Abstract: A method, system and computer program product for aggregate query optimization. A dataset with plurality of values divided into dimensions and measurements is received. Pre-calculated values obtained by aggregates of measurements' values respective of plurality of combinations of dimensions' values are calculated and stored for one or more aggregate measurements of interest. Responsive to an input received of a first set of one or more dimensions and a second set of one or more aggregate measurements of interest, an aggregate result value of a respective member of the second set is calculated and outputted by retrieval of the pre-calculated value therefor respective of members of the first set.

Abstract: A system and method for generating visual representations of interesting plots of tabular data.

Abstract: A method, system, and computer program product for conserving resources in segment trend analytics query processing using event data. A set of events of an entity is aggregated and sorted from earliest to last, and sequentially processed to incrementally set a subset therefrom. A predicate function for determining segment membership is applied respective of a linear timeline of events of the subset represented by a time of an event processed. A data record comprising identification of the entity, time, and respective segment is generated and stored. Data records are aggregated by respective identification of a segment and a time comprised therein, and at least one analytic measure respective of entities which identification thereof is comprised therein, is calculated and stored. An indication of the at least one analytic measure calculated respective of a segment and a time queried is returned, whereby determination of a trend of the segment is enabled.

Abstract: A method, system and computer program product for aggregate query optimization. A dataset with plurality of values divided into dimensions and measurements is received. Pre-calculated values obtained by aggregates of measurements' values respective of plurality of combinations of dimensions' values are calculated and stored for one or more aggregate measurements of interest. Responsive to an input received of a first set of one or more dimensions and a second set of one or more aggregate measurements of interest, an aggregate result value of a respective member of the second set is calculated and outputted by retrieval of the pre-calculated value therefor respective of members of the first set.

Abstract: A method, system, and computer program product for conserving resources in segment trend analytics query processing using event data. A set of events of an entity is aggregated and sorted from earliest to last, and sequentially processed to incrementally set a subset therefrom. A predicate function for determining segment membership is applied respective of a linear timeline of events of the subset represented by a time of an event processed. A data record comprising identification of the entity, time, and respective segment is generated and stored. Data records are aggregated by respective identification of a segment and a time comprised therein, and at least one analytic measure respective of entities which identification thereof is comprised therein, is calculated and stored. An indication of the at least one analytic measure calculated respective of a segment and a time queried is returned, whereby determination of a trend of the segment is enabled.

Abstract: A method, system and computer program product for providing dual mode view of cloud computing environment. User request for performing operation on entity of the environment while in sandbox view being intercepted by client and sent to server with sandbox token obtained therefrom responsive to user switch from production view to sandbox view. Validation of sandbox view by server being performed using the sandbox token. Data structure comprising identification as production/sandbox of each entity of the environment and each sandbox modified production entity, and datastore of all entities of the environment and data thereof, being used for processing the request and recording results thereof. Sandbox entities being filtered out of production view, and sandbox modified production entities being filtered out of sandbox view.

Abstract: A system and method for generating visual representations of interesting plots of tabular data.

Abstract: A system and method for generating visual representations of interesting plots of tabular data.

Abstract: A system and method for tracking users across a plurality of media platforms are provided. The method includes generating unified user-level data of each user across the media of advertising platforms; storing the unified user-level data generated for each user in a storage; taping into the plurality of advertising platforms to render pixel trafficking data; and analyzing raw data based on which the unified user-level data is generated.

Abstract: A system and method for providing big data analytics responsive to dynamically-changing data models are provided. The method includes parsing, based on a logical data schema, a user query into a plurality of sub-queries; sending the plurality of sub-queries to a plurality of data stores, wherein each data store is selected based on a physical data schema of a dynamic data schema; receiving a plurality of sub-result datasets, wherein each sub-result dataset corresponds to a sub-query; and combining the plurality of sub-result datasets into a single resulting data set based on a logical schema of the dynamic data schema, wherein the combining includes at least any of: an aggregation operation and a join operation.

Abstract: A system and method for performing cross-platform data analytics of advertising campaign information.

Abstract: A system and method for generating visual representations of interesting plots of tabular data.

Abstract: A system and method for normalizing campaign data gathered from a plurality of advertising platforms. The method comprises receiving campaign data related to at least one campaign gathered from a plurality of advertising platforms; mapping data dimensions in the received campaign data to a marketing data model to produce a dataset that is organized and functions as the marketing data model; normalizing data values in the dataset according to a unified notation defined for each of the data dimensions in the marketing data model; and optimizing the normalized dataset to allow faster manipulation of data.

Abstract: A system and method for providing significant performance insights on marketing campaign data. The method includes training a regression model using a training set including segments and corresponding performance metrics of a plurality of potentially significant insights, each segment being a combination of a dimension and a value, wherein each insight includes a segment and a corresponding performance metric; filtering, based on the regression model, at least one insight from the plurality of potentially significant insights to result in at least one significant insight; computing, based in part on the regression model, a total significance score for each of the at least one significant insight; and ranking the at least one significant insight based on the computed total significance scores.

Abstract: A system and method for tracking users across a plurality of media platforms are provided. The method includes generating unified user-level data of each user across the media of advertising platforms; storing the unified user-level data generated for each user in a storage; taping into the plurality of advertising platforms to render pixel trafficking data; and analyzing raw data based on which the unified user-level data is generated.

Abstract: A system and method for unifying user-level data across a plurality of media platforms are provided. The method includes receiving user-level data events from the plurality of media platforms, wherein each event relates to at least one online advertisement viewed by a plurality of users; processing the received user-level data events to detect a group of user-level data events related to the same user of the plurality of users; combining user-level data from each group of user-level data events related to the same user; assigning a unique user identifier to the combined user-level data to result in a unified user-level data related to a particular user; and storing the unified user-level data in a database, thereby providing consistent user-level data across the plurality of media platforms.

Abstract: A system and method for unifying user-level data across a plurality of media platforms are provided. The method includes receiving user-level data events from the plurality of media platforms, wherein each event relates to at least one online advertisement viewed by a plurality of users; processing the received user-level data events to detect a group of user-level data events related to the same user of the plurality of users; combining user-level data from each group of user-level data events related to the same user; assigning a unique user identifier to the combined user-level data to result in a unified user-level data related to a particular user; and storing the unified user-level data in a database, thereby providing consistent user-level data across the plurality of media platforms.

Abstract: A system and method for providing big data analytics responsive to dynamically-changing data models are provided. The method includes parsing, based on a logical data schema, a user query into a plurality of sub-queries; sending the plurality of sub-queries to a plurality of data stores, wherein each data store is selected based on a physical data schema of a dynamic data schema; receiving a plurality of sub-result datasets, wherein each sub-result dataset corresponds to a sub-query; and combining the plurality of sub-result datasets into a single resulting data set based on a logical schema of the dynamic data schema, wherein the combining includes at least any of: an aggregation operation and a join operation.

Abstract: A system and method for normalizing campaign data gathered from a plurality of advertising platforms. The method comprises receiving campaign data related to at least one campaign gathered from a plurality of advertising platforms; mapping data dimensions in the received campaign data to a marketing data model to produce a dataset that is organized and functions as the marketing data model; normalizing data values in the dataset according to a unified notation defined for each of the data dimensions in the marketing data model; and optimizing the normalized dataset to allow faster manipulation of data.

Abstract: A system and method for performing cross-platform data analytics of advertising campaign information.