Abstract: An apparatus, computer-readable medium, and computer-implemented method for efficiently classifying a data object, including representing the data object as a data object vector in a vector space, each dimension of the data object vector corresponding to a different feature of the data object, determining a distance between the data object vector and centroids of data domain clusters in the vector space, each data domain cluster comprising data domain vectors representing data domains, sorting the data domain clusters according to their respective distances to the data object vector, and iteratively applying data domain classifiers corresponding to data domains represented in a closest data domain cluster in the sorted data domain clusters to the data object.

Abstract: A deployment platform, computer-readable medium, and computer-implemented method for intelligent execution of a solution on a computer network, including receiving an instruction to execute a solution in a local runtime environment on the deployment platform, the solution including solution code written in a solution language, determining, by a helper program on the deployment platform, whether the solution is executable on the deployment platform based on the solution language and either launching, by the helper program, the solution on the deployment platform when the solution is executable on the deployment platform or launching, by the helper program, the solution on a remote platform on the computer network that is configured to execute the solution when the solution is not executable on the deployment platform, the helper program being configured to communicate with the launched solution to enable the launched solution to interface with the local runtime environment on the deployment platform.

Abstract: A system, method, and computer-readable medium for determining customer adoption based on monitored data, including receiving product usage parameters from a product data store on the computer network, each product usage parameter being determined based on tracking usage of the product by the customer over a predetermined time period, storing a customer profile for the customer comprising customer parameters, the customer parameters being determined based on customer information stored in a customer database on the computer network, receiving service parameters from a customer support data store on the computer network, each service parameter being determined based on tracking support services provided to the customer for the product over the predetermined time period, and generating a product adoption score by applying a machine learning model to the product usage parameters and the customer profile to generate a usage-based adoption score and adjusting the usage-based adoption score based on the service par

Abstract: A system, method, and computer-readable medium for determining risk associated with anomalous behavior of a user on a computer network including receiving anomalous behavioral data corresponding to anomalous activity of the user on the computer network, determining surprisal values corresponding to one or more behavioral factors based on one or more of: one or more probabilities corresponding to one or more current values or one or more characteristics of the one or more behavioral factors, determining one or more dynamic weights corresponding to the one or more behavioral factors based at least in part on the one or more current values and historically expected values of the one or more behavioral factors for the user, and determining a risk metric corresponding to the anomalous activity of the user based on the surprisal values, the one or more dynamic weights, and static weights assigned to the one or more behavioral factors.

Abstract: A system, method and computer-readable medium for data protection simulation and optimization in a computer network, including grouping data stored in data stores in the computer network into groupings according to an architectural or a conceptual attributes, storing, current values of risk metrics for each grouping, each of the metrics corresponding to sensitive domains, receiving a risk reduction goal corresponding to at least one risk metric in the risk metrics, the at least one risk metric corresponding to at least one sensitive domain in the sensitive domains, determining a simulated value of the at least one risk metric for each grouping in the groupings by simulating application of a protection mechanism to sensitive data in each corresponding data store, the sensitive data corresponding to the at least one sensitive domain, and ranking the groupings based on the at least one simulated value of the at least one risk metric for each grouping.

Abstract: Systems, methods, and related techniques and apparatus containing instructions which when executed by one or more computing devices for determining dataset rankings by determining, from the lineage order requirement, one or more first lineage level datasets from the collection of datasets, generating one or more first lineage level asset ranks respectively for each one of the one or more first lineage level datasets, determining at least one second lineage level dataset having an outflow to the one or more first lineage level datasets, and generating a first dataset rank for the at least one second lineage level dataset as a first function of the outflow and at least one of the one or more first lineage level asset ranks.

Abstract: A method, apparatus, and computer-readable medium for searching polymorphically encrypted data includes storing one or more pseudonymous tokens in a data store, the one or more pseudonymous tokens being generated by encrypting a ciphertext using a first algorithm and an encryption key, the first algorithm comprising a polymorphic algorithm configured to generate a distinct pseudonymous token for each application of the polymorphic algorithm to the same plaintext, and identifying data in the data store that corresponds to the ciphertext by querying the data store using a search token generated by encrypting the plaintext using a second algorithm and the encryption key, the search token being distinct from the one or more pseudonymous tokens.

Abstract: A system, method and computer-readable medium for determining a data domain associated with data, including parsing a document to generate one or more document indexes corresponding to the document, the one or more document indexes comprising a plurality of index terms and location information, determining a syntactic confidence score corresponding to a non-dictionary term in the plurality of index terms based on a syntactic analysis of the non-dictionary term, determining a proximity confidence score corresponding to the non-dictionary term based on the location information and at least one proximity query associated with the non-dictionary term and one or more other terms in the document index, determining a semantic confidence score based on a plurality of dictionary terms in the plurality of index terms, and determining an overall confidence score corresponding to the non-dictionary term based on the syntactic confidence score, the proximity confidence score, and the semantic confidence score.

Abstract: An apparatus, computer-readable medium, and computer-implemented method for data subsetting, including receiving a request comprising a criterion indicating a criterion table in a plurality of tables of a database, as schema of the database corresponding to an entity graph, the entity graph comprising a plurality of entities corresponding to the plurality of tables and a plurality of directed edges connecting the plurality of entities, determining directed edges in the plurality of directed edges that must be traversed in both directions in order to traverse all entities in the entity graph starting from a criterion entity corresponding to the criterion table, generating, an ordered list of edges for the entity graph based on the directed edges that must be traversed in both directions and topological ordering, and generating a subset of data from the plurality of tables based on the ordered list of edges for the entity graph and the request.

Abstract: An apparatus, computer-readable medium, and computer-implemented method for extracting a subset, including receiving a request comprising one or more criteria indicating one or more criteria tables in a plurality of tables of the database, storing an entity graph corresponding to a schema of the database and the one or more criteria, determining one or more top-most criteria entities in the entity graph, and generating the subset from the plurality of tables by traversing the entity graph starting at the one or more top-most criteria entities without traversing any directed edge more than once.

Abstract: A system, method and computer-readable medium for missing data identification, including identifying columns in tables of a database, generating categorical columns of categorical data by transforming data values in the columns into categorical data values, generating a co-occurrence matrix corresponding to a pair of categorical columns in the categorical columns, determining an expected frequency of co-occurrence corresponding to each unique pair of categorical data values based at least in part on a marginal totals corresponding to categorical data values in the co-occurrence matrix, and identifying one or more locations of missing data based at least in part on the count of co-occurrence of each unique pair of categorical data values and the expected frequency of co-occurrence corresponding to each unique pair of categorical data values.

Abstract: A system, method, and computer-readable medium for determining risk associated with anomalous behavior of a user on a computer network including receiving anomalous behavioral data corresponding to anomalous activity of the user on the computer network, determining surprisal values corresponding to one or more behavioral factors based on one or more of: one or more probabilities corresponding to one or more current values or one or more characteristics of the one or more behavioral factors, determining one or more dynamic weights corresponding to the one or more behavioral factors based at least in part on the one or more current values and historically expected values of the one or more behavioral factors for the user, and determining a risk metric corresponding to the anomalous activity of the user based on the surprisal values, the one or more dynamic weights, and static weights assigned to the one or more behavioral factors.

Abstract: A data profiling module receives user selection of spreadsheets, and the data from the selected spreadsheets is profiled. At least one matching column is identified among the spreadsheets selected. The data profiling module calculates a match metric for the at least one matching column, and unifies the spreadsheets into a single composite spreadsheet using the at least one identified matching column. A preview view of a composite spreadsheet is generated, visually indicating the at least one matching column, any non-matching columns between the spreadsheets, and the match metric for the matching columns. An action history module identifies spreadsheets for use in the procedure, and stores any action applied to the spreadsheets as a procedure template that can be applied to a plurality of other spreadsheets.

Abstract: A method, apparatus, and computer-readable medium for dynamic hierarchical data flow mapping, including storing dynamic data flow mappings, each dynamic data flow mapping including a mapping of data from an input port corresponding to a source data container to an output port corresponding to a destination data container and a dynamic hierarchical field having a dynamic hierarchical data type, determining a rule language corresponding to each dynamic hierarchical field in the dynamic data flow mappings, the rule language defining acceptable parameters for sub-fields of that dynamic hierarchical data type, and generating static data flow mappings by resolving all dynamic hierarchical fields into static hierarchical fields during compilation of the dynamic data flow mappings with the source data container and the destination data container, the static data flow mappings being generated based at least in part on the rule language corresponding to each dynamic hierarchical field and underlying data in one or more

Abstract: A system, method and computer-readable medium format-preserving encryption of a numerical value, including storing a binary numerical value, the binary numerical value comprising a plurality of binary bits, dividing the plurality of binary bits into a plurality of bit groups and storing the plurality of bit groups in a plurality of bytes, encrypting each byte in the plurality of bytes using a radix value corresponding to a quantity of binary bits in a bit group corresponding to that byte to generate a plurality of ciphertext bytes, and combining a quantity of least-significant bits from each ciphertext byte in the plurality of ciphertext bytes to generate a binary ciphertext value, the quantity of least-significant bits combined from each ciphertext byte corresponding to the radix value used to generate that ciphertext byte.

Abstract: Systems, methods, and techniques for optimizing a plurality of data integration tasks within a data integration collection by identifying, as a sub-set of the plurality of data integration tasks, a plurality of point-to-point data integration tasks defining a data integration transformation plan to include: generating one or more publication data integration tasks comprising publishing from each respective data source of the plurality of point-to-point data integration tasks to generate a single publication topic; and generating one or more subscription data integration tasks causing each respective target of the plurality of point-to-point data integration tasks to subscribe to the single publication topic; and generating a set of optimization instructions configured to cause the at least one computer to implement the data integration transformation plan; and executing the set of optimization instructions to generate the one or more publication data integration tasks and the one or more subscription tasks.

Abstract: Systems, methods, and related techniques and apparatus containing instructions which when executed by one or more computing devices for determining dataset rankings by determining a lineage ordering requirement for a collection of datasets; determining, from the lineage order requirement, one or more first lineage level datasets from the collection of datasets; generating one or more first lineage level asset ranks respectively for each one of the one or more first lineage level datasets, determining at least one second lineage level dataset having an outflow to the one or more first lineage level datasets; and generating a first dataset rank for the at least one second lineage level dataset as a first function of the outflow and at least one of the one or more first lineage level asset ranks.

Abstract: Apparatus, computer-readable medium, and computer-implemented method for dynamic binding of tasks in a data exchange, including generating an execution plan for the data exchange comprising a plurality of streams, each stream corresponding to a pairing of a producer task and a consumer task and comprising a producer task identifier and a consumer task identifier, binding each producer task to a node at execution time by associating a corresponding producer task identifier with a corresponding node identifier of the node, binding each consumer task to a node at execution time by associating a corresponding consumer task identifier with a node identifier of the corresponding node, and routing an output of each producer task from a node bound to the producer task to a node bound to a paired consumer task by writing the output to a stream corresponding to the pairing of the producer task and the consumer task.

Abstract: An apparatus, computer-readable medium, and computer-implemented method for generating a data proliferation graph, including receiving a selection of a target data store, identifying a plurality of data stores which have either received data that was previously on the target data store or which have sent data that was subsequently on the target data store, the plurality of data stores being divided into a plurality of proliferation levels corresponding to degrees of separation from the target data store and direction of data propagation relative to the target data store, generating a data proliferation graph, and transmitting at least one portion of the data proliferation graph.

Abstract: A system and a method are disclosed for processing hierarchical data structures, for example, XML (extensible markup language) documents. A tree view shows a visual representation of the input schema and the output schema and visual representations of associations between nodes from the input schema and output schema. A grid view shows mapping statements configured to map the input hierarchical data structure conforming to the input schema to an output hierarchical data structure conforming to the output schema. The grid view and the tree view are synchronized such that modifications performed using any one view result in corresponding modifications being presented in the other view. Modifications to mapping statements are validated to determine if path expressions used in the mapping statements are valid in the modified mapping statements.