International Business Machines Corporation

Royal Caribbean Cruises Ltd.

Sol Rashidi

Martin Oberhofer

Ram S Narayanan

Carl Michael Marrelli

Arya Eskamani

Carlos Merida

Mallori Harrell

A method, system and computer program product for data deduplication in a travel and transportation data processing system includes loading into memory for comparison from a database of a multiplicity of multi-field records, a pair of two different multi-field records and submitting the pair to a similarity model that correlates a companion passenger with a specified individual so as to indicate a probability of duplication whenever the companion passenger appears in a pair of records submitted to the model for comparison. Thereafter, if the model produces a high probability, the pair is automatically merged into a single record without manual intervention, but if the model produces a medium probability, the pair is placed in a queue pending manual intervention and manual merging, and if the similarity model produces a low probability, the pair is omitted from consideration of merging. Finally, the process repeats for each other pair of different multi-field records in the database.

Data deduplication in a travel and transportation data processing system

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.

Data cleansing and governance using prioritization schema

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.

Data quality analysis and cleansing of source data with respect to a target system

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.

Processing data in data migration

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.

Computing and managing conflicting functional data requirements using ontologies

A computer implemented method, system, and/or computer program product generates technical business data requirements from functional process requirements. Such method, system, and/or computer program product include data processing infrastructure. The data processing infrastructure may further include at least one data persistence component and at least one business process hierarchy. The computer implemented method, system, and/or computer program product obtain a set of technical elements concerning functional process requirements for each business process within the business process hierarchy. Such method, system, and/or computer program product classify technical elements into functional objects, link each of the functional objects to at least one process within the business process hierarchy and generate a plurality of business data roadmap templates in the data processing infrastructure. The generated business data roadmap templates are stored in the persistence component of the data processing infrastructure.

Software tool for generating technical business data requirements

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.

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Miami Beach, FL, United States of America

Sol Rashidi