In this paper, an optimal aggregation and counter-aggregation (drill-down) methodology is proposed on multidimensional data cube. The main idea is to aggregate on smaller cuboids after partitioning those depending on the cardinality of the individual dimensions. Based on the operations to make these partitions, a Galois Connection is identified for formal analysis that allow to guarantee the soundness of optimizations of storage space and time complexity for the abstraction and concretization functions defined on the lattice structure. Our contribution can be seen as an application to OLAP operations on multidimensional data model in the Abstract Interpretation framework. © 2009 IEEE.

SOUMYA SEN

GENERAL

NABENDU CHAKI

Computer Science and Engineering

A CORTESI

University of Calcutta (informally known as Calcutta University or CU) is a collegiate public state university located in Kolkata, West Bengal, India.&nbsp;Within India it is recognized as a &quot;Five-Star University&quot; and accredited &quot;A&quot; Grade by National Assessment and Accreditation Council.

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The University of Calcutta has secured the Fifth position among the Universities of India in the prestigious &quot;Indian University Ranking 2019&quot; list, released by the NIRF of the Ministry of Human Resource Development, Government of India.

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It was established on 24 January 1857, and was one of the first institutions in Asia to be established as a multidisciplinary and Western-style university. Its alumni and faculty include several heads of state, heads of government, social reformers, prominent artists, only academy award winner and Dirac medal winner in India, many Fellows of the Royal Society and five Nobel laureates as of 2019 which is highest in South Asia.

University Of Calcutta

Optimal Space and Time Complexity Analysis on the Lattice of Cuboids Using Galois Connections for Data Warehousing

ICCIT 2009 - 4th International Conference on Computer Sciences and Convergence Information Technology

Disbursement of loan is an important decision-making process for the corporate like banks and NBFC (Non-banking Finance Corporation) those offers loans. The business involves several parameters and the data which are associated to these parameters are generated from heterogeneous data sources and also belong to different business verticals. Henceforth the decision-making on loan scenarios are critical and the outcome involve solving the issues like whether to grant the loan or not, if sanctioned what is highest amount, etc. In this paper we consider the traditional parameters of loan sanction process along with these we identify one special case of Indian credit lending scenario where the people having old loans with good repayment history get priority. This limits the business opportunities for Bank/NBFC or other loan disbursement organizations as potential good customers having no loan history are treated with less priority. In this research work we propose a data warehouse model which integrates the existing parameters of loan disbursement related decisions and also incorporates the newly identified concepts to give the priorities to the customers who don’t have any old credit history. © Springer Nature Singapore Pte Ltd. 2019.

Advances in Intelligent Systems and Computing

A data warehouse based schema design on decision-making in loan disbursement for Indian advance sector

Virtual Data warehouses (VDW) are generally used to store and analyze rapidly generated data and thereafter to make quick decision. VDW may stores data in a schema-less form and without any pre-processing to make the decision making on the fly. But for long term and effective business report generation, VDWs must be linked with physical data warehouse. In real life it is often found that a particular attribute is present in VDWs that is missing in actual data warehouse. In this type of situation the system needs to decide whether the attribute will be added in to physical data warehouse or not. Also in many time it is found that a particular attribute has a poor priority for data analysis, but it found very importance in VDWs. To handle all these, alone VDWs or client ends are not fit enough as they don't have all the information about the system. Hence a specially designated node is required for gathering all the information about the system and changing the structure of the data warehouse. © 2018 IEEE.

2018 7th International Conference on Reliability, Infocom Technologies and Optimization: Trends and Future Directions, ICRITO 2018

Business Intelligence Development by Analysing Customer Sentiment

This book presents Hyper-lattice, a new algebraic model for partially ordered sets, and an alternative to lattice. The authors analyze some of the shortcomings of conventional lattice structure and propose a novel algebraic structure in the form of Hyper-lattice to overcome problems with lattice. They establish how Hyper-lattice supports dynamic insertion of elements in a partial order set with a partial hierarchy between the set members. The authors present the characteristics and the different properties, showing how propositions and lemmas formalize Hyper-lattice as a new algebraic structure. © The Author(s) 2016. All rights reserved.

Hyper-Lattice Algebraic Model for Data Warehousing

Analytical processing on multi-dimensional data is performed over data warehouse. This, in general, is presented in the form of cuboids. The central theme of the data warehouse is represented in the form of fact table. A fact table is built from the related dimension tables. The cuboid that corresponds to the fact table is called base cuboid. All possible combination of the cuboids could be generated from base cuboid using successive roll-up operations and this corresponds to a lattice structure. Some of the dimensions may have a concept hierarchy in terms of multiple granularities of data. This means a dimension is represented in more than one abstract form. Typically, neither all the cuboids nor all the concept hierarchy are required for a specific business processing. These cuboids are resided in different layers of memory hierarchy like cache memory, primary memory, secondary memory, etc. This research work dynamically finds the most cost effective path from the lattice structure of cuboids based on concept hierarchy to minimize the query access time. The knowledge of location of cuboids at different memory elements is used for the purpose. © 2014 Elsevier B.V.

Journal of Computational Science

Dynamic discovery of query path on the lattice of cuboids using hierarchical data granularity and storage hierarchy

This paper propose a new methodology for efficient implementation of OLAP operations using concept hierarchies of attributes in a data warehouse. The different granularity associated with a particular dimension and the hierarchy amongst those may be represented as a lattice. The focus is to move up (roll-up) and down (drill-down) within the lattice structure using an algorithm with optimal time complexity. In this paper, a new algorithm has been proposed using a dynamic data structure that reduces over time resulting in better space utilization and also reduction of computation time. A Galois Connection is identified on this lattice structure with well-defined abstraction and concretization functions based on the concept hierarchy. The contribution offers formalism in analysis using concept hierarchy in an abstract interpretation framework. © 2011 IEEE.

Journal	ICCIT 2009 - 4th International Conference on Computer Sciences and Convergence Information Technology
Publisher	-
Open Access	No