Proceedings ArticleDOI
An Architecture to Maintain Materialized View in Cloud Computing Environment for OLAP Processing
Soumya Sen,Debabrata Datta,Nabendu Chaki +2 more
- pp 360-365
Reads0
Chats0
TLDR
This paper emphasizes on integrating heterogeneous data sources to create virtual data warehouses that could be deployed in a cloud environment to handle multiple OLAP data sources.Abstract:
Cloud Computing is an emerging technology that empowers the present day business scenario by providing services on demand instead of an integrated product. Many of applications on cloud deals with huge amount of data and these are often used for analytical processing to exploit the business intelligence. However working with very large scale of data is often time consuming and requires higher processing time. Materialized views are built and maintained to pre-fetch an effective subset of the entire database for current and immediate future usage. The materialized views are constructed on data warehouse, data marts and virtual data warehouse. In a cloud computing scenario, quite often the materialized views for the distributed data centers resides in different data servers. One of the major challenges is to handle multiple OLAP data sources. The data needs to be, integrated and analyzed continually in an efficient manner before the views are built. This paper emphasizes on integrating heterogeneous data sources to create virtual data warehouses that could be deployed in a cloud environment.read more
Citations
More filters
Journal ArticleDOI
Design science research contribution to business intelligence in the cloud - A systematic literature review
TL;DR: This paper focuses on the deployment of BI in the cloud, from the vantage point of design science research (DSR), and proposes a framework composed of two dimensions: artifact type and BI step, which facilitates the understanding of different research streams.
A dynamic materialized view Selection in a Cloud-based Data Warehouse
Yang Kehua,Abdoullahi Diasse +1 more
TL;DR: This paper proposes a materialized view selection algorithm based on monetary which take in consideration the computation cost, storage cost and transfer cost and can perform in a dynamic manner to select the best set of materialized views.
Book ChapterDOI
Integrating Heterogeneous Data for Big Data Analysis
TL;DR: Because data virtualization requires techniques to integrate data, the authors look at the problems of divergent data in terms of value, syntax, semantic, and structural differences to enable the mapping of this Divergent data into a homogeneous global schema that can more easily be used for big data analysis.
Posted Content
A Framework for Developing Real-Time OLAP algorithm using Multi-core processing and GPU: Heterogeneous Computing
TL;DR: In this paper, the authors propose a framework illustrating the barriers and suggested solutions in the way of achieving real-time OLAP answers that are significantly used in decision support systems and data warehouses.
Proceedings ArticleDOI
Distributed data recovery architecture based on schema segregation
TL;DR: This paper proposes a decentralized disaster recovery structure instead of a single centralized DR, i.e. the databases are hosted on multiple servers, where each of these servers is catering to one or more related schema.
References
More filters
Book
Data Mining: Concepts and Techniques
TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.
Proceedings ArticleDOI
Implementing data cubes efficiently
TL;DR: In this article, a lattice framework is used to express dependencies among views and greedy algorithms are presented to determine a good set of views to materialize, with a small constant factor of optimal.
Proceedings ArticleDOI
Constant-Time Query Processing
Vijayshankar Raman,Garret Swart,Lin Qiao,Frederick Ralph Reiss,Vijay Dialani,Donald Kossmann,Inderpal S. Narang,Richard S. Sidle +7 more
TL;DR: Blink is presented, the first attempt at this goal, that runs every query as a table scan over a fully denormalized database, with hash group-by done along the way, and a scheme for evaluating a conjunction of range and equality predicates in SIMD fashion over compressed tuples.
Posted Content
Clustering-Based Materialized View Selection in Data Warehouses
TL;DR: In this paper, a framework for materialized view selection that exploits a data mining technique (clustering), in order to determine clusters of similar queries is proposed. But it is based on cost models that evaluate the cost of accessing data using views and the costs of storing these views.
Proceedings ArticleDOI
ETL queues for active data warehousing
TL;DR: This paper proposes a framework for the implementation of active data warehousing, with the following goals: minimal changes in the software configuration of the source, minimal overhead for the source due to the active nature of data propagation, and the possibility of smoothly regulating the overallconfiguration of the environment in a principled way.
Related Papers (5)
A cloud-based framework for supporting effective and efficient OLAP in big data environments
Alfredo Cuzzocrea,Rim Moussa +1 more
Mobile query optimization based on agent-technology for distributed data warehouse and OLAP applications
A. Hameurlain,F. Morvan +1 more