Abstract: Disclosed herein is a method and a failure prediction system for predicting failures in a diverse set of asset types in an enterprise. In an embodiment, asset information related each assets are analyzed for determining an asset type and a failure mode of each of the assets. Thereafter, one of a plurality of prediction models is selected for predicting failures in each of the assets based on the asset type and the failure mode of each of the assets. Finally, selected one of the plurality of prediction models is used to analyze the asset information for predicting the failures in each of the assets. In an embodiment, the present disclosure provides a universal failure prediction system for predicting failures in the diverse set of asset types and thereby eliminates requirement of using multiple prediction systems for predicting failures in each type of the assets.

Abstract: Disclosed herein is a method and a failure prediction system for predicting failures in a diverse set of asset types in an enterprise. In an embodiment, asset information related each assets are analyzed for determining an asset type and a failure mode of each of the assets. Thereafter, one of a plurality of prediction models is selected for predicting failures in each of the assets based on the asset type and the failure mode of each of the assets. Finally, selected one of the plurality of prediction models is used to analyze the asset information for predicting the failures in each of the assets. In an embodiment, the present disclosure provides a universal failure prediction system for predicting failures in the diverse set of asset types and thereby eliminates requirement of using multiple prediction systems for predicting failures in each type of the assets.

Abstract: A method and device for automatically generating Extract Transform Load (ETL) codes includes a code generation device that automatically detects one or more ETL patterns based on the received predefined ETL codes. The code generation device scans pattern database which comprises one or more ETL patterns to determine the presence of the one or more detected ETL patterns. Upon selecting the detected one or more ETL patterns by the user, the code generation device retrieves the selected one or more ETL patterns from the pattern database. User inputs are received for each of the one or more ETL patterns retrieved from the pattern database. The code generation device automatically identifies one or more ETL mappings from the primary data source to the secondary data source for each of the one or more ETL patterns and automatically generates ETL codes based on the one or more ETL mappings.

Abstract: The present disclosure relates to a method and a system for enabling real time location based personalized offer management to a customer. In one embodiment, the method identifies a plurality of customers likely visiting the store, and determines a plurality of relevant personalized bars that can be provided to the identified customers. Th.e method further receives real time information about the presence of customers within the store and provides the in-store customers with one or more real time recommendations of offers on products based on the usage of the relevant personalized offers. Thus, the method and system provides personalized promotional offer based on convenience of individual customers, customers interest on different products on real-time within the establishment. Further, the method and system also provides alternate offers to customers present within store and assess the promotional effectiveness of the campaign on a real-time basis.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media for assessing data quality in multi-stage, multi-source batch processes that do not require validation of input data prior to processing. Embodiments of the present disclosure are further capable of identifying or predicting potential data quality issues, assessing their impact (if any) on the batch process, and providing recommendations for preventing or resolving the identified or predicted data quality issues.

Abstract: A method, non-transitory computer readable medium, and a service management computing device comprises obtaining one or more call detail records associated with one or more customers from one or more data sources. Each of the obtained call detail records is scanned to determine presence of a call drop in each of the obtained call detail records. Next, a customer experience index and an impact value is determined for the one or more call detail records for which the call drop is determined to be present. Based on the determined experience index, one or more actions are performed.