Factors in the Design and Development of a Data Warehouse for Academic Data.

Data warehousing is a relatively new field in the realm of information technology, and current research centers primarily around data warehousing in business environments. As new as the field is in these environments, only recently have educational institutions begun to embark on data warehousing projects, and little research has been done regarding the special considerations and characteristics of academic data, and the complexity of analyzing such data. Educational institutions measure success very differently from business-oriented organizations, and the analyses that are meaningful in such environments pose very unique and intricate problems in data warehousing. This research describes the process of developing a data warehouse for a community college, focusing on issues specific to academic data

New directions for warehousing data management research: Extensions to an existing review: Special session on 'Emerging technologies in logistics'

Existing research has conducted reviews of warehousing research and has suggested potential important areas for future work. In this paper we focus on warehousing data management-related issues and augment the findings from a recent review of warehousing research to suggest new areas of future work. To determine these potential areas we visited a large, national warehousing organisation and observed their warehouses, operations, and information systems. We compared our findings against the recommendations from an academic review, and identified five new areas of important future research.This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/INDIN.2015.728180

Data Management and Mining in Astrophysical Databases

We analyse the issues involved in the management and mining of astrophysical data. The traditional approach to data management in the astrophysical field is not able to keep up with the increasing size of the data gathered by modern detectors. An essential role in the astrophysical research will be assumed by automatic tools for information extraction from large datasets, i.e. data mining techniques, such as clustering and classification algorithms. This asks for an approach to data management based on data warehousing, emphasizing the efficiency and simplicity of data access; efficiency is obtained using multidimensional access methods and simplicity is achieved by properly handling metadata. Clustering and classification techniques, on large datasets, pose additional requirements: computational and memory scalability with respect to the data size, interpretability and objectivity of clustering or classification results. In this study we address some possible solutions.Comment: 10 pages, Late

Big Data Harmonization – Challenges and Applications

As data grow, need for big data solution gets increased day by day. Concept of data harmonization exist since two decades. As data is to be collected from various heterogeneous sources and techniques of data harmonization allow them to be in a single format at same place it is also called data warehouse. Lot of advancement occurred to analyses historical data by using data warehousing. Innovations uncover the challenges and problems faced by data warehousing every now and then. When the volume and variety of data gets increased exponentially, existing tools might not support the OLAP operations by traditional warehouse approach. In this paper we tried to focus on the research being done in the field of big data warehouse category wise. Research issues and proposed approaches on various kind of dataset is shown. Challenges and advantages of using data warehouse before data mining task are also explained in detail

A Survey of Data Warehousing Success Issues

Data warehousing is an important area of practice and research, yet few studies have assessed its practices in general and critical success factors in particular. Although many guidelines for implementation exist, most are derived from anecdotal evidence. A survey of data warehousing professionals was conducted to gain insight into data warehousing success issues. The results reveal that data warehousing success is a multi-faceted construct and that improved productivity is the most valued measure for success. The results also put clearly defined business needs/benefits and source data quality at the top of the list of critical success factors. In addition, different success factors were found to be significant for different success measures

Proximity-graph-based tools for DNA clustering

There are more than one billion documents on the Web, with the count continually rising at a pace of over one million new documents per day. As information increases, the motivation and interest in data warehousing and mining research and practice remains high in organizational interest. The Encyclopedia of Data Warehousing and Mining, Second Edition, offers thorough exposure to the issues of importance in the rapidly changing field of data warehousing and mining. This essential reference source informs decision makers, problem solvers, and data mining specialists in business, academia, government, and other settings with over 300 entries on theories, methodologies, functionalities, and applications

The Survey On: Data Mining Data Warehousing & OLAP

This paper gives a review of the Data mining handle. After the investigation of the way of data mining and its significance in information warehousing is included. It depicts the CRISP-DM standard now being utilized as a part of industry as the standard for an innovation impartial data mining prepare display. The paper finishes up with a noteworthy delineation of the data mining handle system and the unsolved issues that offer open doors for research. The approach is both reasonable and theoretically stable to be valuable to both scholastics and experts

An investigation into practices, issues and improvement opportunities of logistical outsourcing : a study of integrated warehouse services : a thesis presented in partial fulfilment of the requirements for the degree of Master of Applied Science in Logistics and Supply Chain Management at Massey University

Some Bahasa Indonesian LanguageA pressure to maintain company's profitability and at the same time a need for the company to increase service level and productivity, has forced the organisation to re-engineer its business systems into a more efficient and effective process. Outsourcing has introduced a new concept to re-engineering the company's business system by transferring the company's non-core business to the experts. Outsourcing can be a tool to achieve the competitive advantage. Even though, unsuccessful outsourcing implementation due to poor planning of outsourcing strategy might result in many problems for the company. The reality is outsourcing is expected to be further developed in the future. Thus, there is plenty of room for logistical outsourcing growth. Nonetheless, the barriers of logistical outsourcing growth, such as poor outsourcing planning strategy causes the lack of understanding of outsourcing and lack of proper logistical infrastructure. These barriers result in the need to review the issues applicable in the practices of logistical outsourcing. This research, therefore, investigates practices, issues and improvement opportunities of logistical outsourcing with regards to the practices of Integrated Warehouse Services. The use of multi-strategy research by combining the qualitative and quantitative research leads to the achievement of the research objective. This research found that reasons to outsource, the selection of outsourced activities and outsourcing provider selection process were the most important factors in outsourcing decision making process. The practices of IWS has been identified to gain success in improving customer service, reducing product cost, improve productivity, improving information sharing, reducing response time and improving space utilisation. The outcomes of this research illustrates that there is a tendency to perceive provider selection process and criteria and also the logistical outsourcing agreements and relationships as the logistical outsourcing issues to have the most concern in the practices of Integrated Warehouse Services. This research also found that the company needs to have improvements in the outsourcing agreements and relationships, employees training of outsourcing concept and the selection process of outsourcing provider

Cancer Surveillance using Data Warehousing, Data Mining, and Decision Support Systems

This article discusses how data warehousing, data mining, and decision support systems can reduce the national cancer burden or the oral complications of cancer therapies, especially as related to oral and pharyngeal cancers. An information system is presented that will deliver the necessary information technology to clinical, administrative, and policy researchers and analysts in an effective and efficient manner. The system will deliver the technology and knowledge that users need to readily: (1) organize relevant claims data, (2) detect cancer patterns in general and special populations, (3) formulate models that explain the patterns, and (4) evaluate the efficacy of specified treatments and interventions with the formulations. Such a system can be developed through a proven adaptive design strategy, and the implemented system can be tested on State of Maryland Medicaid data (which includes women, minorities, and children)