Medical Card System Data Warehouse

Medical Card System Data W arehouseMuhammad NadeemS.No callP.No1Introduction (What project is about)3-42System Overview, Data architecture and storage,5-63ER-Diagram, OLTP-Architecture,Master / buckle down Medical Card System6-104MCS OLTP, MCS information, storage,MCS Business staff or Services litigate11-145Request Flow, Data repository, MySQL15-196Data warehousing19-277Service improvement288statistical Analysis29-309Summary, conclusion, Learned31-3510Appendix36IntroductionA Medical Card is a plastic dining table, 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 nothing out of pocket. Sometime recently, 2009. healing(p) card frame throw was a decentralized and comprising littler upbeat sheets. Since, they are isolated to each others, It was making taking after oddities.Duplicate Medical cards. subtlety Medical cardsSystem deficiencyIncreasing ComplexityBudget deficit in health budgetLack of staf fing and System expertiseTo take root these issues the HSE, choose to incorporated Medical card framework. They gather master from every wellbeing board and accumulate in Dublin. On framework level, it was a major(ip) perplexity mass before centralization. The reason was every wellbeing board has their own medicinal card framework on a few innovations equivalent prophet, SQL server and so forth. A Single Medical card framework was meldning on ORACLE, SQL, MYSQL and MUMS thus on rely on upon the decision of wellbeing board. There were loads of reports and Hauge paper works was included and it was night horse to handle it. To, determine this issue The HSE made a remains to gap discipline into three entropybases, for example, ORACLE, MongoDB.Each of the infobase has there on noteworthiness. The HSE additionally choose to making and dealing with their own information distribution center. There was an alternative accessible for confuse bene converges but since of the way of inf ormation. The HSE fabricate their own information product house. The HSE utilized Mongo DB since it is a record situated database and what it does, it is intended for even versatility. Because this, if your database develops, you burn down fundamentally include more equipment or more assets from the cloud.2.1 MCS System OverviewThe Medical card system data were divided into followingThe data from parvenu medical card forms was divided in 3 parts. First data was Manual filled application which was later typed in the system.The data come from Legacy system and besotted into new system. That sort of data take ond big ETL.Third was supporting archives.The size of data was 2 tetra bytes per month2.2 MCS Data StorageThe data was storing in following technologiesMongoDBNeo4jORACLEMYSQLhybrid system (HyPer)MongoDBMySQLOracleNeo4j Document-orientedCross-platform supportReliable databaseOLTPSupports JSON format.Stored procedures groundbreaking Index CompressionJSON and XLS formatNo DBASQ L/PSMApproximate Count pellucidIndexes by using Apache LucenceFlexible replication for shading across nodes.Triggers.Attribute Clusteringsupports in effect(p) ACIDMulti-version concurrencyCursorsAutomatic Big Table CachingUI for CQLconsistency in complex transactionsUpdatable viewsFDA Support for CDBsNative GPE(Graph Processing Engine).Dynamic queries and powerful aggregates.Online DDLFull Database Caching(CRUD) operationIndex support and ap/reduce functionsInformation schemaIn-Memory hookupAccess by Java, Spring, Scala3.1 MCS Database Architecture3.2 MCS OLTP Architecture Master / Slave Medical Card SystemOne 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 configHardware was dual proc, dual core AMD opterons with 32 GB RAM3.3 MCS OLTPMedical card OLTP systems are employ for come out new application, Medi cal card transactions, customer relationship management (CRM) etc. Such systems get to 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-model-self-governing and mean to professionally handle accidental, ad hoc queries in an analytical system environs. 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 memory board data in multi places so in case of disaster recovery ordain be easy.3.4 MCS DataIt consists on the followingClient personnel and Medical Histo ry such as Client name, address, ppsno and GP informationGP registered inside certain countyHospital information such as OPD, ANE etc.CWO in each areaPharmacies and registered PharmaciesHSE Local offices3.5 MCS Data storageMCS data keep on different devices and system as followingQuantum StorNext scale-out file system.NetBackup product. NetBackup is integrated with copy data management, Veritas Resiliency Platform and Veritas Information Map.MySQLMangoDBNeo4jOracle4.1 MCS Business faculty or Services processFOR NEW APPLICATIONFOR 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 data MCS (Medical Card System) warehouse is, how data for it are prepared, and how it is implemented 3-dimensional 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 stand for decision makingDecision support system (DSS)Arrangement of computerized tools used to assist managerial decision making within line of descent ordinarily requires spacious data massaging to produce informationUsed at all levels within organizationOften tailored to focus on specific business areasProvides ad hoc query 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 external data sourcesEnd-user query toolUsed to create queries that access databaseEnd-user display toolUsed to organize and present data5.6 MCS Main Components of A D SS/BI5.7 MCS DSS/BI Needs a different type of databaseA narrow DBMS tailored to provide fast answers to complex queries.Database schemaMust support complex data representationsMust contain aggregated and summarized dataQueries moldiness 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 emphasize speed, security, flexibility, reduce redundancy and abnormalities.5.8 MCS Operational vs DSS Data6.1 MCS Data warehouseThe 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 processingcentralized, consolidated databaseperiodically updated, never removedRequires time, money, and considerable managerial effort to create6.2 MCS OLAP (Online Analytical Processing) ripe data analysis envi ronment that supports decision making, business modeling, and operations researchengine or platform for DSS or Data WarehouseOLAP systems share quatern main characteristicsUse multidimensional data analysis techniquesProvide advanced database supportProvide easy-to-use end-user interfacesSupport 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 structureParticularly attractive to business decision makersAugmented by following functionsAdvanced data presentation functionsAdvanced data aggregation, consoli dation 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 dataDefined as an advanced data analysis environment that supports decision making, business modeling, and an operations research activitiesIn most implementations, data warehouse and OLAP are interrelated and complementary environments6.12 MCS FactsNumeric measurements (values) that represent specific business aspect or activityNormally stored in fact table that is center of star schemaFact table contains facts that are linked done 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 dodge 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 institution8.1 Statistical AnalysisMCS Difference in Clinical Services Improvement Young and Old patients8.2 canvass 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. muckle who hold a Medical Card are enti tled to a range of Health Services free of charge. In this project, we have seen a switch of centralized medical card system with the help of NOSQL and RDBMS changed the service final result. HSE have Mongo DB which make it suitable 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 analogous 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, modify and Delete (CRUD) operations working on a graph data model.MCS data-model-self-governing and planned to professionally handle accidental, 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 w eek 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 (Medical 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 visualization 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 learned 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 compass in IT things a rapidly changing.RDBMS are good 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 efficacy 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 discovered 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 M ongoDB, it is hard to work on command promptDownload inteleJ IDEA and configured and that will make the job easier.Available online https//www.jetbrains.com/idea/download/section=windowsI have tried to install Oracle NOSQL and there were no windows versionAll process required extra expertise in Linux and Unix and one point I gave upInstalling/configuring process in case of MongoDB and Neo4j is very simple and straight forward.Neo4j is quite straight forward to install and work.Once installed the Neo4j you need to front 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 trouble in query design, Neo4j prompt for the mistake, but if you have query structure problem or logical error there is no error message. wish 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 slice 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/ escort?v=1uFY60CESlMlist=PL6gx4Cwl9DGDQ5DrbIl20Zu9hx1IjeVhOhttps//www.youtube.com/watch?v=eE6G5BX8GG0list=PL1zjgLKnHOtga1W4cdyjxRbliw4-n84hRhttp//dist.Neo4j .org/Neo4j -manual-1.4.M03.pdfhttps//www.youtube.com/watch?v=eE 6G5BX8GG0list=PL1zjgLKnHOtga1W4cdyjxRbliw4-n84hR