DISCUSS CRITICALLY THE MAJOR DEVELOPMENTS IN DATABASE TECHNOLOGY AND RESEARCH. 2

DISCUSS CRITICALLY THE MAJOR DEVELOPMENTS IN DATABASE TECHNOLOGY AND RESEARCH. 2. DISCUSS CRITICALLY THE USE OF DATA WITHIN ORGANISATIONS, WITH RESPECT TO DATA MINING, DATA WAREHOUSING, QUALITY OF DATA ETC.

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Posting Time: - 7/17/2015 12:59:48 AM
Subject: - Computer Science

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Answer by:- Eddy

INTRODUCTION

Ability of database is increasing on daily basis. So requirement to store large amount of information is required for long time so that information will be easy to access and control and now database as changed to a large extent & there is a big change as database nowadays is supporting several high performance factors like analytics, data mining & reporting. This high level performance has resulted in creation of several new type of database like data warehousing that has tools like data mart, data mining and OLAP. These are considered to be best solution for Regional Health Authority (RHA) and they can help in solving problems that are related to study of healthcare performance, patient satisfaction, data quality and making researches. So various health care institutes are making use of data warehouse that makes information available at right time and in correct format. Health care management must implement strategy of data warehouse & data mining in RHA. Data of healthcare can be divided into 4 categories patient centric data, transformation based data, aggregate data and comparative data. Patient centric data stores information about patient whereas aggregate data stores information about resources, transformed based data stores information about plans and management data and comparative data stores information about research and outcomes. Sometimes, regional health authority have problems to utilize data that is gathered from online processing & is not integrated for decision making, management & processes of clinical care. Information that is collected must be accessible on proper time in effective form that provides opportunity to regional health organization that must provide effective decision & health plans to Local health authority. Additionally, health care organizations must acknowledge the role that is played by management in healthcare field so most of healthcare organization must use data warehouse as it gives fexilibility to decision making, accessibility of data & patient satisfaction. Data warehouse is a platform that gathers data from various organizations at one place & then centralized it and then normalized it to complete report with precise analysis and decision support. Decision support strategy can meet demand of all facilities in healthcare organizations. Main problem is the data that is collected over several years. Way out is creation of Executive information system that comprises of data mart & user interface to carry out data mining. Data mart is an element of data warehouse. Data mart is OLAP that enables user to access information when query is made about large amount of data. OLAP cube is another total that makes use of OLAP technology. (Suryakant B. Patil (2011)).

RHA will convert data into information by making use of data mart and data warehouse strategies. It will transform information further into knowledge & intelligence. Other significant advantage for RHA is management of time. For instance, if RHA gathers information on time basis at point of need from several LHA (Local Health Authority) about patient & make it available for doctors that it will allow to solve problems & make decisions. Nowadays, most of Database Management Software’s supports supporting data warehouse. Most of the Local Health authority (LHA) make use of different DBMS so it collect data, RHA can use different DBMS at same time that can result in powerfulness & cost effectiveness so RHA does not need to choose any specific data warehouse such that they can utilize existing DBMS. To solve issues RHA make use of powerful features of divers DBMS in proper manner. Steps to implement RHA are that RHA first should identify goals so as to include all needs & finalize requirement of software and hardware. Next step is to identify source system & resource that also includes team selection that will maintain & implement data warehouse. It team will with team of health information management, administration, clinical department & administration to identify data & pass it to data warehouse. Next step is to edit & clean data to pass it to data warehouse. Next step is to roll out & data marts for identification of service line so data mart creates Executive information system (EIS) that enables answer to question of administrators. Last step is to implement education program that allow user to make best use of data warehouse application. (Srikantha Rao(2011)).

Data warehouse has supporting tool like data mining that makes data warehouse powerful. Data mining can also be called as data exploration, information & knowledge that are a process to analyze data from several resources & summarize it to useful information. This information can be used by researchers to make research, enhance satisfaction patient & cuts cost. Additionally, data mining enables RHA to find out hidden patterns without predetermined idea about the pattern. In RHA, data mining is important as organization contains a large amount of data that is converted into information & knowledge that can support control cost, enhance profit & maintain high value of patient care. By making use of data mining, RHA may research data & find out hidden pattern whereas OLAP find out what to do with its result. Other advantage is research making prospect. For instance, processing system of medical information & tele medicine is efficient & user friendly. Such type of system has dual purpose. They can assist professional in case of medical research and it can be use for source of information for patients. Telemedicine has number of problems like document retrieval, mining of database & visualization of high dimension data. Such type of data mining can be used by patients to search similar disease and other information. (R. Kelly (2012-05-01))

DATA WAREHOUSING

It is an architected, coordinated & cyclic copying of data from a number of sources, both inside & outside of an enterprise, into a situation that is optimized for analytical & informational processing.( Rainer (2012-05-01))

Step to put into action a data warehouse for (RHA) Regional Health Authority

If RHA management granted with decision support plan that includes creation of data warehouse step, some of the steps must be followed to implement data warehouse. First step is to identify business goals of RHA (Regional Health Authority). There is a need to improve satisfaction of patient, so there is a need to create database that contains patient information & facilitate information sharing between health authorities to perk up decision making of doctors & nurses and medical researchers also. Other step is identification of source system that is used to gather data that must be identified together with resources. So there must be a team to implement data warehouse. A decisions support team is designed for clinical data. This team should work with information system that includes clinical department members, health information management & administration. Team work with owners of source system to identify data that needs to put in data warehouse. Last step is to put data into data warehouse that should be edited & clean. A timeline must be defined to download data from source. Data mart should be building & rolled out to identify service line. And then finally train user to make use of data warehouse. Dimensional approaches can involve normalizing data to a degree (Andrea (2010)).

Application of Data warehousing in Regional Health Authority

RHA is accountable for all local health authorities (LHA). If hospitals & health authorities carry out in a different way and there is a way to resolve this issue by executing one central database that contain all data related to hospital like information about doctor, information about patient, information about nurse & types of treatment for some specified disease. By making use of data warehouse & analyze information by means of data mining tools, RHA may discover suitable treatment for disease that is succeed in several hospitals. By implementing Data warehousing all hospitals share same centralized database where doctors & nurses have access to information of patient and treatment given to them. The access & use of information helps in improvement in decision making of doctors & nurses to treat diseases (Roberto (2010)).

If there will be a sole data warehouse for all health authorities, RHA will have control over it & able to oblige some policies & standard to health authority so that all hospitals follow similar policies. Once health authorities & hospitals begin following same policies & treating patient on basis of same policies, and then patient will be pleased. Data warehouse play a main role if all hospitals fabricate & share similar data warehouse. Data warehouse enclose copy of data & information from a variety database sources. Database of every health authority includes a enormous amount of data correlated to patient that will be copied to data warehouse that is easy to get to by all hospitals. After constructing data warehouse for RHA, data warehouse encompasses patient data that can be shared with other authorities. Information about a patient can be getting by doctor and nurse instantly. It will provide instant feedback on condition of patient, plan of care & current medication. By making use of this information, doctors & researchers may make use of OLAP tools to examine patient information for research purposes & find out new treatments.( Mark (2007) )

OLAP tools are a type of software tools that give study of data that is stored in a database. These tools facilitate users to examine diverse dimensions of multidimensional data. If data warehouse is executed properly it can be a stage that encloses patient information in centralized & normalized form for use to doctors, nurses & other staff to allow them to carry out simple reporting, benchmarking and complicated analysis (Andrea (2010)).

Disadvantage to implement data warehouse is that data that come from numerous sources must be cleaned. This process can be time consuming. In case of RHAuthority it will acquire a long time to nurses and doctors to get access to information of patient. Information that is needed will not be accessible in time. People who work with data warehouse of RHA must be trained properly before using it. There may be some compatibility issues. For instance, new system of database should not work with existing one. If data warehouse is accessible by means of internet then it may result in some privacy issues so patient information will be accessible through malicious person. It is quite costly to maintain data warehouse. RHA may spend a large amount of money to maintain data warehouse. (Dietterich, 2000)

DATA MINING

It is a combination of methods like decision trees, neural networks and some usual statistical techniques like extraction of information from data that let decision makers to make use of it in area like forecasting, estimation, decision support & prediction. (Bret (2006)).

Application of Data mining in Regional Health Authority

RHA can make use of data mining techniques to discover hidden & unpredicted patterns in data for planned decision-making. By making use of information, doctors & researchers can make use of some OLAP tools to evaluate patient information for research purposes & find out new-fangled treatments. If all hospitals & health authorities carry out in a different way, RHA may propose setting up similar policies on hospitals, after each treatment doctors can build a report of treatment that will be stored to data warehouse. In future if doctors face some complexity then they can consult those reports to treat disease. There is loads of knowledge to be gathered from automated health records. Doctors of Health Authority can make use of data mining technology to inspect amount of information that is related to patient & make a good decision to treat disease. When data mining is applied on existing data, then new & useful knowledge that have remained in the databases. After implementation of data warehouse then management of hospital may make use of data mining technology to access & examine information that was applied by single hospital & do well so as to put into practice it to other hospitals. By applying data mining RHA will be able to formulate decision on how hospitals & health authorities should work.( Monk (2006))

Advantages and disadvantages of data warehouse and data mining

Advantages of data warehouse system:

a) Provides centralization of communal data resources.

b) It is enclosed in a well-managed situation.

c) It has regular & repeatable process that is defined for loading data from communal applications.

Advantages of Data mining:

Other significant advantage for RHA is management of time. For instance, if RHA gathers information on time basis at point of need from several LHA (Local Health Authority) about patient & make it available for doctors that it will allow to solve problems & make decisions. (Ellen(2006)).

Other advantage is research making prospect. For instance, processing system of medical information & tele-medicine is efficient & user friendly.

First disadvantage of data warehouse is time related as before storing information in data warehouse it needs to be loaded & extracted that takes a large amount of time. Other disadvantage is related to compatibility as there may be some new transactions that may not work with existing system. Additionally, other problem is that data warehouse is hard to uphold. For instance, if a number of organization implements data warehouse it should be forever maintained that take additional money(Sim, 1989).

Disadvantages of data mining include security issue, privacy issue & inaccurate information. Privacy issue is that patient information will be accessible without consent of patient that will be infringement of patient right. In case of security issue, RHA will have personal information like social security number, account number & address that can be accessed by hacker because of inadequate security system. Other disadvantages are inaccurate information that may be misused & information that was acquired through data mining may be accustomed to take compensation of susceptible people or distinguish against certain people. Additionally, data mining technique is not 100% precise; this may have serious result. (Wagner (2006)).

CONCLUSION

These days Data warehouse & data mining turn out to be mostly used database technologies by healthcare organizations. RHA could gain remuneration of using data warehousing & data mining such as forming one central database for hospitals. It could aid hospitals to access data timely & fastly. Data warehouse & data mining should be used by Health Authorities for analyzing, decision making & improve access to information. But even then those technologies have a number of disadvantages like security, privacy, maintenance cost of data warehouse.( Dan (2003) )



REFERENCES:

Patil, Preeti S.; Srikantha Rao; Suryakant B. Patil (2011). "Optimization of Data Warehousing System: Simplification in Reporting and Analysis". IJCA Proceedings on International Conference and workshop on Emerging Trends in Technology (ICWET) (Foundation of Computer Science) 9 (6): 33–37.

Rainer, R. Kelly (2012-05-01). Introduction to Information Systems: Enabling and Transforming Business, 4th Edition (Kindle Edition). Wiley. pp. 127, 128, 130, 131, 133.

Battiti, Roberto; and Brunato, Mauro; Reactive Business Intelligence. From Data to Models to Insight, Reactive Search Srl, Italy, February 2011. ISBN 978-88-905795-0-9.



Battiti, Roberto; Passerini, Andrea (2010). "Brain-Computer Evolutionary Multi-Objective Optimization (BC-EMO): a genetic algorithm adapting to the decision maker". IEEE Transactions on Evolutionary Computation 14 (15): 671–687.doi:10.1109/TEVC.2010.2058118.



Braha, Dan; Elovici, Yuval; Last, Mark (2007) Theory of actionable data mining with application to semiconductor manufacturing control, International Journal of Production Research 45(13)



Fountain, Tony; Dietterich, Thomas; and Sudyka, Bill (2000); Mining IC Test Data to Optimize VLSI Testing, in Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, ACM Press, pp. 18–25



Monk, Ellen; Wagner, Bret (2006). Concepts in Enterprise Resource Planning, Second Edition. Boston, MA: Thomson Course Technology. ISBN 0-619-21663-8.OCLC 224465825.



Elovici, Yuval; Braha, Dan (2003) A Decision-Theoretic Approach to Data Mining, IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans 33(1)

Miller, Harvey J.; and Han, Jiawei (eds.) (2001);Geographic Data Mining and Knowledge Discovery, London, GB: Taylor & Francis



Ma, Y.; Richards, M.; Ghanem, M.; Guo, Y.; Hassard, J. (2008). "Air Pollution Monitoring and Mining Based on Sensor Grid in London". Sensors 8 (6): 3601.


 
   

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