1162 results about "Multi dimensional data" patented technology

A spreadsheet user-interfaced web-based business data publishing system allows users to input and visualize field data and analytical results with interactive charts through a familiar MS-EXCEL user interface. A plug-in module associated with the user's browser and EXCEL application enables a background, web-services connection over the Internet to a management sub-system which extracts, transforms, and publishes data. Charts are customized using a WYSIWYG interface, and business dashboards are constructed through a simple drag-n-drop process. An account management system is included with access control to protect information security. The system is used for visualizing data managing reports, providing special tools to use SAP data, access Query Cubes in SAP BW, and standard and custom R/3 reports. Once data has been extracted from SAP, it is transformed, merged with other data sources, and published as a dashboard or in a business portal. Its management and configuration functions are suited for enterprise reporting and sharing business data.

A GUI is disclosed including a set of visualization routines designed to improve display, visualization and manipulation of multi-dimensional data. Many of the routines combine 2D and 3D renderings with domain selecting criteria and stacking criteria with line segments connecting variable values between records in a given dataset or between corresponding variable values in records of related datasets. The GUI also employs active, persistent and slider variables to probe variable relationships, group relationships and dataset relationships.

Improved method of and apparatus for aggregating data elements in multidimensional databases (MDDB). In one aspect of the present invention, the apparatus is realized in the form of a high-performance stand-alone (i.e. external) aggregation server which can be plugged-into conventional OLAP systems to achieve significant improments in system performance. In accordance with the principles of the present invention, the stand-alone aggregation server contains a scalable MDDB and a high-performance aggregation engine that are integrated into the modular architecture of the aggregation server. The stand-alone aggregation server of the present invention can uniformly distribute data elements among a plurality of processors, for balanced loading and processing, and therefore is highly scalable. The stand-alone aggregation server of the present invention can be used to realize (i) an improved MDDB for supporting on-line analytical processing (OLAP) operations, (ii) an improved Internet URL Directory for supporting on-line information searching operations by Web-enabled client machines, as well as (iii) diverse types of MDDB-based systems for supporting real-time control of processes in response to complex states of information reflected in the MDDB. In another aspect of the present invention, the apparatus is integrated within a database management system (DBMS). The improved DBMS can be used to realize achieving a significant increase in system performance (e.g. deceased access/search time), user flexibility and ease of use. The improved DBMS system of the present invention can be used to realize an improved Data Warehouse for supporting on-line analytical processing (OLAP) operations or to realize an improved informational database system, operational database system, or the like.

A multi-dimensional database and indexes and operations on the multi-dimensional database are described which include video search applications or other similar sequence or structure searches. Traversal indexes utilize highly discriminative information about images and video sequences or about object shapes. Global and local signatures around keypoints are used for compact and robust retrieval and discriminative information content of images or video sequences of interest. For other objects or structures relevant signature of pattern or structure are used for traversal indexes. Traversal indexes are stored in leaf nodes along with distance measures and occurrence of similar images in the database. During a sequence query, correlation scores are calculated for single frame, for frame sequence, and video clips, or for other objects or structures.

A method and system for producing graphics. A hierarchical structure of a database is determined. A visual table, comprising a plurality of panes, is constructed by providing a specification that is in a language based on the hierarchical structure of the database. In some cases, this language can include fields that are in the database schema. The database is queried to retrieve a set of tuples in accordance with the specification. A subset of the set of tuples is associated with a pane in the plurality of panes.

A software visualization tool consistent with the present invention integrates OLAP functionality with focus+context based techniques for navigation through and inspection of large multidimensional datasets. Focus+context based navigation techniques are used to increase the clarity and information content provided to the user. The visualization tool supports a number of operations of the data set, including: select-slice, aggregation, promote/demote, repeat-variables, and sort.

Systems or apparatus, methods, data structures and/or computer programs are provided for implementing an OLAP system that has increased query execution speed, requires reduced data storage capacity for an OLAP system and/or facilitates scaling of an OLAP system to large data cubes. The OLAP system can advantageously be implemented as an all-main memory OLAP system.

An improved method of partitioning and indexing multi-dimensional data that maps the data to one-dimensional values according to the sequence in which an approximation of a Hilbert space-filling curve passes through all of the points corresponding to potential multi-dimensional data in a data space. Data is partitioned into pages, each corresponding to a length of Hilbert curve. A page identifier is the sequence of the first point on its corresponding Hilbert curve section. The mapping orders data and also orders the data pages that contain data within a database. Mapping multi-dimensional data to one-dimensional values enables the data to be indexed using any one-dimensional index structure. The practical application of the indexing method is made viable and useful by the provision of a querying algorithm enabling data to be selectively retrieved in response to queries wherein all or some of the data that lies within a rectangular space within multi-dimensional space is required to be retrieved. The querying algorithm identifies pages whose corresponding curve sections intersect with a query region. The first intersecting page is found by calculating the lowest one-dimensional value corresponding to a possible multi-dimensional data value or point within the query region, and looking up in the index to find which page may contain this point. The next intersecting page, if it exists, is found by calculating the lowest one-dimensional value equal to or greater than the identifier of the next page to the one just identified. This new lowest one-dimensional, if found, is used to look up in the index and find the next page intersecting with the query region. Subsequent pages to be found, if any, are determined in a similar manner until no more are found. Pages found to intersect the query region can be searched for data lying within the query region.

A method and system for performing data analysis where multiple, categorical dimensions and statistical measures are used. The method includes preparing multi-dimensional data into nodes and arranging them logically in the form of a partial-order database. The database may then be traversed by a data-mining tool, or queried in an OLAP manner. Queries are answered through a process of associative partial-order search, which includes optional support for “children-of” requests, and optional support for fuzzy pattern-matching. By aggregating measures on-the-fly, this method is able to preform well without requiring a large number of summary nodes, when taken as a percentage of the total node count.

Disclosed is a method, system, and program for query processing. Metadata for a facts metadata object and one or more dimension metadata objects that are associated with the facts metadata object is stored. A view with columns for one or more measures in the facts metadata object and one or more attributes in the one or more dimension metadata objects is constructed. Additional metadata that describes roles of columns in the fact and dimension metadata objects is generated.

Also disclosed is a computer-readable medium for storing data for access by a program. A data structure stored in the computer-readable medium includes data for use by the program. The data includes a cube model metadata object that includes a facts metadata object, one or more dimension metadata objects, and one or more join metadata objects that describe how one or more tables in the facts metadata object and one or more tables in the one or more dimension metadata objects are joined. The data also includes a cube metadata object that represents a subset of the cube model metadata object and comprises a view with columns for one or more measures of one of the facts metadata objects and one or more attributes of one or more of the dimension metadata objects and a document that describes roles of columns in the facts metadata object and the one or more dimension metadata objects.

A data warehouse design that combines data from multiple source ledgers or modules is constructed and from that an associated, single physical Star or Snow-Flake schema and OLAP hyper-cube analytic structure is generated to enable cross-functional analysis of any those multiple source ledgers or modules. The step of constructing the data warehouse or the step of generating the associated OLAP cube is achieved without significant human intervention using software. The present invention is based on the insight that the technical bias against generating individual data marts and OLAP cubes from multiple source ledgers is not well founded. Previously, the norm has been to generate a single physical OLAP cube for each individual ledger—hence one for the General Ledger, a further one for sales order processing etc. This prior art approach makes cross functional analysis multiple source ledgers and sub-ledgers difficult since it requires the creation of a further level of physical or virtual cubes across multiple physical cubes and complex querying. This is no longer necessary with the present invention.

A computer network is disclosed comprising a plurality of interconnected computer devices including a plurality of disk drives for storing network data, each disk drive comprising a head and a disk. The computer network comprises a plurality of interconnected nodes, and a reservation facility for reserving resources within the disk drives and the nodes to support a predetermined Quality-of-Service constraint with respect to data transmitted between the disk drives through the nodes of the computer network. In one embodiment, a switched node is disclosed comprising switching circuitry having more than two bi-directional ports for simultaneously transmitting data in multiple dimensions through a computer network, a disk for storing data, a head actuated over the disk for writing data to and reading data from the disk, and a reservation facility for reserving resources associated with data read from the disk and written to the disk to support the predetermined Quality-of-Service constraint with respect to data transmitted through the computer network.

Methods, systems and computer programs for automatic, highly accurate machine comprehension of a plurality of segments of free form unstructured text in a natural language. The system answers a plurality of complex, free-form questions asked in a natural language, based on the totality of input text. The system further uses a multi-dimensional data model to measure the total effects of actions/verbs acting on various unique nouns present in the input text. The system may convert the questions into another multi-dimensional data model and may then compare the two data models in program memory to derive the answers to the posed questions. The system may then automatically detect unknown words and optionally look them up in digital information sources, such as online dictionaries and encyclopedias, to fill in the gaps in knowledge to answer the questions with expert-like reliability.

Methods, systems, and machine-readable mediums are disclosed for viewing multiply-dimensioned data. In one embodiment, a method is disclosed which comprises displaying multiply-dimensioned data in a table format, the table format having a plurality of rows, a plurality of columns, and a plurality of cells displaying data, a first column of the plurality of columns including data having at least two hierarchical levels. Data for at least a first set of the plurality of cells is displayed in a graphical format, the first set including cells in the first column, the graphical format of the cells in the first set in the first column indicating a hierarchical level associated with the cell data and a mechanism is displayed for a first one of the rows to display at least one additional row having data in the first column associated with a lower hierarchical level of the first row data.

Techniques exporting data and metadata from a source database environment to a target database environment are provided. The techniques include the steps of analyzing metadata that describes one or more items, the data for which is in a source database, where the one or more items include at least one of a view, a sequence, a dimension, a cube, an ETL mapping, and any database object for which the metadata is stored outside of the source and target databases. The data for each item resides in a data file associated with the source database. The data for each item is incorporated into the target database based on the metadata by providing the target database access to an incorporated data file, where the incorporated data file is the data file or a copy thereof. Techniques are also provided for exporting database data from the source database. The techniques include extracting metadata that describes one or more items, the data for which is in the source database, where the one or more items include at least one of the structures described above. The data for each item resides in a data file associated with the source database. After the exporting, a database server that manages the target database is provided access to an incorporated data file, where the incorporated data file is the data file or a copy thereof.

A multi-dimensional database query to be sent to a data source may be split into multiple smaller queries by a mid-tier solution and sent individually to the data source(s) for calculation and retrieval of data. This may be accomplished by creating row and column tree structures representing title and header rows and header columns in the query grid. The operation to be performed by the query may then be performed on these tree structures. The grid may then be split based on the resulting tree structures, and forwarded independently to one or more data servers. The results may be merged to generate the complete result or cursored. This allows the system to pass multiple smaller grids to data servers.

Multidimensional clustered tables are provided for efficient processing and management in a relational database management system. A multidimensional clustered table is one whose data is simultaneously clustered along one or more independent dimensions, or clustering keys, and physically organized into blocks or pages on disk. When such a table is created, one can specify one or more keys as dimensions along which to cluster the table's data. Each of the dimensions can consist of one or more columns. Further provided are efficient query processing and maintenance techniques for use in conjunction with multidimensional clustered tables.

A technique for efficiently updating a key table during outline restructure of a multi-dimensional database. A command is executed in a computer to perform a database operation on a relational database stored on a data store connected to the computer. It is determined that a multi-dimensional database has been restructured. Then, a key table of the relational database is rebuilt to correspond to the restructured multidimensional database.

Interactive and dynamic exploring of filter criteria for large amounts of numerical data having multiple dimensions is described. Exploration occurs without excessive amounts of computation or querying of a database based on a data set summary that may be obtained from a server in a search system and applied by a client device. A data set is summarized so as to capture relationships between distributions of items in the data set along multiple dimensions. To explore filter criteria, a user may interactively adjust a range of values that act as a filter criteria along a dimension and determine an effect on a distribution of items along another dimension. The client device may apply the data summary in reverse to determine, based on user input specifying aspects of a distribution along one dimension, filter criteria for another dimension that would result in the specified distribution.

A system, processor, and method for multiplying multi-dimensional data, for example, matrices, stored in vector memories. Each data element in a vector memory representing a sequential single element in a row of a left operand data array may be multiplied with a respective vector in a vector memory representing a sequential row in the right operand data array. The memory element representing the left operand element may be multiplied with the memory vector representing the right operand row that is in the same sequential order. A plurality of vectors of product elements may be generated by the multiplying. A single product element from each of the plurality of vectors of product elements may be added to a sum of product elements to generate each respective element in the same sequential order in a row of a product data array to generate a vector of a complete row of elements of the product data array.

A system automatically generates OLAP metadata objects for a multidimensional analysis program such as OLAP from SQL statements without involving the database administrator, and eliminates the need for database administrators to manually perform this analysis and design. The system deconstructs a set of SQL statements into tables and aggregates metrics for measures and joins. It recognizes that the relational database structure contains both dimension tables and fact tables. Over many SQL statements, fact tables will have a large measure metric while dimension tables will have a low measure metric. Tables are linked based on large join metrics; small join metrics are ignored. The present system builds the OLAP cube model from the fact tables, dimension tables, and joins. The analysis of the SQL statements allows the system to map the hierarchies within the dimension table, and provides the system with information about attribute relationships and cubes.