Abstract: Processing of a request is optimized. The request has one or more predicates. A list of the one or more predicates in the request is created and predicates for which an actual cost has not been stored or for which a cost cannot be estimated are pruned from the list. An access path for the each of the predicates is selected. The request is processed using the selected access paths producing one or more actual predicate costs. The one or more actual predicate costs are stored.

Abstract: An aggregate User Defined Function (UDF) processing used for multi-regression is provided. The aggregate UDF initializes storage space for multiple nodes of a database environment. Data is then extracted from a relational database and populated according to groupings on each of the nodes. Multiple rows or records are then processed to create a merge and multi-regression processed.

Abstract: Techniques are presented for managing fraud information. Metadata defines user profiles, security levels, fraud cases, and presentation information. One or more queries or reports are processed against disparate data store tables and the results are aggregated into a repository. The repository is also defined by the metadata. Furthermore, operations associated with sharing, viewing, and accessing the results from the repository is defined and controlled by the metadata. In an embodiment, portions of the metadata may be viewed and navigated in a hierarchical and graphical formatted presentation.

Abstract: Various embodiments may include taking an initial dump of a database table and tracking changes to the database table, with regard to but outside of transactions, since a most recent full or partial dump has been taken. A partial dump, in such embodiments, may be taken since the most recent full or partial dump and used to create a data structure which may be used to update only those database table rows modified since a last full or partial dump. As a result, the dumps of a database table will include a single full dump and may include one or more partial dumps. These full and partial dumps may then be instantiated to create or update an instance of the database table. In some embodiments, dumps may be taken directly to a mirrored instance of a database table.

Abstract: A computer network is used to improve the profitability of one or more business entities. The network receives business-related data from at least two business entities and stores at least some of the data from each of the business entities in a common database. Then, in accordance with the terms of an agreement among the business entities, the network allows at least one of the business entities to receive information gathered from the common database.

Abstract: A Life-Time Value (LTV) system is a data-driven computer-facilitated financial model that provides accurate and consistent profitability projections using current period account level profitability data stored in a Relational Database Management System (RDBMS). The Life-Time Value system performs Net Present Value (NPV) and Future Value (FV) processing using business-rule and data-driven applications that embrace the current period profit components, defines forecast periods, parameters and methodologies, and applies appropriate growth values, attrition values and propensity values to an object of future value interest.

Abstract: A Life-Time Value (LTV) system is a data-driven computer-facilitated financial model that provides accurate and consistent profitability projections using current period account level profitability data stored in a Relational Database Management System (RDBMS). The Life-Time Value system performs Net Present Value (NPV) and Future Value (FV) processing using business-rule and data-driven applications that embrace the current period profit components, defines forecast periods, parameters and methodologies, and applies appropriate growth values, attrition values and propensity values to an object of future value interest.

Abstract: A Life-Time Value (LTV) system is a data-driven computer-facilitated financial model that provides accurate and consistent profitability projections using current period account level profitability data stored in a Relational Database Management System (RDBMS). The Life-Time Value system performs Net Present Value (NPV) and Future Value (FV) processing using business-rule and data-driven applications that embrace the current period profit components, defines forecast periods, parameters and methodologies, and applies appropriate growth values, attrition values and propensity values to an object of future value interest.

Abstract: A system and method for identifying a selection of index candidates for a relational database. The system includes a Predicate Analyzer for examining database queries in workload and recording column and predicate information; a Search Engine for performing a combinatorial search of index candidates; an Index Emulator for emulating the existence of a set of candidate indexes by making necessary “fake” entries into the relational database management system data dictionary; and a Query Optimizer for estimating the cost of a given query within a given index configuration. In accordance with the method, data indicative of a workload comprising one or more queries is received, and predicates are then analysed and organized into column groups for each basic predicate type. Statistics are collected on each of these groups. Non-predicate portions of each query are scanned to obtain additional covering columns. A combinational search is performed on the column groups to identify covering and non-covering candidates.

Abstract: A modeling tool for determining the impact that a data warehouse solution will have upon a business organization considering implementing a data warehouse solution. The modeling tool is implemented on a server computer with restricted access through a client computer. A server computer includes: a business impact model comprising a mathematical representation of a data warehouse solution, and an assessment questionnaire; and a modeling application for calculating a value of a data warehouse solution to a business organization from the business impact model and assessment questionnaire answers. A client computer is connectable to the server computer for receiving a copy of the business impact model, and providing offline collection of answers to the assessment questions, and offline calculation of a value of the data warehouse solution to the business organization. An application residing on the server computer keeps a record of the business impact model received by the client computer.

Abstract: A Life-Time Value (LTV) system is a data-driven computer-facilitated financial model that provides accurate and consistent profitability projections using current period account level profitability data stored in a Relational Database Management System (RDBMS). The Life-Time Value system performs Net Present Value (NPV) and Future Value (FV) processing using business-rule and data-driven applications that embrace the current period profit components, defines forecast periods, parameters and methodologies, and applies appropriate growth values, attrition values and propensity values to an object of future value interest.

Abstract: A Life-Time Value (LTV) system is a data-driven computer-facilitated financial model that provides accurate and consistent profitability projections using current period account level profitability data stored in a Relational Database Management System (RDBMS). The Life-Time Value system performs Net Present Value (NPV) and Future Value (FV) processing using business-rule and data-driven applications that embrace the current period profit components, defines forecast periods, parameters and methodologies, and applies appropriate growth values, attrition values and propensity values to an object of future value interest.

Abstract: Techniques for partitioning indexes are provided. A predefined data type associated with a column of a database table is acquired. Column value statistics for the column are acquired. The values are analyzed to produce multiple partitions for the values. Each partition includes each of the values and each partition includes multiple groupings of the values. Also, each grouping of a particular partition includes a subset or range of the values. Furthermore, each grouping of a partition includes a same distribution for the values as other groupings of that partition. Each partition represents a potential partitioning index for the column and its values.

Abstract: A system and method for selectively recompiling stored execution plans within a database system. In one technique the execution plans include respective version numbers of database software operable within the database system during compilation of the respective plans. A request is received to execute one of the stored execution plans, and the stored execution plan is retrieved from computer memory. A version number is obtained of database software operable within the database system during retrieval of the stored execution plan. The obtained version number is compared with the version number associated with the retrieved execution plan. On detecting a mismatch between the obtained version number and the retrieved version number, the stored execution plan is recompiled. In another technique the stored execution plans include respective cost parameters representing the hardware capabilities of the system at the time of plan compilation.

Abstract: Data consumed by a threaded forecasting module is acquired in advance of a request for that data by the forecasting module. The data is used for servicing multiple instances of the threaded forecasting module as they concurrently process. The instances concurrently produce different portions of the forecasting results.

Abstract: A system calculates the optimal allocation of two or more resources provided by a resource provider to a task within a computer system from a plurality of possible allocations. In doing so, the system calculates the total volume of an N-dimensional cube, where N is the number of resources provided by the resource provider, representing the respective amounts of resources available to be allocated. The system also calculates the average volume of the N?1 dimensional shapes forming the sides of the N-dimensional cube. The system then calculates, at least partly from the ratio of the total volume to the average volume, the balance resulting from the allocation of resources represented by the N-dimensional cube. The system then calculates the imbalance resulting from the allocation of resources at least partly from the balance and determines the smallest imbalance as the optimal allocation of resources.

Abstract: Methods and systems provide automatic search generation capabilities. A search constraint and a control field identifier are received. A search generating module generates a search that when executed returns records from a data store. The records satisfy the search constraint and have identical values for the control field identifier for unique customer identifications.

Abstract: A system and method profiles different users having a common terminal identifier in communication system. The system comprises a user activity data analyzer for extracting profile data from user terminal activity data, a user identifier for determining whether the profile data corresponds to a profile data history associated with the user terminal, and a user profile generator for generating a profile data history from the profile data for another user to be associated with the terminal in response to the profile data not corresponding to the profile data history associated with the user terminal. The user activity data analyzer extracts site addresses, URLs, click event data, metadata and other user activity from a session log to compile information useful for assessing a user's interests. This extracted profile data may then be compared to a profile history previously generated and associated with the terminal identifier.

Abstract: A method and apparatus identifies SQL statements in a first transaction that specify modification operations that are commutative and associative. The SQL statements are combined into one SQL statement, and the one SQL statement is submitted to a database system. Optionally, or alternatively, multiple transactions can be grouped together into one transaction.

Abstract: A database query is optimized for a star database schema that includes at least one fact table and at least one dimension table, where the database query includes an IN-List condition. During optimization, the IN-List is transformed into a relation and the relation is joined with the dimension table to produce a join result. The join result is then joined to the fact table.