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Role of Business Intelligence and HR Planning in Modern Industrialization
Published in Deepmala Singh, Anurag Singh, Amizan Omar, S.B. Goyal, Business Intelligence and Human Resource Management, 2023
This subsystem manages the collection, storage, and structuring of data into databases in the following formats: Data LakeData Lake is a huge set of raw data that are stored in the native format for a purpose not yet defined.Data WarehouseData Warehouse is a storehouse for organized, filtered, and processed data.Data MartData Mart is a subset of a data warehouse, but it holds data only for a specific department or line of business, such as sales, finance, or HRs.Operational Data StoreOperational Data Store is a snapshot of data gathered from multiple transactional systems for operational reporting.
Predictive HR analytics and talent management: a conceptual framework
Published in Journal of Management Analytics, 2021
R. Navodya Gurusinghe, Bhadra J. H. Arachchige, Dushar Dayarathna
One of the leading thinkers in HR analytics, Josh Bersin (2016) has introduced the HR analytics maturity model to explain four different levels of the adoption of HR analytics. These four maturity levels are operational reporting, advanced reporting, advanced analytics, and predictive analytics. According to him, in 2016, many organisations (56%) are at the level of operational reporting. At this stage, organisations mostly focus on operational reporting such as metrics on workforce headcount, employee turnover, absenteeism, cost of labour and the like. At this stage, even though the HR department reports these data reactively to the management meetings, these data cannot be used for decision making as data are from different separate systems. Data cannot be integrated. In other words, even though firms generate these types of metrics, nothing much can be done with these data. Further, regularly updating these data is time-consuming.