Abstract: Various embodiments are directed to managing annotations over a network for visualizations. An annotation engine enables users to associate a data object value with any number of notes, comments, videos, graphics, pictures, audio, references, links, or any other information A visualization engine generates visualizations that include annotation identifiers when the visualizations include data object values that are associated with annotations and the type of visualization is approved for use with the annotations.

Abstract: Embodiments are directed to managing data models for managing resource allocation. A data model portion may be provided. Allocation information based on resource allocations associated with pass-through objects that may be included in the data model portion. A memory buffer may be configured to include allocation ratio information and fixed resource value information. A reciprocal model based on the memory buffer and the data model portion may be provided. Providing the reciprocal model may include providing an effective resource value engine based on solving a linear system corresponding to the allocation ratio information and the fixed resource value information. If resource information for a pass-through object associated with the reciprocal model may be requested, the reciprocal model may be employed to provide the resource information to the data model.

Abstract: Embodiments are directed towards managing changes to data. A modeling engine may provide a data model based on objects comprised of one or more versions of one or more properties. Each version of the properties may be associated with separate validity ranges over time during which each version is valid. A report for visualizing the data model at a point-in-time may be provided. One or more report values may be provided based on each version of the properties that have a validity range that includes the point-in-time. The report may be displayed to provide provides one or more visualizations based on the one or more report values.

Abstract: Various embodiments are directed to managing annotations over a network for visualizations. An annotation engine enables users to associate a data object value with any number of notes, comments, videos, graphics, pictures, audio, references, links, or any other information A visualization engine generates visualizations that include annotation identifiers when the visualizations include data object values that are associated with annotations and the type of visualization is approved for use with the annotations.

Abstract: Embodiments are directed towards managing changes to data. A modeling engine may provide a data model based on objects comprised of one or more versions of one or more properties. Each version of the properties may be associated with separate validity ranges over time during which each version is valid. A report for visualizing the data model at a point-in-time may be provided. One or more report values may be provided based on each version of the properties that have a validity range that includes the point-in-time. The report may be displayed to provide provides one or more visualizations based on the one or more report values.

Abstract: Embodiments are directed to managing data models for managing resource allocation. A data model portion may be provided. Allocation information based on resource allocations associated with pass-through objects that may be included in the data model portion. A memory buffer may be configured to include allocation ratio information and fixed resource value information. A reciprocal model based on the memory buffer and the data model portion may be provided. Providing the reciprocal model may include providing an effective resource value engine based on solving a linear system corresponding to the allocation ratio information and the fixed resource value information. If resource information for a pass-through object associated with the reciprocal model may be requested, the reciprocal model may be employed to provide the resource information to the data model.

Abstract: The subject technology discloses configurations for creating reusable predictive models for applying to one or more data sources. The subject technology specifies a business problem to determine a probability of an event occurring. The business problem may include a constraint. A data source is selected for a predictive model associated with a predictive algorithm in which the predictive model includes one or more queries and parameters. A set of transformations are then determined based on the queries and parameters for at least a subset of data from the data source to be processed by the predictive algorithm. The subject technology identifies a set of patterns based on the set of transformations for at least the subset of data from the data source. A trained predictive model is then provided including the determined set of patterns, the set of transformations, and the associated predictive algorithm for solving the specified business problem.

Abstract: The subject disclosure relates to column based data encoding where raw data to be compressed is organized by columns, and then, as first and second layers of reduction of the data size, dictionary encoding and/or value encoding are applied to the data as organized by columns, to create integer sequences that correspond to the columns. Next, a hybrid greedy run length encoding and bit packing compression algorithm further compacts the data according to an analysis of bit savings. Synergy of the hybrid data reduction techniques in concert with the column-based organization, coupled with gains in scanning and querying efficiency owing to the representation of the compact data, results in substantially improved data compression at a fraction of the cost of conventional systems.

Abstract: A method and system that generate reproducible reports describing one or more analytical functions are disclosed. The reports describe a sequence of analytical functions and allow subsequent executions of the sequence of analytical functions. The matrix space that is inherent in worksheets is used to record a sequence of operations as a tabular report that can be interpreted by a computer program.

Abstract: The subject disclosure relates to column based data encoding where raw data to be compressed is organized by columns, and then, as first and second layers of reduction of the data size, dictionary encoding and/or value encoding are applied to the data as organized by columns, to create integer sequences that correspond to the columns. Next, a hybrid greedy run length encoding and bit packing compression algorithm further compacts the data according to an analysis of bit savings. Synergy of the hybrid data reduction techniques in concert with the column-based organization, coupled with gains in scanning and querying efficiency owing to the representation of the compact data, results in substantially improved data compression at a fraction of the cost of conventional systems.

Abstract: The subject disclosure relates to column based data encoding where raw data to be compressed is organized by columns, and then, as first and second layers of reduction of the data size, dictionary encoding and/or value encoding are applied to the data as organized by columns, to create integer sequences that correspond to the columns. Next, a hybrid greedy run length encoding and bit packing compression algorithm further compacts the data according to an analysis of bit savings. Synergy of the hybrid data reduction techniques in concert with the column-based organization, coupled with gains in scanning and querying efficiency owing to the representation of the compact data, results in substantially improved data compression at a fraction of the cost of conventional systems.

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 and methods that supply extensibility mechanisms for analysis services, via a plug-in component that enables additional functionalities. The plug-in component provide additional custom logic for the analysis services unified dimensional model (UDM). Accordingly, server functionalities can be extended in an agile manner, and without a requirement for a new release, for example.

Abstract: Data expressed as tabular data having columns and rows can be analyzed and data determined to be an exception can be flagged. In addition, reasons for flagging such data as exceptions can be presented to a user to facilitate further analysis and action on the data. A predictive analysis component can utilize a clustering algorithm with predictive capabilities to autonomously analyze the data. Periodic re-analysis of the data can be performed to determine if exceptions have changed based on new or modified data.

Abstract: Fields contained in data expressed as tabular data having columns and rows can initially be marked as exceptions, wherein a column within a row can be the potential cause of the exception. A user configurable parameter can be utilized to change the sensitivity or allowable exceptions for each row and/or column, to increase or decrease the number of exceptions detected. As data within each field are modified, added or deleted, or when the configurable parameter is changed, the exceptions marked can be automatically updated. Such updated exceptions can be the same or different from the initially marked exceptions. As such, a user can evaluate data and determine whether various changes within the data will change various outcomes.

Abstract: Seeking goals in data that can be expressed as rows and columns is provided through predictive analytics. If a desired goal is achievable, the changes to the rows and/or columns that can achieve the goal are presented to a user. If the desired goal is not achievable, an error message or other indicator can be presented to the user. Predictive analytics can include a predictive algorithm, various data mining techniques, or other predictive techniques. A confidence metric of a goal-seek result can be normalized to estimate the degree of confidence that a particular change will yield the desired outcome.

Abstract: A system that effectuates fetching a complete set of relational data into a mining services server and subsequently defining desired partitions upon the fetched data is provided. In accordance with the innovation, the data can be locally cached and partitioned therefrom. Accordingly, upon the same mining structure (e.g., cache) that has been partitioned, the novel innovation can build mining models for each partition. In other words, the innovation can employ the concept of mining structure as a data cache while manipulating only partitions of this cache in certain operations. The innovation can be employed in scenarios where a user wants to train a mining model using only data points that satisfy a particular Boolean condition, a user wants to split the training set into multiple partitions (e.g., training/testing) and/or a user wants to perform a data mining procedure known as “N-fold cross validation.

Abstract: The subject invention relates to systems and methods that extend the network data access capabilities of mark-up language protocols. In one aspect, a network data transfer system is provided. The system includes a protocol component that employs a computerized mark-up language to facilitate data interactions between network components, whereby the data interactions were previously limited or based on a statement command associated with the markup language. An extension component operates with the protocol component to support the data transactions, where the extension component supplies at least one other command from the statement command to facilitate the data interactions.

Abstract: The subject disclosure relates to column based data encoding where raw data to be compressed is organized by columns, and then, as first and second layers of reduction of the data size, dictionary encoding and/or value encoding are applied to the data as organized by columns, to create integer sequences that correspond to the columns. Next, a hybrid greedy run length encoding and bit packing compression algorithm further compacts the data according to an analysis of bit savings. Synergy of the hybrid data reduction techniques in concert with the column-based organization, coupled with gains in scanning and querying efficiency owing to the representation of the compact data, results in substantially improved data compression at a fraction of the cost of conventional systems.

Abstract: Various technologies and techniques are disclosed for calculating and evaluating the behavior of recommendation systems. Accuracy measures are computed for a plurality of items in a real recommendation system, an ideal recommendation system, and a popularity-based baseline recommendation system. The accuracy measures for the plurality of items are presented to a user so the user can evaluate a performance of the real recommendation system in comparison to the ideal recommendation system and the popularity-based baseline recommendation system. The accuracy measures can be presented in an interactive graph.