Abstract: According to an embodiment of the present invention, a computer-implemented method of cleansing data is provided that comprises determining a criticality score and a complexity score for identified attributes of an enterprise, wherein the criticality score represents a relevance of an attribute to one or more enterprise dimensions and the complexity score represents complexity of cleansing data for an attribute. The identified attributes for data cleansing based on the criticality and complexity scores are prioritized, and data of the identified attributes is cleansed in accordance with priority of the identified attributes. Embodiments further include a system, apparatus and computer readable media to cleanse data in substantially the same manner as described above.

Abstract: Embodiments provide a system and method for integrating a cognitive system into a call center. The system and method include ingesting, in real-time through an instant messaging application, one or more questions from one or more call center agents; ingesting, in real-time through the instant messaging application, one or more answers associated with the one or more questions; storing one or more question and answer pairs in a corpus; analyzing, through a cognitive system, the corpus of the one or more question and answer pairs; receiving, through the instant messaging system, one or more additional questions; determining a proposed answer to each additional question based on the analysis of the corpus; analyzing, through the cognitive system, the proposed answer; and incorporating the analysis of the proposed answer into the analysis of the one or more question and answer pairs. The answers can be provided by subject matter experts or call center managers.

Abstract: Embodiments provide a system and method for integrating a cognitive system into a call center.

Abstract: A system transfers data between source systems and a target system. The system determines a domain score for data domains of source data from the source systems based on data quality metrics for the target system. The domain score indicates data quality with respect to the target system. Corresponding processes of the target system are identified for the data domains, and a process score is determined for the identified processes based on a corresponding domain score. The process score indicates data quality with respect to the identified processes. The system cleanses the source data based on the domain score and/or process score, and validates the cleansed source data against the target system for transference. Embodiments of the present invention further include a method and computer program product for transferring data between source systems and a target system in substantially the same manner described above.

Abstract: Embodiments provide a system and method for integrating a cognitive system into a call center. The system and method include ingesting, in real-time through an instant messaging application, one or more questions from one or more call center agents; ingesting, in real-time through the instant messaging application, one or more answers associated with the one or more questions; storing one or more question and answer pairs in a corpus; analyzing, through a cognitive system, the corpus of the one or more question and answer pairs; receiving, through the instant messaging system, one or more additional questions; determining a proposed answer to each additional question based on the analysis of the corpus; analyzing, through the cognitive system, the proposed answer; and incorporating the analysis of the proposed answer into the analysis of the one or more question and answer pairs. The answers can be provided by subject matter experts or call center managers.

Abstract: According to an embodiment of the present invention, a computer-implemented method of cleansing data is provided that comprises determining a criticality score and a complexity score for identified attributes of an enterprise, wherein the criticality score represents a relevance of an attribute to one or more enterprise dimensions and the complexity score represents complexity of cleansing data for an attribute. The identified attributes for data cleansing based on the criticality and complexity scores are prioritized, and data of the identified attributes is cleansed in accordance with priority of the identified attributes. Embodiments further include a system, apparatus and computer readable media to cleanse data in substantially the same manner as described above.

Abstract: Embodiments provide a system and method for integrating a cognitive system into a call center.

Abstract: Embodiments provide a system and method for integrating a cognitive system into a call center. The system and method include ingesting, in real-time through an instant messaging application, one or more questions from one or more call center agents; ingesting, in real-time through the instant messaging application, one or more answers associated with the one or more questions; storing one or more question and answer pairs in a corpus; analyzing, through a cognitive system, the corpus of the one or more question and answer pairs; receiving, through the instant messaging system, one or more additional questions; determining a proposed answer to each additional question based on the analysis of the corpus; analyzing, through the cognitive system, the proposed answer; and incorporating the analysis of the proposed answer into the analysis of the one or more question and answer pairs. The answers can be provided by subject matter experts or call center managers.

Abstract: According to an embodiment of the present invention, a computer-implemented method of cleansing data is provided that comprises determining a criticality score and a complexity score for identified attributes of an enterprise, wherein the criticality score represents a relevance of an attribute to one or more enterprise dimensions and the complexity score represents complexity of cleansing data for an attribute. The identified attributes for data cleansing based on the criticality and complexity scores are prioritized, and data of the identified attributes is cleansed in accordance with priority of the identified attributes. Embodiments further include a system, apparatus and computer readable media to cleanse data in substantially the same manner as described above.

Abstract: A system transfers data between source systems and a target system. The system determines a domain score for data domains of source data from the source systems based on data quality metrics for the target system. The domain score indicates data quality with respect to the target system. Corresponding processes of the target system are identified for the data domains, and a process score is determined for the identified processes based on a corresponding domain score. The process score indicates data quality with respect to the identified processes. The system cleanses the source data based on the domain score and/or process score, and validates the cleansed source data against the target system for transference. Embodiments of the present invention further include a method and computer program product for transferring data between source systems and a target system in substantially the same manner described above.

Abstract: A computer-implemented method for processing information related to an extract-transform-load (ETL) data migration, including aggregating operational metadata and determining: a plurality of metrics, organized by business object, corresponding to the migration; a number of business object instances not successfully loaded; a first end-to-end execution time for at least one business object; relevant input metadata; load readiness status per business object; impact of a business object that is not load ready by analyzing business process hierarchies; business object load readiness by reference to incomplete development status or data defects; scope per test cycle based, at least in part, upon business object load readiness; and high-priority defects of business objects that stop testing based, at least in part, upon analysis of business process hierarchies.

Abstract: According to an embodiment of the present invention, a computer-implemented method of cleansing data is provided that comprises determining a criticality score and a complexity score for identified attributes of an enterprise, wherein the criticality score represents a relevance of an attribute to one or more enterprise dimensions and the complexity score represents complexity of cleansing data for an attribute. The identified attributes for data cleansing based on the criticality and complexity scores are prioritized, and data of the identified attributes is cleansed in accordance with priority of the identified attributes. Embodiments further include a system, apparatus and computer readable media to cleanse data in substantially the same manner as described above.

Abstract: A system transfers data between source systems and a target system. The system determines a domain score for data domains of source data from the source systems based on data quality metrics for the target system. The domain score indicates data quality with respect to the target system. Corresponding processes of the target system are identified for the data domains, and a process score is determined for the identified processes based on a corresponding domain score. The process score indicates data quality with respect to the identified processes. The system cleanses the source data based on the domain score and/or process score, and validates the cleansed source data against the target system for transference. Embodiments of the present invention further include a method and computer program product for transferring data between source systems and a target system in substantially the same manner described above.

Abstract: A system transfers data between source systems and a target system. The system determines a domain score for data domains of source data from the source systems based on data quality metrics for the target system. The domain score indicates data quality with respect to the target system. Corresponding processes of the target system are identified for the data domains, and a process score is determined for the identified processes based on a corresponding domain score. The process score indicates data quality with respect to the identified processes. The system cleanses the source data based on the domain score and/or process score, and validates the cleansed source data against the target system for transference. Embodiments of the present invention further include a method and computer program product for transferring data between source systems and a target system in substantially the same manner described above.

Abstract: A computer-implemented method for processing information related to an extract-transform-load (ETL) data migration, including aggregating operational metadata and determining: a plurality of metrics, organized by business object, corresponding to the migration; a number of business object instances not successfully loaded; a first end-to-end execution time for at least one business object; relevant input metadata; load readiness status per business object; impact of a business object that is not load ready by analyzing business process hierarchies; business object load readiness by reference to incomplete development status or data defects; scope per test cycle based, at least in part, upon business object load readiness; and high-priority defects of business objects that stop testing based, at least in part, upon analysis of business process hierarchies.

Abstract: For creating a data governance assessment, a response module receives responses to an automated questionnaire. A scoring module computes a data governance assessment comprising a maturity level describing organizational adoption of data governance, a data governance model describing a data centralization level, and a framework describing a tier of data governance by calculating the maturity level, the data governance model, and the framework from the responses.

Abstract: In one or more embodiments of the invention, functional data analysts may use a functional data authoring module to capture functional metadata in a consistent manner. Conflict reports for the business processes may be generated for a subset of the business processes or as an overall report across all business processes. One or more embodiments of the invention may provide early detection of data usage and type conflicts from functional data requirements, automated detection of conflicts from functional data requirements, reports listing detected conflicts, conflicts resolution tracking mechanism, ongoing notification regarding changes in functional data requirements or detected conflicts, and avoidance of conflicting functional requirement in the realization phase, thereby reducing costs and project risks and avoiding project delays.

Abstract: In one or more embodiments of the invention, functional data analysts may use a functional data authoring module to capture functional metadata in a consistent manner. Conflict reports for the business processes may be generated for a subset of the business processes or as an overall report across all business processes. One or more embodiments of the invention may provide early detection of data usage and type conflicts from functional data requirements, automated detection of conflicts from functional data requirements, reports listing detected conflicts, conflicts resolution tracking mechanism, ongoing notification regarding changes in functional data requirements or detected conflicts, and avoidance of conflicting functional requirement in the realization phase, thereby reducing costs and project risks and avoiding project delays.

Abstract: For creating a data governance assessment, a response module receives responses to an automated questionnaire. A scoring module computes a data governance assessment comprising a maturity level describing organizational adoption of data governance, a data governance model describing a data centralization level, and a framework describing a tier of data governance by calculating the maturity level, the data governance model, and the framework from the responses.