Abstract: Techniques for consent centric data compliance checking are disclosed. In an example embodiment, multiple applications associated with an organization are received. Further, a purpose for each of the multiple applications associated with the organization is derived. Furthermore, consents of data subjects are captured for the derived purpose of each of the multiple application in a data subject preference master. Also, reconciliation of the data subject preference master and data subjects' data available in the organization is performed to determine consent lacking information.

Abstract: Techniques for consent centric data compliance checking are disclosed. In an example embodiment, multiple applications associated with an organization are received. Further, a purpose for each of the multiple applications associated with the organization is derived. Furthermore, consents of data subjects are captured for the derived purpose of each of the multiple application in a data subject preference master. Also, reconciliation of the data subject preference master and data subjects' data available in the organization is performed to determine consent lacking information.

Abstract: A method and a system to enable enterprise data management are disclosed. The method for enterprise data management consists of extracting discriminative terms from enterprise policies comprising enterprise level rules and data management goals. Further, one or more data management services and operational unit information are identified corresponding to the discriminative terms. Each data management service comprises of one or more parameters. Subsequently, conceptual enterprise data elements related to the discriminative terms are derived from a data dictionary corresponding to the enterprise policies. Furthermore, a multi-level mapping of the parameters and the operational unit information with one or more corresponding resource databases is performed. The plurality of resource databases comprises of work-items, execution information, geographical area and work-item data associated with each of the work-items.

Abstract: Systems and methods for signal detection are described. The method comprises obtaining, by a data processing module, data from one or more data sources. The method further comprises standardizing the data, by the data processing module, based on at least one template to obtain standardized data. The standardized data have data properties depicting a format and a size of the data. Further, the method comprises determining, by an analysis module, one or more detection rules based on at least one of recommendation data and the data properties of the standardized data. The method further comprises detecting, by the analysis module, at least one signal present in the standardized data based on the one or more detection rules.

Abstract: Systems and methods for signal detection are described. The method comprises obtaining, by a data processing module, data from one or more data sources. The method further comprises standardizing the data, by the data processing module, based on at least one template to obtain standardized data. The standardized data have data properties depicting a format and a size of the data. Further, the method comprises determining, by an analysis module, one or more detection rules based on at least one of recommendation data and the data properties of the standardized data. The method further comprises detecting, by the analysis module, at least one present in the standardized data based on the one or more detection rules.

Abstract: A method comprising receiving a data insertion request, where the data insertion request includes a data reference, indicating data to be stored, and a data repository indicator indicating a data repository, from amongst a plurality of data repositories in which the data is to be stored, and wherein at least one data repository from the plurality of data repositories is a big data system. Further, a resource type, from amongst one or more resource types, corresponding to the data repository, is identified based on the data insertion request. Further, a configuration element, from amongst one or more configuration elements, corresponding to the data repository is determined based on the resource type. Further, an application programming interface (API) associated with the configuration element is triggered for establishing a connection with the data repository for storing the data.

Abstract: An assessment system for assessment of Open Source Software (OSS) products including a computation module configured to receive a rating, for product criterions of each OSS product from an assessor, based on product parameters of each of the OSS products. The product criterions are associated with one or more product categories. The computation module is further configured to compute a product weighted score for each product criterion based at least on the rating and then generates a product scorecard for each OSS product. Upon generation of the product scorecards, an assessing module is configured to identify an optimum OSS product amongst the OSS products based on the assessment of the product scorecard and a benchmark scorecard of an OSS product.

Abstract: A system and method for processing data in a big data storage system has been described, wherein the data is being pulled, transformed and loaded from a singular or a plurality of source systems to a big data storage system, Further, a query engine is configured to execute one or more query in a real-time for retrieving the data from the target big data storage system and a processor maps the executed query with the data thus stored by generating a key value in a preset format with respect to each query, such that the query results are retrieved by scanning the target big data storage system in accordance with the key value thus formed.