based on the relationship information; and, querying by a computer system in communication with the analytics server for the change in total cost of the at least one product based on a change in any one of the measures.

Challenges associated with maintaining information about multiple instances of an activity are addressed. Separate database tables are maintained for data corresponding to active instances of an organization's activities and for data corresponding to inactive instances of an organization's activities. Multiple database tables can be maintained for data corresponding to inactive instances of an activity. In another aspect, data from the active instances table and one or more inactive instances tables are processed to generate combined analysis data.

A business intelligence solution tailored to health care services. Specifically, the present invention consists at least one Payor source as enterprise resource planning (ERP) / legacy engine integrated with plurality of data; a extract transform and load (ETL) engine designed for extracting data from said Enterprise resource planning (ERP) / legacy engine consisting of business metrics relating to performance of the business with its organized data in hierarchy; at least one LANDING PAD / staging layer having at least one staging data table; at least one analytic engine called STAR SCHEMA designed for reporting, analysis and planning of information based on business metric implemented; at least one TRANSACTIONA DATA MODEL for transforming data from said Payor source into web interface; designed to support business analytic activities such as healthcare data, financial data and business administration.

An embodiment of the present invention migrates data between source and target systems. Retrieved source data is mapped to corresponding data elements of a data design for a computer implemented scenario on a target system. One or more of the data elements of the data design are stored on the target system in a format different than a format of the retrieved data. Filters and transformations are generated based on the mapping and data design, and the retrieved data are converted to the format of the target system. One or more from a group of the mapping, filters, and transformations is adjusted in response to detecting at least one from a group of modifications to the data design and non-conforming data received from the one or more source systems. The converted data is stored for the corresponding data elements on the target system for use by the computer implemented scenario.

A computer-implemented method is provided for defining interesting portions of a workflow of a business or other type of process. Using a tracking profile editor, a portion of a given workflow is selected and associated with a named process part. Items of payload data to be used in reports are selected from a message schema associated with the given workflow. A profile is generated based on the given workflow and the selected items of payload data. A tracking profile compiler receives the created tracking profile and generates a star schema, a flattened view and OLAP cube based on the tracking profile. An interceptor extracts monitored workflow events and stores event information to a tracking stream, based on the tracking profile. A tracking service extracts information pertaining to the monitored events from the tracking stream and stores the information in the queryable database. The OLAP cube and the flattened view are updated based on the information written to the queryable database.

In one embodiment the present invention includes a method comprising receiving a data filter for filtering a collection of data, wherein the collection of data is configured as a star schema including a fact table and dimension tables. The data filter is applied against the dimension tables to generate a modified dimension table. The modified dimension tables are applied against the fact table to produce a modified fact table. The data filter is then applied against the modified fact table to generate a second modified fact table, which is the output of the process.

A system and method for ensuring large and frequent updates to a data warehouse. The process leverages a set of temporary staging tables to track the updates. A set of intermediate steps are performed to accomplish bulk deletions of the outdated changed records, and perform modifications to the map tables for models such as snowflake. Finally, bulk load operations load the updates and insert them into the final dimension tables. The process ensures performance comparable to insertion-only schemes with at most only slight performance degradation. Furthermore, a modified process is applied on the newfact data warehouse dimension model. The process can be readily adapted to handle star schema and other hierarchical data warehouse models.