Shrinked Data Marts Enabled for Negative Caching

Most HEIs have piecemeal partially linked QMS (Quality Management System) or mechanisms to manage the data, statistics and documents heavy quality management of its academic aspirations disjointed from the planning dimension. The integrated eIQA structured in 9 e-modules are aimed at integrating the quality-information-planning trilogy into a paperless online real-time era of quality-information-planning management working in full tandem in conjunctions with each other holistically to support the key management and institution performance management and informed decision making. The linkages are establlished via the key reports, statistics, documents and action plans and projects required of quality management and accreditation across the QMS-PMS (Planning Management System) duo, as supported by a data warehouse and its applications data marts that interlinks the 9 e-modules in in eIQA.

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An MDA Approach and QVT Transformations for the Integrated Development of Goal-Oriented Data Warehouses and Data Marts

Innovations in Database Design, Web Applications, and Information Systems Management ◽

10.4018/978-1-4666-2044-5.ch003 ◽

2013 ◽

pp. 44-71

Author(s):

Jesús Pardillo ◽

Jose-Norberto Mazón ◽

Juan Trujillo

Keyword(s):

Data Warehousing ◽

Complete Solution ◽

Requirement Engineering ◽

User Requirements ◽

Data Warehouses ◽

Integrated Development ◽

Model Driven ◽

Organizational Challenges ◽

Uml Profiles ◽

Data Marts

To customize a data warehouse, many organizations develop concrete data marts focused on a particular department or business process. However, the integrated development of these data marts is an open problem for many organizations due to the technical and organizational challenges involved during the design of these repositories as a complete solution. In this article, the authors present a design approach that employs user requirements to build both corporate data warehouses and data marts in an integrated manner. The approach links information requirements to specific data marts elicited by using goal-oriented requirement engineering, which are automatically translated into the implementation of corresponding data repositories by means of model-driven engineering techniques. The authors provide two UML profiles that integrate the design of both data warehouses and data marts and a set of QVT transformations with which to automate this process. The advantage of this approach is that user requirements are captured from the early development stages of a data-warehousing project to automatically translate them into the entire data-warehousing platform, considering the different data marts. Finally, the authors provide screenshots of the CASE tools that support the approach, and a case study to show its benefits.

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Designing Data Marts from XML and Relational Data Sources

Data Warehousing Design and Advanced Engineering Applications ◽

10.4018/978-1-60566-756-0.ch004 ◽

2010 ◽

pp. 55-80 ◽

Cited By ~ 2

Author(s):

Yasser Hachaichi ◽

Jamel Feki ◽

Hanene Ben-Abdallah

Keyword(s):

Design Method ◽

Large Data ◽

Relational Data ◽

Data Types ◽

Economic Competition ◽

Data Mart ◽

Relational Data Model ◽

Xml Documents ◽

Data Marts ◽

Data Volume

Due to the international economic competition, enterprises are ever looking for efficient methods to build data marts/warehouses to analyze the large data volume in their decision making process. On the other hand, even though the relational data model is the most commonly used model, any data mart/ warehouse construction method must now deal with other data types and in particular XML documents which represent the dominant type of data exchanged between partners and retrieved from the Web. This chapter presents a data mart design method that starts from both a relational database source and XML documents compliant to a given DTD. Besides considering these two types of data structures, the originality of our method lies in its being decision maker centered, its automatic extraction of loadable data mart schemas and its genericity.

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Data Discovery Over Time Series From Star Schemas Based on Association, Correlation, and Causality

International Journal of Data Warehousing and Mining ◽

10.4018/ijdwm.2020100106 ◽

2020 ◽

Vol 16 (4) ◽

pp. 95-111

Author(s):

Wallace Anacleto Pinheiro ◽

Geraldo Xexéo ◽

Jano Moreira de Souza ◽

Ana Bárbara Sapienza Pinheiro

Keyword(s):

Time Series ◽

Data Discovery ◽

Neglected Disease ◽

Tegumentary Leishmaniasis ◽

Data Marts ◽

American Tegumentary Leishmaniasis ◽

Over Time

This work proposes a methodology applied to repositories modeled using star schemas, such as data marts, to discover relevant time series relations. This paper applies a set of measures related to association, correlation, and causality to create connections among data. In this context, the research proposes a new causality function based on peaks and values that relate coherently time series. To evaluate the approach, the authors use a set of experiments exploring time series about a particular neglected disease that affects several Brazilian cities called American Tegumentary Leishmaniasis and time series about the climate of some cities in Brazil. The authors populate data marts with these data, and the proposed methodology has generated a set of relations linking the notifications of this disease to the variation of temperature and pluviometry.

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Automatic Theme Extraction for Marine Data Marts Using Semantic Web

Journal of Convergence Information Technology ◽

10.4156/jcit.vol8.issue1.94 ◽

2013 ◽

Vol 8 (1) ◽

pp. 765-771

Author(s):

FengJing Shao ◽

ShunYao Wu ◽

JinLong Wang ◽

ChunYuan Tian

Keyword(s):

Semantic Web ◽

Data Marts ◽

Marine Data

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