Topic
Data mart
About: Data mart is a research topic. Over the lifetime, 559 publications have been published within this topic receiving 8550 citations.
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TL;DR: An extension of the traditional multidimensional model by taking into account the explicit representation of the semantics for measure formulas is proposed, and a novel query reformulation approach for a scenario of federated data warehouses is proposed.
7 citations
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06 Jan 2010
TL;DR: In this paper, the authors proposed a method for accurately building a customer portrait of a mobile communication data service, which comprises the following steps of: selecting a subservice view from a data mart according to the demand of mobile data service; selecting a key field from the sub-service view, and carrying out customer grouping based on statistics; building a unified view of all the customers in the data mart; adopting various classification algorithms to build a plurality of classification models based on the unified view.
Abstract: The invention relates to a method for accurately building a customer portrait of a mobile communication data service, which comprises the following steps of: selecting a subservice view from a data mart according to the demand of a mobile data service; selecting a key field from the subservice view, and carrying out customer grouping based on statistics; building a unified view of all the customers in the data mart; adopting various classification algorithms to build a plurality of classification models based on the unified view of the customers; and evaluating the plurality of classification models, selecting the optimal classification model from the classification models, and releasing the optimal classification model Compared with the prior art, the method can realize the accurate portrait of the customer under a specific data service and realizes comprehensive and accurate description to the customer
7 citations
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TL;DR: The crucial tip of the proposed work is integrated on delivering an enhanced and an exclusive innovative model based on the intention of enhancing security measures, which at times have been found wanting and also ensuring improved accessibility using Hashing modus operandi.
Abstract: Data warehouse is a set of integrated databases deliberated to expand decision-making and problem solving, espousing exceedingly condensed data. Data warehouse happens to be progressively more accepted theme for contemporary researchers with respect to contemporary inclination towards industry and executive purview. The crucial tip of the proposed work is integrated on delivering an enhanced and an exclusive innovative model based on the intention of enhancing security measures, which at times have been found wanting and also ensuring improved accessibility using Hashing modus operandi. An unsullied algorithm was engendered using the concept of protein synthesis, prevalently studied in Genetics, that is, in the field of Biotechnology, wherein three steps are observed, namely; DNA Replication, Translation and Transcription. In the proposed algorithm, the two latter steps, that is, Translation and Transcription have been taken into account and the concept have been used for competent encryption and proficient decryption of data. Central Dogma Model is the name of the explicit model that accounts for and elucidates the course of action for Protein Synthesis using the Codons which compose the RNA and the DNA and are implicated in numerous bio–chemical processes in living organisms. It could be observed that subsequently a dual stratum of encryption and decryption mechanism has been employed for optimal security. The formulation of the immaculate Hashing modus operandi ensure that there would be considerable diminution of access time, keeping in mind the apt retrieval of all indispensable data from the data vaults.
The pertinent appliance of the proposed model with enhanced security might be in its significant service in a variety of organizations where accrual of protected data is of extreme magnitude. The variety of organizations might include educational organizations, corporate houses, medical establishments, private establishments and so on and so forth.
7 citations
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01 May 20206 citations
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01 Jan 2000
TL;DR: Metadata is the foundation for success of Data warehouse and is the Information Directory containing Yellow Pages, Road Map and ‘Places of Interest’ for navigating the warehouse.
Abstract: Metadata is the foundation for success of Data warehouse. Metadata is central piece of the whole Data Warehousing Concepts. Metadata allows the end user to be pro-active in the use of the warehouse. It is the Information Directory containing Yellow Pages, Road Map and ‘Places of Interest’ for navigating the warehouse.
6 citations