Abstract: The present disclosure relates to methods and systems for processing data via a data profiling process. Data profiling can include modifying attributes included in source data and identifying aspects of the source data. The data profiling process can include processing an attribute according to a set of validation rules to validate information included in the attribute. The process can also include processing the attribute according to a set of standardization rules to modify the attribute into a standardized format. The process can also include processing the attribute according to a set of rules engines. The modified attributes can be outputted for further processing. The data profiling process can also include deriving a value score and usage rank of an attribute, which can be used in deriving insights into the source data.

Abstract: The present disclosure is directed to continuous data profiling (CDP). Entities may house large amounts of disorganized and/or duplicative data. To organize and standardize data across a data set, the data may be profiled. However, profiling large data set can be inefficient and give rise to security problems, as profiling datasets typically requires exporting a dataset to a third-party profiling runtime environment. To remedy these issues, the present disclosure is directed to a continuous data profiling platform that comprises a CDP manager communicatively coupled to a client's database. The CDP manager provides access to a CDP API that may install CDP tools on a client's native database environment, enabling the database management system to profile datasets within the client's native database environment, which results in a more efficient use of computing resources and more secure process of profiling datasets.

Abstract: The present disclosure relates to methods and systems for contextual data masking and registration. A data masking process may include classifying ingested data, processing the data, and tokenizing the data while maintaining security/privacy of the ingested data. The data masking process may include data configuration that comprises generating anonymized labels of the ingested data, validating an attribute of the ingested data, standardizing the attribute into a standardized format, and processing the data via one or more rules engines. One rules engine can include an address standardization that generates a list of standard addresses that can provide insights into columns of the ingested data without externally transmitting the client data. The masked data can be tokenized as part of the data masking process to securely maintain an impression of the ingested data and generate insights into the ingested data.

Abstract: The present disclosure is directed to systems and methods for reference source matching. Specifically, the systems and methods disclosed enable matching among tokens using a reference source. In one example, a Consolidation Platform may receive tokens from a customer environment and tokens from a reference source environment. The customer tokens may be compared to each other using AB matching. If a match does not occur, the customer tokens may further be compared to the reference source tokens via transitive matching. If a match does occur, then the customer tokens may be denoted as a match. In further example aspects, the reference source may be a universal reference token repository that comprises unique tokens. If, after a match is indicated, the matched token(s) may be compared to the universal reference token repository. If the matched token(s) does not exist, it may be added to the repository for future use.

Abstract: The present disclosure is directed to continuous data profiling (CDP). Entities may house large amounts of disorganized and/or duplicative data. To organize and standardize data across a data set, the data may be profiled. However, profiling large data set can be inefficient and give rise to security problems, as profiling datasets typically requires exporting a dataset to a third-party profiling runtime environment. To remedy these issues, the present disclosure is directed to a continuous data profiling platform that comprises a CDP manager communicatively coupled to a client's database. The CDP manager provides access to a CDP API that may install CDP tools on a client's native database environment, enabling the database management system to profile datasets within the client's native database environment, which results in a more efficient use of computing resources and more secure process of profiling datasets.

Abstract: The present disclosure relates to methods and systems for contextual data masking and registration. A data masking process may include classifying ingested data, processing the data, and tokenizing the data while maintaining security/privacy of the ingested data. The data masking process may include data configuration that comprises generating anonymized labels of the ingested data, validating an attribute of the ingested data, standardizing the attribute into a standardized format, and processing the data via one or more rules engines. One rules engine can include an address standardization that generates a list of standard addresses that can provide insights into columns of the ingested data without externally transmitting the client data. The masked data can be tokenized as part of the data masking process to securely maintain an impression of the ingested data and generate insights into the ingested data.

Abstract: The present disclosure is directed to systems and methods for reference source matching. Specifically, the systems and methods disclosed enable matching among tokens using a reference source. In one example, a Consolidation Platform may receive tokens from a customer environment and tokens from a reference source environment. The customer tokens may be compared to each other using AB matching. If a match does not occur, the customer tokens may further be compared to the reference source tokens via transitive matching. If a match does occur, then the customer tokens may be denoted as a match. In further example aspects, the reference source may be a universal reference token repository that comprises unique tokens. If, after a match is indicated, the matched token(s) may be compared to the universal reference token repository. If the matched token(s) does not exist, it may be added to the repository for future use.

Abstract: The present disclosure is directed to embodiments directed to systems and methods for policy management. In some implementations, a master policy management system can create a policy template in which all policies of a user can be built, monitored, and enforced. The master policy management system can create a taxonomy for the policy template and receive access and control settings for the policy template from the user. A user can generate policies in the policy template and the master policy management system can review and certify the policies based the accuracy of the policies. Once a policy is built, the master policy management system can review and certify the policy, provide a quality score for the policy, perform lifecycle management, record the policy use, and report alerts regarding the policy.

Abstract: The present disclosure is directed to a universal data language (UDL) translator. Specifically, the systems and methods disclosed enable input data from a variety of sources to be translated into a UDL that can be consistently analyzed and compared against other sources of data. For example, an entity may upload input data that has a plurality of data terms and definitions (e.g., header column in a spreadsheet). These terms may be duplicative and/or inaccurate with respect to the underlying data. If the entity wishes to compare and transact data within a data marketplace, the entity may not fully comprehend what data it is missing and/or what data another entity may have to offer for trade. To remedy this problem of business semantic management, the present invention discloses steps for creating a UDL and a UDL translator so that any input data can be translated to UDL.

Abstract: The present disclosure is directed to continuous data profiling (CDP). Entities may house large amounts of disorganized and/or duplicative data. To organize and standardize data across a data set, the data may be profiled. However, profiling large data set can be inefficient and give rise to security problems, as profiling datasets typically requires exporting a dataset to a third-party profiling runtime environment. To remedy these issues, the present disclosure is directed to a continuous data profiling platform that comprises a CDP manager communicatively coupled to a client's database. The CDP manager provides access to a CDP API that may install CDP tools on a client's native database environment, enabling the database management system to profile datasets within the client's native database environment, which results in a more efficient use of computing resources and more secure process of profiling datasets.

Abstract: The present disclosure is directed to a data marketplace for enriching data records. Specifically, the systems and methods disclosed enable the enrichment of data via matching, identifying composite data records, and utilizing Reference Source datasets. In one example aspect, Customer data is tokenized and then subsequently transmitted to a third-party Data Marketplace Platform. Similarly, a Reference Source dataset may be tokenized and transmitted to a Data Marketplace Platform. On the Data Marketplace Platform, the customer data and the reference source data may be compared, wherein certain data attributes (i.e., tokens on the Data Marketplace Platform) may be identified as missing in the customer dataset and present in the reference source dataset. The customer may then have the ability to acquire the missing and value-added data attributes by transacting with the reference source via a data broker, such as the Data Marketplace Platform.

Abstract: The present disclosure relates to methods and systems for contextual data masking and registration. A data masking process may include classifying ingested data, processing the data, and tokenizing the data while maintaining security/privacy of the ingested data. The data masking process may include data configuration that comprises generating anonymized labels of the ingested data, validating an attribute of the ingested data, standardizing the attribute into a standardized format, and processing the data via one or more rules engines. One rules engine can include an address standardization that generates a list of standard addresses that can provide insights into columns of the ingested data without externally transmitting the client data. The masked data can be tokenized as part of the data masking process to securely maintain an impression of the ingested data and generate insights into the ingested data.

Abstract: The present disclosure relates to methods and systems for contextual data masking and registration. A data masking process may include classifying ingested data, processing the data, and tokenizing the data while maintaining security/privacy of the ingested data. The data masking process may include data configuration that comprises generating anonymized labels of the ingested data, validating an attribute of the ingested data, standardizing the attribute into a standardized format, and processing the data via one or more rules engines. One rules engine can include an address standardization that generates a list of standard addresses that can provide insights into columns of the ingested data without externally transmitting the client data. The masked data can be tokenized as part of the data masking process to securely maintain an impression of the ingested data and generate insights into the ingested data.

Abstract: The present disclosure is directed to systems and methods for enriching data. Specifically, the systems and methods disclosed enable the enrichment of data via matching, identifying composite data records, and utilizing Reference Source datasets. In one example aspect, Customer data is tokenized and then subsequently transmitted to a third-party Consolidation Platform. The Customer tokens may comprise multiple token records, wherein the multiple token records are displayed in the form of a bitmap. The bitmap may indicate which attributes in a Customer record may be present or absent. The composited Customer token records may then be matched to a Reference Source token set, wherein the matching analysis identifies missing data attributes in the Customer token set that the Customer may or may not already possess. The missing data attributes may be populated and/or updated in a Customer environment based on the Reference Source token set.

Abstract: The present disclosure is directed to systems and methods for reference source matching. Specifically, the systems and methods disclosed enable matching among tokens using a reference source. In one example, a Consolidation Platform may receive tokens from a customer environment and tokens from a reference source environment. The customer tokens may be compared to each other using AB matching. If a match does not occur, the customer tokens may further be compared to the reference source tokens via transitive matching. If a match does occur, then the customer tokens may be denoted as a match. In further example aspects, the reference source may be a universal reference token repository that comprises unique tokens. If, after a match is indicated, the matched token(s) may be compared to the universal reference token repository. If the matched token(s) does not exist, it may be added to the repository for future use.

Abstract: The present disclosure relates to methods and systems for processing data via a data profiling process. Data profiling can include modifying attributes included in source data and identifying aspects of the source data. The data profiling process can include processing an attribute according to a set of validation rules to validate information included in the attribute. The process can also include processing the attribute according to a set of standardization rules to modify the attribute into a standardized format. The process can also include processing the attribute according to a set of rules engines. The modified attributes can be outputted for further processing. The data profiling process can also include deriving a value score and usage rank of an attribute, which can be used in deriving insights into the source data.

Abstract: The present disclosure relates to methods and systems for contextual data masking and registration. A data masking process may include classifying ingested data, processing the data, and tokenizing the data while maintaining security/privacy of the ingested data. The data masking process may include data configuration that comprises generating anonymized labels of the ingested data, validating an attribute of the ingested data, standardizing the attribute into a standardized format, and processing the data via one or more rules engines. One rules engine can include an address standardization that generates a list of standard addresses that can provide insights into columns of the ingested data without externally transmitting the client data. The masked data can be tokenized as part of the data masking process to securely maintain an impression of the ingested data and generate insights into the ingested data.

Abstract: A method, apparatus, and computer program product for processing data is disclosed. In one aspect of the invention, a computer implemented method comprises receiving, on one or more computers, a record having one or more attributes from a source system. The method also comprises measuring, on one or more computers, a data accuracy of the received record as compared to a golden record stored in a master data management system. One or more remediation actions are performed, on one or more computers, to enforce improvements to the measured data accuracy of the received record in the source system. In one or more embodiments, measurement of data accuracy comprises calculating, on one or more computers, an accuracy score defined by a closeness of the received record to the golden record.

Abstract: A method, apparatus, and computer program product for processing data is disclosed. In one aspect of the invention, a computer implemented method comprises receiving, on one or more computers, a record having one or more attributes from a source system. The method also comprises measuring, on one or more computers, a data accuracy of the received record as compared to a golden record stored in a master data management system. One or more remediation actions are performed, on one or more computers, to enforce improvements to the measured data accuracy of the received record in the source system. In one or more embodiments, measurement of data accuracy comprises calculating, on one or more computers, an accuracy score defined by a closeness of the received record to the golden record.

Abstract: Systems and methods for indexing, associating or compositing data records and hierarchies from various information sources are disclosed. Embodiments of the present invention may provide the ability to link data records and thus to link data records to known hierarchies of data records. More specifically, embodiments of the present invention may provide the capability to associate data records in varying information sources and to thereby associate incoming data record with existing data records or existing data hierarchies such that an incoming data record may not only be associated with an existing data record comprising information about the same entity but may additionally be associated with other members of the data hierarchy in the same manner as the existing data record.