Abstract: Apparatus and method for a scalable pricing engine. A scalable pricing engine is operable in a low-scale mode and a high-scale or scalable mode to process pricing data in response to pricing requests. The pricing engine operates in a first runtime environment in the low-scale mode in which it can service pricing requests up to a threshold number and in which the pricing data can be updated and tested. The pricing engine also operates in a second runtime environment which is a scalable runtime supporting pricing requests above the specified threshold. The scalable runtime and pricing engine rely on a scalable read-only data service which distributes a read-only copy of at least a portion of the pricing data from the primary database, a high-scale cache to reduce access latency, data processing and network resource allocations, and data reduction techniques when processing requests and responses.

Abstract: Apparatus and method for asynchronous pricing. For example, some implementations include an asynchronous pricing service in addition to the pricing service. When performing a first pricing operation on a first set of pricing data, the pricing service performs operations on a pricing engine. In response to a second pricing request at the asynchronous pricing service with a second set of pricing data, the second set of pricing data is subdivided into a plurality of portions and a corresponding plurality of pricing jobs are specified, which are independently executed by the pricing engine to produce a corresponding plurality of partial pricing results. The asynchronous pricing service aggregates the partial pricing results to generate a second pricing result.

Abstract: Embodiments are directed to a pluggable architecture for performance of pricing operations. An embodiment of a storage medium includes instructions for installing multiple pricing methods at a pricing service including a pluggable architecture for pricing methods, each pricing method including a set of pricing functions; receiving a pricing request for a sales transaction including one or more sales items, the pricing request including a pricing context for each sales item; and performing a price calculation for the sales transaction, including resolving a pricing method for each sales item, applying the set of pricing functions for the resolved pricing method for each sales item, the application of the set of pricing functions being based at least in part on the pricing context for the sales item, calculating a price for each sales item based upon an outcome of the pricing functions, and aggregating the calculated prices for the sales items.

Abstract: Pluggable pricing modules with functional extension points. A plurality of pricing methods are installed with a pricing service. The pricing service has a pluggable architecture to accept pricing methods including a set of pricing functions, and one or more extension points that provide programmatic hooks within an operational flow of the pricing service to provide optional interfaces to functional modules external to the pricing service. In response to a pricing request for a sales transaction, the pricing request including a pricing resolving selected pricing method for each sales item of the one or more sales items from the plurality of pricing methods. At least one of the one or more extension points are used to call an external functional module to interact with the operational flow of the pricing service. Aggregated results are provided to the source of the pricing request.

Abstract: Disclosed herein are system, method, and computer program product embodiments for detecting duplicates with exact and fuzzy matching on encrypted match indexes using an encryption key in a cloud computing platform. An embodiment operates by determining a match rule index value upon reception of a new record. The embodiment encrypts the match index rule value using the customer's encryption key and a deterministic encryption method and stores the encrypted match rule index value. Duplicate detection may be later performed by using the same deterministic encryption method to determine a cypher text for a candidate entry and comparing the ciphertext to the stored encrypted match indexes.

Abstract: Provided herein are system, methods and computer program products for identifying duplicate records stored in a database system, comprising: generating a plurality of encrypted match indexes for each of a plurality of records stored in the database system, each of the plurality of encrypted match indexes encrypts a value of each encryption enabled field of a respective one of the plurality of records defined by at least one match rule, creating a cluster of records comprising at least one set containing at least two records of the plurality of records, the at least two records having respective encrypted match indexes corresponding to the at least one match rule, causing identification of duplicate records in the at least one set according to detection of records of the at least one set having respective match indexes matching the at least one match rule, and outputting an indication of the identified duplicate records.

Abstract: Methods for splitting a plurality of records into subsets for parallel processing by separate threads are disclosed. In one embodiment, a plurality of records are added to a database. The adding includes tracking, for each unique value found in the plurality of records within a selected one of the sequence of fields, a statistic based on the values found in the plurality of records within a next one of the sequence of fields. Then a plurality of queries are generated, each includes a row value constructor (RVC) with a logical operation, a specific one of the unique values found within the selected one of the sequence of fields, and, for that specific value, the tracked statistic. Then a plurality of threads are caused to execute that each submit one of the queries and operate on a subset of the plurality of records responsive to execution of that query.

Abstract: Preservation of price calculation data in performance of price calculation operations is described. An example of a system includes one or more processors, a memory, an API to receive requests, a pricing service to generate price calculations, and price data functions to perform operations on price calculation data, wherein in response to a request for price calculation for a first transaction the system is to generate a unique transaction identifier; record context data for the price calculation; calculate a pricing result for each of one or more sales items and collect price calculation data for each sales item; aggregate the pricing results to generate a final pricing result, generate a price calculation data set for the first transaction including at least the transaction identifier, the context data, and the price calculation data for the sales items, and store the generated price calculation data set in the memory.

Abstract: Provided herein are system, methods and computer program products for identifying duplicate records stored in a database system, comprising: generating a plurality of encrypted match indexes for each of a plurality of records stored in the database system, each of the plurality of encrypted match indexes encrypts a value of each encryption enabled field of a respective one of the plurality of records defined by at least one match rule, creating a cluster of records comprising at least one set containing at least two records of the plurality of records, the at least two records having respective encrypted match indexes corresponding to the at least one match rule, causing identification of duplicate records in the at least one set according to detection of records of the at least one set having respective match indexes matching the at least one match rule, and outputting an indication of the identified duplicate records.

Abstract: A system receives an object selection, and outputs the object. The system receives a first service selection, outputs the first service's object, receives a second service selection, and outputs the second service's object. The system receives selections of the object's first field and the first service object's field, and stores first metadata that maps between the object's first field and the first service object's field. The system receives selections of the object's second field and the second service object's field, and stores second metadata that maps between the object's second field and the second service object's field. The system updates an object instance by using the first metadata to send first request data to the first service and receive first response data from the first service, and by using the second metadata to send second request data to the second service and receive second response data from the second service.

Abstract: Embodiments regard pricing operation using artificial intelligence for price adjustment. An embodiment of one or more mediums include instructions for receiving a request at a pricing platform for pricing of sales items in a sales transaction, including a first sales item; generating a price for the first sales item; and determining whether a dynamic price adjustment function is enabled for the first sales item, and, if so, performing the dynamic adjustment price function for the first sales item, including accessing a trained neural network trained for price adjustments based at least in part on training data including news data from one or more sources and data regarding pricing, receiving a dynamic price adjustment for the first sales item from the trained neural network, and applying the dynamic price adjustment to the generated price to produce an adjusted price for the first sales item.

Abstract: Embodiments regard pricing operations utilizing a uniform abstract sales transaction model. An embodiment of one or more storage mediums include instructions for receiving a pricing request for pricing of one or more sales items, the pricing request including a sales transaction, the sales transaction being a data structure that includes an input parameter, the input parameter including input data; directing the sales transaction to a pricing engine for the sales operation; performing pricing for each sales item of one or more sales items based on the sales transaction to generate a pricing output; generating an output parameter utilizing the input parameter, and inserting the pricing output into the output parameter; and generating a pricing response including the sales transaction with the output parameter, the sales transaction data structure being unchanged by the pricing engine.

Abstract: Pluggable pricing modules with functional extension points. A plurality of pricing methods are installed with a pricing service. The pricing service has a pluggable architecture to accept pricing methods including a set of pricing functions, and one or more extension points that provide programmatic hooks within an operational flow of the pricing service to provide optional interfaces to functional modules external to the pricing service. In response to a pricing request for a sales transaction, the pricing request including a pricing resolving selected pricing method for each sales item of the one or more sales items from the plurality of pricing methods. At least one of the one or more extension points are used to call an external functional module to interact with the operational flow of the pricing service. Aggregated results are provided to the source of the pricing request.

Abstract: Embodiments regard determination and optimization of pricing plans for sales transactions. An embodiment of one or more storage mediums include instructions for receiving a request for pricing of a sales transaction including one or more sales items; storing the sales transaction in memory for analysis; performing a static analysis of the sales transaction, including scanning the received sales transaction in memory to analyze structure and content of the sales transaction; generating an initial pricing plan for the sales transaction based on the static analysis; commencing a price calculation for the sales transaction; identifying one or more inefficiencies in the initial pricing plan during the price calculation; and dynamically modifying the initial pricing plan based at least in part on the identified one or more inefficiencies to improve performance of pricing for the sales transaction.

Abstract: Embodiments are directed to a pluggable architecture for performance of pricing operations. An embodiment of a storage medium includes instructions for installing multiple pricing methods at a pricing service including a pluggable architecture for pricing methods, each pricing method including a set of pricing functions; receiving a pricing request for a sales transaction including one or more sales items, the pricing request including a pricing context for each sales item; and performing a price calculation for the sales transaction, including resolving a pricing method for each sales item, applying the set of pricing functions for the resolved pricing method for each sales item, the application of the set of pricing functions being based at least in part on the pricing context for the sales item, calculating a price for each sales item based upon an outcome of the pricing functions, and aggregating the calculated prices for the sales items.

Abstract: Disclosed herein are system, method, and computer program product embodiments for detecting duplicates with exact and fuzzy matching on encrypted match indexes using an encryption key in a cloud computing platform. An embodiment operates by determining a match rule index value upon reception of a new record. The embodiment encrypts the match index rule value using the customer's encryption key and a deterministic encryption method and stores the encrypted match rule index value. Duplicate detection may be later performed by using the same deterministic encryption method to determine a cypher text for a candidate entry and comparing the ciphertext to the stored encrypted match indexes.

Abstract: Disclosed herein are system, method, and computer program product embodiments for detecting duplicates with exact and fuzzy matching on encrypted match indexes using an encryption key in a cloud computing platform. An embodiment operates by determining a match rule index value upon reception of a new record. The embodiment encrypts the match index rule value using the customer's encryption key and a deterministic encryption method and stores the encrypted match rule index value. Duplicate detection may be later performed by using the same deterministic encryption method to determine a cypher text for a candidate entry and comparing the ciphertext to the stored encrypted match indexes.

Abstract: Methods for splitting a plurality of records into subsets for parallel processing by separate threads are disclosed. In one embodiment, a plurality of records are added to a database. The adding includes tracking, for each unique value found in the plurality of records within a selected one of the sequence of fields, a statistic based on the values found in the plurality of records within a next one of the sequence of fields. Then a plurality of queries are generated, each includes a row value constructor (RVC) with a logical operation, a specific one of the unique values found within the selected one of the sequence of fields, and, for that specific value, the tracked statistic. Then a plurality of threads are caused to execute that each submit one of the queries and operate on a subset of the plurality of records responsive to execution of that query.

Abstract: Some embodiments of the present invention include a method for performing data assessment. The method includes receiving, by a first server computing system, a request to assess first data stored in a storage device associated with a second server computing system, the request including one or more rules indicating how the first data is to be assessed; performing, by the first server computing system, an assessment of the first data based on the one or more rules and based on a data source associated with the first server computing system, the data source including data provided by one or more data providers, the assessment of the first data including assessing outdated information and missing information based on the data source; and providing, by the first server computing system, an assessment result from the assessment of the first data and an option to engage in an enrichment of the first data based on the assessment result and the data source.

Abstract: Methods for splitting a plurality of records into subsets for parallel processing by separate threads are disclosed. In one embodiment, a plurality of records are added to a database. The adding includes tracking, for each unique value found in the plurality of records within a selected one of the sequence of fields, a statistic based on the values found in the plurality of records within a next one of the sequence of fields. Then a plurality of queries are generated, each includes a row value constructor (RVC) with a logical operation, a specific one of the unique values found within the selected one of the sequence of fields, and, for that specific value, the tracked statistic. Then a plurality of threads are caused to execute that each submit one of the queries and operate on a subset of the plurality of records responsive to execution of that query.