Medical Card System Data Warehouse

aesculapian twit System entropy W beho aimMuhammad NadeemS.No ennobleP.No1Introduction (What project is near)3-42System Overview, entropy architecture and storage,5-63ER-Diagram, OLTP-Architecture,Master / hard unraveler aesculapian calling card System6-104MCS OLTP, MCS information, storage,MCS Business Module or values process11-145 put across Flow, Data repository, MySQL15-196Data w behousing19-277Service improvement288statistical Analysis29-309Summary, conclusion, Learned31-3510 addendum36IntroductionA Medical Card is a plastic card, about the span of a Visa, issued by the HSE. Individuals who hold a Medical Card are qualified for a scope of Health Services for nonhing out of pocket. Some epoch recently, 2009. healing(predicate) card framework was a decentralized and comprising littler wellbeing sheets. Since, they are isolated to each others, It was qualification taking after oddities.Duplicate Medical cards.GHOST Medical cardsSystem deficiency diverseness magnitud e ComplexityBudget deficit in health budgetLack of staffing and System expertiseTo lay these issues the HSE, choose to incorporated Medical card framework. They gather master from either wellbeing board and blood in Dublin. On framework level, it was a major perplexity mass before centralization. The reason was every wellbeing board has their own medicinal card framework on a few innovations deal prophet, SQL server and so forth. A Single Medical card framework was hunt downning on ORACLE, SQL, MYSQL and MUMS thence on rely on upon the decision of wellbeing board. there were loads of reports and Hauge paper works was include and it was night horse to handle it. To, de vergeine this issue The HSE made a agreement to gap selective reading into three selective informationbases, for example, ORACLE, MongoDB.Each of the selective informationbase has there on noteworthiness. The HSE additionally choose to making and dealing with their own information distri merelyion center. There was an alternative accessible for cloud bene take ons but since of the way of information. The HSE fabricate their own information product house. The HSE utilized Mongo DB since it is a record situated infobase and what it does, it is intended for even versatility. Because this, if your informationbase develops, you can fundamentally include more equipment or more assets from the cloud.2.1 MCS System OverviewThe Medical card placement information were divided into followingThe selective information from new medical card forms was divided in 3 parts. First entropy was Manual filled application which was later typed in the form.The data come from Legacy system and idiotic into new system. That sort of data pose a bun in the ovend big ETL.Third was supporting documents.The size of data was 2 tetra bytes per month2.2 MCS Data StorageThe data was storing in following technologiesMongoDBNeo4jORACLEMYSQLhybrid system (HyPer)MongoDBMySQL illusionistNeo4j Document-orientedCr oss- computer program supportReliable databaseOLTPSupports JSON format.Stored procedures forward-looking Index CompressionJSON and XLS formatNo DBASQL/PSMApproximate Count lucidIndexes by using Apache LucenceFlexible replication for shading across nodes.Triggers.Attribute Clusteringsupports full virulentMulti-version concurrencyCursorsAutomatic Big Table CachingUI for CQLconsistency in complex transactionsUpdatable viewsFDA Support for CDBsNative GPE(Graph bear on Engine).Dynamic queries and powerful aggregates.Online DDLFull Database Caching(CRUD) operationIndex support and ap/reduce functionsInformation synopsisIn-Memory appealAccess by Java, Spring, Scala3.1 MCS Database Architecture3.2 MCS OLTP Architecture Master / Slave Medical Card System matchless index per cityGrowth by shredding into 2 and 3Master build index every 10 minutesUse indexes and pearl code for to generate XMLBuild versioning and rollback segmentSlave pull the indexes via resync and reloadUse pre-forking co nfigHardware was dual proc, dual core AMD opterons with 32 GB lumber3.3 MCS OLTPMedical card OLTP systems are used for order new application, Medical card transactions, customer birth management (CRM) etc. Such systems sire many users who conduct short transactions. Database queries are usually simple, require sub-second response times and return relatively few records. An important attribute of medical card OLTP system is its ability to maintain concurrency. To avoid single points of failure, MCS OLTP systems is decentralized.MCS data- seat-self-governing and planned to professionally handle accidental, ad hoc queries in an analytical system environment. We are using Mango DB, Neo4j, Oracle, MySQL on with legacy System the likes of MUMS. The Size of the data per week is 1 tetra byte. We have Online replication. HSE have hot backup and full disaster recovery model apply. HSE have one(a) raw server stockpile in Waterford region which they used as cold backup. HSE policy to l ineage data in multi places so in case of disaster recovery bequeath be easy.3.4 MCS DataIt consists on the following lymph gland personnel and Medical History such as Client name, address, ppsno and GP informationGP registered within certain countyHospital information such as OPD, ANE etc.CWO in each areaPharmacies and registered PharmaciesHSE Local offices3.5 MCS Data storageMCS data store on different devices and system as followingQuantum StorNext scale-out file system.NetBackup product. NetBackup is integrated with copy data management, Veritas resilience Platform and Veritas Information Map.MySQLMangoDBNeo4jOracle4.1 MCS Business Module or Services processFOR NEW coatingFOR RENEWAL APPLICATION4.2 MCS Request Flow4.3 MCS Flow4.4 MCS Data Repositories4.5 MCS My SQL5.1 MCS Data Warehousing Relationships between DSS/BI, database, data managementDSS/BI transforming data into info to support decision makingMCS (Medical Card System) operational data and DSS/BI data differWhat a dat a MCS (Medical Card System) storage warehouse is, how data for it are prepared, and how it is implementedMultidimensional databaseDatabase technology for BI OLAP, OLTPExamples of applications in healthcare5.2 MCS BI Extraction of Knowledge from Data5.3 MCS DSS/BI Architecture Learning and Predicting5.4 MCS DSS/BIDSS/BI are technologies designed to extract information from data and to use such information as a basis for decision makingDecision support system (DSS)Arrangement of computerized tools used to assist managerial decision making within handicraftUsually requires enormous data massaging to produce informationUsed at all levels within organizationOften tailor to focus on specific business areasProvides ad hoc interrogatory tools to retrieve data and to display data in different formats5.5 MCS DSS/BI ComponentsData store componentBasically, a DSS databaseData extraction and data filtering componentUsed to extract and validate data taken from operational database and extern al data sourcesEnd-user query toolUsed to create queries that access databaseEnd-user presentation toolUsed to organize and present data5.6 MCS Main Components of A DSS/BI5.7 MCS DSS/BI Needs a different type of databaseA narrow down DBMS tailored to provide fast answers to complex queries.Database schemaMust support complex data representationsMust contain aggregated and summarized dataQueries must be able to extract multidimensional time slicesDatabase size DBMS must support very large databases (VLDBs), Wal-Mart data warehouses is measured in atomic number 82 (1,000 terabyte)Technology Data warehouse and OLAP punctuate speed, security, flexibility, reduce redundancy and abnormalities.5.8 MCS Operational vs DSS Data6.1 MCS Data storeThe Data store is an integrated, subject-oriented, time-variant, non-volatile database that provides support for decision making.Usually a read-only database optimized for data compend and query touch oncentralized, consolidated database sporadic ally updated, never removedRequires time, money, and considerable managerial effort to create6.2 MCS OLAP (Online Analytical Processing)Advanced data analysis environment that supports decision making, business modeling, and operations researchengine or platform for DSS or Data WarehouseOLAP systems share four main characteristicsUse multidimensional data analysis techniquesProvide advanced database supportProvide easy-to-use end-user larboardsSupport client/server architecture6.3 MCS OLAP vs OLTPOnline Transactional Processing (OLTP)emphasize speed, security, flexibility, reduce redundancy and abnormalities.Online Analytical Processing (OLAP)multi-dimensional data analysisadvanced database supporteasy-to-use user interfacesupport client/server architecture6.4 MCS Multidimensional Data AnalysisGoal analyze data from different dimensions and different levels of aggregation6.7 MCS Multidimensional Data Analysis TechniquesData are processed and viewed as part of a multidimensional str uctureParticularly attractive to business decision makersAugmented by following functionsAdvanced data presentation functionsAdvanced data aggregation, consolidation and classification functionsAdvanced computational functionsAdvanced data modeling functions6.8 MCS integration OLAP with Spreadsheet6.9 MCS easy-to-Use End-User InterfaceMany of interface features are borrowed from previous generations of data analysis tools that are already familiar to end usersMakes OLAP easily accepted and readily used6.10 MCS Client/Server ArchitectureProvides framework within which new systems can be designed, developed, and implementedEnables OLAP system to be divided into several components that define its architectureOLAP is designed to meet ease-of-use as well as system flexibility requirements6.11 MCS OLAP ArchitectureDesigned to use both operational and data warehouse data delimit as an advanced data analysis environment that supports decision making, business modeling, and an operations res earch activitiesIn most implementations, data warehouse and OLAP are interrelated and complementary environments6.12 MCS FactsNumeric measurements ( measure outs) that represent specific business aspect or activityNormally stored in fact table that is center of star schemaFact table contains facts that are linked through their dimensionsMetrics are facts computed or derived at run time6.13 MCS Dimensions simple star schema6.14 MCS Attribute Hierarchies in multidimensional analysis6.15 MCS Star abstract Representation6.17 MCS Multi-dimensional database6.18 MCS Star Schema6.19 Snowflake schema7.1 Service improvementMCS Outcome DatabaseCenter for Medical ServiceMore than fifty community health centers contributed to this database.547,719 transactions13 Outcome indicators, 72,541 episodes of treatment, 17,205 patients, 108 therapists, 48 founding8.1 Statistical AnalysisMCS Difference in Clinical Services Improvement Young and Old patients8.2 analyse Cancer Incidence of Dublin County to Carlow County from 1996-20009.1 ConclusionA Medical Card is a plastic card, about the size of a credit card, issued by the HSE. People who hold a Medical Card are entitled to a range of Health Services free of charge. In this project, we have seen a change of centralized medical card system with the help of NOSQL and RDBMS changed the service outcome. HSE have Mongo DB which make it equal for this kind of project is it is Schema-less. A document can have any number of key/value pairs. Instead of using a schema, documents of the same time (for example, documents representing blog posts) all have a sympathetic set of key/value pairs. Second, a database which HSE have here is Neo4j graph database. The reason why they have used Neo4j because it provides OLTP and supports Jason and XLS format. Another reason to use Neo4j is it is Create, Read, Update and Delete (CRUD) operations working on a graph data model.MCS data-model-self-governing and planned to professionally handle accident al, ad hoc queries in an analytical system environment. We are using Mango DB, Neo4j, Oracle, MySQL along with legacy System like MUMS. The Size of the data per week is 1 tetra byte. We have Online replication. HSE have hot backup and full disaster recovery model implemented. HSE have one cold server run in Waterford region which they used as cold backup. HSE policy to store data in multi places so in case of disaster recovery will be easy.The MCS Data Warehouse is an integrated, subject-oriented, time-variant, non-volatile database that provides support for decision making. Usually a read-only database optimized for data analysis and query processing. centralized, consolidated database, periodically updated, never removed. It is Requires time, money, and considerable managerial effort to create. Relationships between DSS/BI was studied in detail along with, database, data management. We have explored the DSS/BI transforming data into info to support decision making. The MCS (Medica l Card System) operational data and DSS/BI data differ from which we have used to test the system. We have explored what data MCS (Medical Card System) warehouse is, how data for it are prepared, and how it is implemented Multidimensional database. The Database technology for BI OLAP, OLTP. Examples of applications in healthcare.During this project, we were Combining Data Warehouse (OLAP) and GIS.OLAP handles large data, fast retrieval multidimensional, multilevel aggregation, analyses/data mining on huge complex databases. IS visual image and spatial analyses. Visualization and Analysis Charts and Maps + Statistical Analysis.The outcome we have from the MCS Database is we have center for Medical Service More than fifty community health centers contributed to this database. The transaction span to 547,719 transactions. WE have 13 Outcome indicators, 72,541 episodes of treatment, 17,205 patients, 108 therapists, 48 institutions.9.2 Learned During completing this project, I have lear ned followingNOSQL MongoDB, Neo4j Installation and deploymentOLTP in detailI have studied Data Warehouse comprehensivelyI have Learned about Data Analysis such as Statistical AnalysisNoSQL and SQL have both their significance depend on what you want to do.It was a great learning curve and extend my horizon about technologyThere is a lot to learn the especially field in IT things a rapidly changing.RDBMS are beneficial to work but they will not answer for all your IT needs.MongoDB and Neo4j are emerging technologies and best fit for the system like the medical card.During, my lab I have come across the term like horizontal scalability It is the ability of a system, network, or process to cover a rising sum of work, or it is potential to be magnified in rank to accommodate that increase.For object lesson, it can refer to the capability of a system to increase its total output under an increased load when resources (typically hardware) are added.Another, an inserting term I have disc overed is a document database. Although it was covered in a lecture but not so clear. Hereafter working and installing it make quite a sense.9.3 Problems/IssuesFor MongoDB, it is hard to work on command promptDownload inteleJ IDEA and configured and that will make the job easier. purchasable online https//www.jetbrains.com/idea/download/section=windowsI have tried to install Oracle NOSQL and there were no windows versionAll process needful extra expertise in Linux and Unix and one point I gave upInstalling/configuring process in case of MongoDB and Neo4j is very simple and heterosexual person forward.Neo4j is quite straight forward to install and work.Once installed the Neo4j you need to look around how to run Neo4j. it is almost hard to run Neo4j on http//127.0.0.1 instead if you run it on http//localhost7474/browser/ on your browser window.Command structure not so great, as long your system gets complex, the query process of Neo4j is getting complex as well.IT required previous Knowledge of Jason.If there is a problem in query design, Neo4j prompt for the mistake, but if you have query structure problem or logical error there is no error message. care all technology, you need to memories a lot. There is no toll-like workbench for help.If you have previously worked with RDBMS like oracle or MySQL it will take a while to get a hand on Neo4j.10.1 Appendixhttp//www2.seas.gwu.edu/bell/csci243/lectures/data_warehousing.pdfhttp//www.hse.ie/eng/services/list/1/schemes/mc/http//www.hse.ie/eng/http//www.businessdictionary.com/definition/data-analysis.htmlhttps//www.linkedin.com/pulse/20140728161327-51272350-what-is-collection-in-nosql-databases-specifically-in-mongodbhttps//Neo4j .com/why-graph-databases/http//www.w3resource.com/mongodb/nosql.phphttp//www.tutorialspoint.com/Neo4j /Neo4j _features_advantages.htmhttp//www.itbusinessedge.com/slideshows/top-five-nosql-databases-and-when-to-use-them.htmlhttps//www.youtube.com/ make up ones mind?v=1uFY60CESlMlist=PL6gx4C wl9DGDQ5DrbIl20Zu9hx1IjeVhOhttps//www.youtube.com/watch?v=eE6G5BX8GG0list=PL1zjgLKnHOtga1W4cdyjxRbliw4-n84hRhttp//dist.Neo4j .org/Neo4j -manual-1.4.M03.pdfhttps//www.youtube.com/watch?v=eE6G5BX8GG0list=PL1zjgLKnHOtga1W4cdyjxRbliw4-n84hR