The Use of Olap Reporting Technology to Improve Patient Care Services Decision Making Within the University Health Center

The purpose of this paper is to demonstrate that it is feasible for the student health center to leverage existing clinical data in a data warehouse by using OLAP reporting in order to improve patient care and health care services decision making. Historically, University health care centers have relied mainly on operational data sources for critical health care decision making. These sources of data do not contain enough information to allow health officials to recognize trends or predict how future changes in health care services might vastly improve overall heath care. Four proof of concept artifacts are constructed through design science research methodology, and a feasibility study is presented to build the case for the adoption of OLAP reporting technology. The study concludes that it is feasible to implement an OLAP reporting infrastructure at the student health center if physicians, clinical staff, and administration clearly define the need for the new technology, develop proper data extraction, loading, and transformation strategy, and adequately provide project management and data warehouse design towards the implementation of the solution

Property Management Analytics (OLAP) System

In information technology, on-line analytical processing (OLAP) is an approach or technique to analyze the raw data in multi-dimensional analytical perspectives to provide summaries. OLAP consists of basic analytical operations such as consolidation (roll-up), drill-down, and slicing and dicing. This involves aggregation of data that can be accumulated and computed in one or more dimensions based on the data hierarchy. Typical applications of OLAP include key performance indicators i.e., does the current value satisfy the goal, business reporting for sales, marketing, management reporting, business process management (BPM), budgeting & forecasting, financial reporting. OLAP functionality depicts the multi-dimensional analysis of consolidated enterprise data supporting end user analytical and navigational activities including: calculations and modeling applied across dimensions, hierarchies, trend analysis over sequential time periods, and drill-down to deeper levels of consolidation. OLAP encompasses: Relational database Report writing Data mining Databases configured for OLAP uses a multi-dimensional data model, allowing for complex analytical and ad-hoc queries with a rapid execution time. They borrow aspects of navigational databases, hierarchical databases, and relational databases that allow business users to slice and dice data at will. Property Management Analytics (OLAP) System is being developed for the in-house use for meeting business needs from time to time. This Property Management Analytics (OLAP) System will extensively be used by managers and service providers, which will help in making certain business decisions. It was developed for this audience to be able to provide better service. A key feature of this Property Management Analytics (OLAP) System is embedding business portability centralized to one system

Analytical study and computational modeling of statistical methods for data mining

Today, there is tremendous increase of the information available on electronic form. Day by day it is increasing massively. There are enough opportunities for research to retrieve knowledge from the data available in this information. Data mining and app

Analyzing and Developing Technique for Mining Very Large Databases to Support Knowledge Exploration

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Treatment of imprecision in data repositories with the aid of KNOLAP

Traditional data repositories introduced for the needs of business processing, typically focus on the storage and querying of crisp domains of data. As a result, current commercial data repositories have no facilities for either storing or querying imprecise/ approximate data. No significant attempt has been made for a generic and applicationindependent representation of value imprecision mainly as a property of axes of analysis and also as part of dynamic environment, where potential users may wish to define their “own” axes of analysis for querying either precise or imprecise facts. In such cases, measured values and facts are characterised by descriptive values drawn from a number of dimensions, whereas values of a dimension are organised as hierarchical levels. A solution named H-IFS is presented that allows the representation of flexible hierarchies as part of the dimension structures. An extended multidimensional model named IF-Cube is put forward, which allows the representation of imprecision in facts and dimensions and answering of queries based on imprecise hierarchical preferences. Based on the H-IFS and IF-Cube concepts, a post relational OLAP environment is delivered, the implementation of which is DBMS independent and its performance solely dependent on the underlying DBMS engine

Proceedings TLAD 2012:10th International Workshop on the Teaching, Learning and Assessment of Databases

This is the tenth in the series of highly successful international workshops on the Teaching, Learning and Assessment of Databases (TLAD 2012). TLAD 2012 is held on the 9th July at the University of Hertfordshire and hopes to be just as successful as its predecessors. The teaching of databases is central to all Computing Science, Software Engineering, Information Systems and Information Technology courses, and this year, the workshop aims to continue the tradition of bringing together both database teachers and researchers, in order to share good learning, teaching and assessment practice and experience, and further the growing community amongst database academics. As well as attracting academics and teachers from the UK community, the workshop has also been successful in attracting academics from the wider international community, through serving on the programme committee, and attending and presenting papers. Due to the healthy number of high quality submissions this year, the workshop will present eight peer reviewed papers. Of these, six will be presented as full papers and two as short papers. These papers cover a number of themes, including: the teaching of data mining and data warehousing, SQL and NoSQL, databases at school, and database curricula themselves. The final paper will give a timely ten-year review of TLAD workshops, and it is expected that these papers will lead to a stimulating closing discussion, which will continue beyond the workshop. We also look forward to a keynote presentation by Karen Fraser, who has contributed to many TLAD workshops as the HEA organizer. Titled “An Effective Higher Education Academy”, the keynote will discuss the Academy’s plans for the future and outline how participants can get involved

Proceedings TLAD 2012:10th International Workshop on the Teaching, Learning and Assessment of Databases

This is the tenth in the series of highly successful international workshops on the Teaching, Learning and Assessment of Databases (TLAD 2012). TLAD 2012 is held on the 9th July at the University of Hertfordshire and hopes to be just as successful as its predecessors. The teaching of databases is central to all Computing Science, Software Engineering, Information Systems and Information Technology courses, and this year, the workshop aims to continue the tradition of bringing together both database teachers and researchers, in order to share good learning, teaching and assessment practice and experience, and further the growing community amongst database academics. As well as attracting academics and teachers from the UK community, the workshop has also been successful in attracting academics from the wider international community, through serving on the programme committee, and attending and presenting papers. Due to the healthy number of high quality submissions this year, the workshop will present eight peer reviewed papers. Of these, six will be presented as full papers and two as short papers. These papers cover a number of themes, including: the teaching of data mining and data warehousing, SQL and NoSQL, databases at school, and database curricula themselves. The final paper will give a timely ten-year review of TLAD workshops, and it is expected that these papers will lead to a stimulating closing discussion, which will continue beyond the workshop. We also look forward to a keynote presentation by Karen Fraser, who has contributed to many TLAD workshops as the HEA organizer. Titled “An Effective Higher Education Academy”, the keynote will discuss the Academy’s plans for the future and outline how participants can get involved