Abstract: A method for configuring the operation of the software of a data as a service (DAAS) system during run time is described. The configuring includes at least one of configuring ingestion of a vendor dataset to produce an ingested dataset and which analysis operations to perform on the vendor dataset to produce an analyzed dataset, and the configuring also includes at least one of how to search the vendor dataset based on a search query from a customer to allow the customer to locate a new record from the vendor dataset and how to match records in the vendor dataset with a match query from the customer to provide an updated record to the customer.

Abstract: In various embodiments, a system of synchronizing data is described. The system may store data associated with a plurality of data vendors. The system may synchronize the stored data with data from a first data vendor. The received data may be parsed by identifying data values indicated by associated metadata, and modifying the data values based on a universal data format. The system may also receive synchronization requests from a user of the service. The synchronization requests may indicate requested data and a list of processing operations. The requested data may correspond to data received from multiple data vendors. The system may perform the list of processing operations and return the data. Accordingly, the system may manage data received from multiple data vendors even if the data vendors have different synchronization conditions and provide the data in different formats. The data may be analyzed and output together to a user.

Abstract: Some embodiments of the present invention include a system and method for removing duplicate records from a group of records in a database system. The method includes generating a first cluster of records from the group of records, generating a second cluster of records from the group of records, identifying sets of duplicate records in the first cluster of records, and identifying sets of duplicate records in the second cluster of records. The method also includes merging at least two sets of duplicate records associated with both the first cluster and the second cluster of records to form a merged set of duplicate records. The merging is performed based on the at least two sets of duplicate records having a common record. Duplicate records in the group of records may then be removed by removing duplicate records from the merged set of duplicate records.

Abstract: System creates three tries based on values stored in first three fields by records. System associates node in third trie with record, based on value stored in third field by record. System associates node with first dispersion measure, based on values stored in first field by records associated with node, and with second dispersion measure, based on values stored in second field by records associated with node. System identifies branch sequence in third trie as key for prospective record, based on value stored in third field by prospective record. System uses key to identify a subset of records that match prospective record. If a count of the subset exceeds threshold, the system identifies other branch sequence in first trie or second trie as other key for prospective record, based on first dispersion measure and second dispersion measure. System uses the key and the other key to identify at least one record that matches prospective record.

Abstract: The system tokenizes values stored by records' fields, creates trie from tokenized values, each branch labeled with tokenized value, each node storing count indicating number of records associated with tokenized value sequence beginning from trie root. The system tokenizes value stored by record field, identifies nodes, beginning from trie root, corresponding to token value sequence associated with tokenized value, until node is identified that stores count that is less than node threshold. The system identifies branch sequence comprising each identified node as record's key, and associates key with node storing count less than node threshold, and record with key. The system tokenizes prospective value stored by prospective record's field, identifies nodes, beginning from trie root, corresponding to another token value sequence associated with tokenized prospective value, until another node is identified that stores another count that is less than node threshold.

Abstract: A system identifies a first number of distinct values stored in a first field by a dataset of records. The system identifies a second number of distinct values stored in a second field by the dataset of records. The system creates a trie from values stored in a field by multiple records, the field corresponding to the first field or the second field, based on comparing the first number to the second number. The system associates a node in the trie with one of the multiple records, based on a value stored in the field by the record. The system identifies a branch sequence in the trie as a key for a prospective record, based on a prospective value stored in a corresponding field by the prospective record. The system uses the key for the prospective record to identify one of the multiple records that matches the prospective record.

Abstract: Some embodiments of the present invention include a method for determining duplicate records in multiple objects and may include combining records associated with a first object with records associated with a second object to generate a third object, wherein the first object is related to the second object; performing de-duplication on the third object to generate a combined group of duplicate sets; and from the combined group of duplicate sets, identifying at least one duplicate set associated with both the first object and the second object based on the duplicate set having at least one record associated with the first object and at least one record associated with the second object.

Abstract: Some embodiments of the present invention include a system and method for removing duplicate records from a group of records in a database system. The method includes generating a first cluster of records from the group of records, generating a second cluster of records from the group of records, identifying sets of duplicate records in the first cluster of records, and identifying sets of duplicate records in the second cluster of records. The method also includes merging at least two sets of duplicate records associated with both the first cluster and the second cluster of records to form a merged set of duplicate records. The merging is performed based on the at least two sets of duplicate records having a common record. Duplicate records in the group of records may then be removed by removing duplicate records from the merged set of duplicate records.

Abstract: Some embodiments of the present invention include a method for identifying duplicate records from a group of records in a database system.

Abstract: Systems and methods are provided for creating indices and loading key-value pairs for NoSQL databases. Attributes are created that correspond to records in a NoSQL database based on corresponding record fields. An index is created based on the attributes. A memory is loaded with attributes that correspond to a subset of the index as keys in a key-value pair and identifiers that correspond to records that correspond to the attributes as values in the key-value pair. The attributes that correspond to the subset of the index are sorted in the memory. Any duplicate attributes are identified from the sorted attributes in the memory. Any identifiers that correspond to any duplicate attributes also identify records in the NoSQL database to be evaluated as potential duplicate records.

Abstract: Systems and methods are provided for creating indices and loading key-value pairs for NoSQL databases. Attributes are created that correspond to records in a NoSQL database based on corresponding record fields. An index is created based on the attributes. A memory is loaded with attributes that correspond to a subset of the index as keys in a key-value pair and identifiers that correspond to records that correspond to the attributes as values in the key-value pair. The attributes that correspond to the subset of the index are sorted in the memory. Any duplicate attributes are identified from the sorted attributes in the memory. Any identifiers that correspond to any duplicate attributes also identify records in the NoSQL database to be evaluated as potential duplicate records.