Abstract: In embodiments, systems and methods may involve using a platform as disclosed herein for applications described herein where the systems and methods involve receiving a dataset in an analytic platform, the dataset including fact data and dimension data for a plurality of distinct product categories. It may also involve storing the data in a flexible hierarchy, the hierarchy allowing the temporary fixing of data along a dimension and flexible querying along other dimensions of the data. It may also involve pre-aggregating certain combinations of data to facilitate rapid querying, the pre-aggregation based on the nature of common queries. It may also involve facilitating the presentation of a cross-category view of an analytic query of the dataset. In embodiments, the temporarily fixed dimension can be rendered flexible upon an action by the user.

Abstract: In embodiments of the present invention, a method is described for reducing bias by data fusion of a household panel data and a loyalty card data. In embodiments, a method is provided for receiving a consumer panel dataset in a data fusion facility, receiving a consumer point-of-sale dataset in a data fusion facility, receiving a dimension dataset in a data fusion facility, fusing the datasets received in the data fusion facility into a new panel dataset based at least in part on an encryption key, estimating a consumer behavior using a first model based on the consumer panel dataset, estimating a consumer behavior using a second model based only on those consumers present in both the consumer panel dataset and the consumer point-of-sale dataset, and refining the first model based at least on the results of the second model.

Abstract: A product database describing products and attributes associated with the products is identified. Some attributes have values including words. A dictionary including the words is identified. The dictionary is partitioned into synonym classes of words. A representative word from the dictionary is selected. Replacement rules are identified, each of which replace a target word with the target word's corresponding representative. For each product in the database, the replacement rules are applied to produce a standardized product database.

Abstract: Using a computer, a database comprising a field is identified. A query relating to the field is identified. Prior to processing the query, the field is dynamically altered to conform to a desired bit size. The query is processed. The results of the query are returned.

Abstract: Improved capabilities are described for identifying a first classification scheme associated with product attributes of a first grouping of products, identifying a second classification scheme associated with product attributes of a second grouping of products, and receiving a record of data relating to an item, the classification of which is uncertain. It may also involve receiving a dictionary of attributes associated with products and assigning the item to at least one of the classification schemes based on probabilistic matching among the attributes in the classification schemes, the attributes in the dictionary of attributes and the known attributes of the item.

Abstract: Systems and methods are presented that may involve receiving a causal fact dataset including facts relating to items perceived to cause actions, wherein the causal fact dataset includes a data attribute that is associated with a causal fact datum. It may also involve pre-aggregating a plurality of the combinations of a plurality of causal fact data and associated data attributes in a causal bitmap. It may also involve selecting a subset of the pre-aggregated combinations based on suitability of a combination for the analytic purpose. It may also involve storing the subset of pre-aggregated combinations to facilitate querying of the subset.

Abstract: In embodiments of the present invention improved capabilities are described for identifying a first classification scheme associated with product attributes of a first grouping of products, identifying a second classification scheme associated with product attributes of a second grouping of products, and receiving a record of data relating to an item, the classification of which is uncertain. It may also involve receiving a dictionary of attributes associated with products and assigning the item to at least one of the classification schemes based on probabilistic matching among the attributes in the classification schemes, the attributes in the dictionary of attributes and the known attributes of the item.

Abstract: In embodiments of the present invention improved capabilities are described for identifying a classification scheme associated with product attributes of a grouping of products of an entity, receiving a record of data relating to an item of a competitor to the entity, the classification of which is uncertain, receiving a dictionary of attributes associated with products, and assigning a product code to the item, based on probabilistic matching among the attributes in the classification scheme, the attributes in the dictionary of attributes and at least one known attribute of the item.

Abstract: A product database describing products and attributes associated with the products is identified. Some attributes have values including words. A dictionary including the words is identified. The dictionary is partitioned into synonym classes of words. A representative word from the dictionary is selected. Replacement rules are identified, each of which replace a target word with the target word's corresponding representative. For each product in the database, the replacement rules are applied to produce a standardized product database.

Abstract: In embodiments of the present invention improved capabilities are described for identifying a classification scheme associated with product attributes of a grouping of products of an entity, receiving a record of data relating to an item of a competitor to the entity, the classification of which is uncertain, receiving a dictionary of attributes associated with products, and assigning a product code to the item, based on probabilistic matching among the attributes in the classification scheme, the attributes in the dictionary of attributes and at least one known attribute of the item.

Abstract: In embodiments of the present invention improved capabilities are described for identifying a classification scheme associated with product attributes of a grouping of products of an entity, receiving a record of data relating to an item of a competitor to the entity, the classification of which is uncertain, receiving a dictionary of attributes associated with products, and assigning a product code to the item, based on probabilistic matching among the attributes in the classification scheme, the attributes in the dictionary of attributes and at least one known attribute of the item.

Abstract: Using a computer, a database comprising a field is identified. A query relating to the field is identified. Prior to processing the query, the field is dynamically altered to conform to a desired bit size. The query is processed. The results of the query are returned.

Abstract: The present invention provides a method for updating data sources. The method may include identifying a plurality of data sources, identifying a plurality of overlapping attribute segments to use for comparing the data sources, calculating a factor as a function of each of the plurality of overlapping attribute segments, and using the factors to update a first group of values in the second data source to reduce bias. Further, at least a first data source is more accurate than a second data source.

Abstract: In embodiments, systems and methods may involve using a platform as disclosed herein for applications described herein where the systems and methods involve receiving a dataset in an analytic platform, the dataset including fact data and dimension data for a plurality of distinct product categories. It may also involve storing the data in a flexible hierarchy, the hierarchy allowing the temporary fixing of data along a dimension and flexible querying along other dimensions of the data. It may also involve pre-aggregating certain combinations of data to facilitate rapid querying, the pre-aggregation based on the nature of common queries. It may also involve facilitating the presentation of a cross-category view of an analytic query of the dataset. In embodiments, the temporarily fixed dimension can be rendered flexible upon an action by the user.

Abstract: In embodiments of the present invention improved capabilities are described for identifying a first classification scheme associated with product attributes of a first grouping of products, identifying a second classification scheme associated with product attributes of a second grouping of products, and receiving a record of data relating to an item, the classification of which is uncertain. It may also involve receiving a dictionary of attributes associated with products and assigning the item to at least one of the classification schemes based on probabilistic matching among the attributes in the classification schemes, the attributes in the dictionary of attributes and the known attributes of the item.

Abstract: The present invention provides a method for updating data sources. The method may include identifying a plurality of data sources, identifying a plurality of overlapping attribute segments to use for comparing the data sources, calculating a factor as a function of each of the plurality of overlapping attribute segments, and using the factors to update a first group of values in the second data source to reduce bias. Further, at least a first data source is more accurate than a second data source.

Abstract: Systems and methods are presented that may involve specifying an availability condition associated with a data hierarchy in a database. It may also involve storing the availability condition in a matrix and using the matrix to determine access to data in the data hierarchy. In embodiments, the data hierarchy may be a flexible data hierarchy wherein a selected dimension of data within the hierarchy may be held temporarily fixed while flexibly accessing other dimensions of the data. In embodiments, the process may further involve specifying an availability condition, wherein the specification of the availability condition does not require modification of the datum or restatement of the database.

Abstract: Systems and methods presented may involve specifying an availability condition associated with a component of an analytic platform. It may involve storing the availability condition in a matrix. It may involve using the matrix to determine access to the component of the analytic platform.

Abstract: Systems and methods are presented that may involve receiving a aggregated dataset, wherein the aggregated dataset includes data from a panel data source, a fact data source, and a dimension data source that have been associated with a standard population database. The process may also involve storing the aggregated data in a partition within a partitioned database, wherein the partition is associated with a data characteristic. The process may also involve associating a master processing node with a plurality of slave nodes, wherein each of the plurality of slave nodes is associated with a partition of the partitioned database. The process may also involve submitting an analytic query to the master processing node. The process may also involve assigning analytic processing to at least one of the plurality of slave nodes by the master processing node, wherein the assignment is based at least in part on the association of the partition with the data characteristic.

Abstract: In embodiments of the present invention, a method is described for reducing bias by data fusion of a household panel data and a loyalty card data. In embodiments, a method is provided for receiving a consumer panel dataset in a data fusion facility, receiving a consumer point-of-sale dataset in a data fusion facility, receiving a dimension dataset in a data fusion facility, fusing the datasets received in the data fusion facility into a new panel dataset based at least in part on an encryption key, estimating a consumer behavior using a first model based on the consumer panel dataset, estimating a consumer behavior using a second model based only on those consumers present in both the consumer panel dataset and the consumer point-of-sale dataset, and refining the first model based at least on the results of the second model.