My name is Al. We are going to talk about the designing and a centralized person data repository. I have around 20 of experience in database technology and currently working with a healthcare company as a data architect. So we are going to talk about that, how to design a centralized percent data repository. Nowadays a large healthcare organization, the percent data is scattered across multiple systems, electronic health records, lab reports, pharmacy reports, and insurance claims. Our task is how to design and implement a centralized data repository that would consolidate all percent information into a single, secure and easily accessible platform. For that. This is what the, today's topic is designing a centralized. Percent data repository. Nowadays, the all healthcare has a lot of data and we have to see how to maintain it. Healthcare, cognition worldwide are experiencing a challenge in managing and exchanging percent data across various system and institutions. The advantage of healthcare technologies introduce new complexity data management. With modern healthcare facility generating an average of 6 65 terabyte or percent data annually through various source, including diagnostic imaging, technical documentation, and real time monitoring devices. The system architecture, when we talk, we are going to talk about here basically Microsoft Architecture Cloud approach, and cost efficiency. When we talk about Microsoft architecture. Microservice architecture is evolved significantly to address the growing complexity of modern data management analysis. Analysis of public health institution has shown that implementing a microservices based architecture with distributed storage capabilities can improve system performance by up to 45% compared to traditional mono approaches. A comprehensive study of public hospitals revealed that organization adopting cloud native architecture experience a 38% reductions in operational cost and 52% improvement in data accessibility. The economic impact of improved healthcare. Interability has been substantial healthcare cognition that have been successfully implemented. Comprehensive interability solutions have observed an address cost saving of $3.7 million annually to reduce duplicate testing, improved resource allocation, and enhance operational efficiency. When we talk about the cloud native approach or the cost efficiency health cognition, adopting our cloud native architecture have experienced a 38% reductions in operational cost and a 52% improvement in percent data as across department, our specializing cloud based. Archival system reduced storage cost by 60, 60% while maintaining a rapid retrieval times under 200 millisecond for frequent excess percent revy data. The core component is the data storage and integration data source layer and integration layer. Once we talk about the data storage layer basically represents the cornerstone of healthcare and pharmacy system requiring careful concentration of data type access patterns and complaints. Requirement research conducted across multiple public hospital demonstrate that post SQL implementation for structural clinical data achieved 99.99% uptime. While managing an average of 7800000.0% records, the study reveals that facilities utilizing MongoDB for unstructured data can also improve the time the cloud-based system reduce the storage cost by 63% while maintaining several retrieval times under 200 millisecond. That is what going on because it's a used amount of data. If you talk about, or the same thing, if you talk about the integration layer, FHIR, gateway implementation, reduce integration complexity by 56% and improve data consistency by 71%. Integration layer is basically. Serve as a critical middleware component, facilitating seamless data exchange between this D disparate healthcare systems. Research. Analyzing F-H-I-R-A-P-I Gateways implementations across public hospital indicate that externalized API approaches reduced in complexity by 56% and data consistency by 71%. The HL seven masses processor component demonstrate the capability to handle 850,000 clinical masses daily with a 99.95% successful processing rate. ETL pipeline implementations in public health environment have shown remarkable efficiency in data transformation and loading process. According to recent studies, modern EL system can process up to three 50 GB of clinical data per hour. While maintaining data quality scores above 95%, the realtime event bus architecture has proven particularly effective in managing clinical workflows, processing an average of 12,000 events per second with latency and a hundred milliseconds enabling realtime clinical decision support system. The security layer, if we think about. Security comprehensive IM system reduced unauthorized access attempt by 97% while processing an average of 500,000 authentication requests daily. R Bs combined with A BAC has sown to reduce security incident by 82%. RBS means role-based access control, and a BS means attribute based access control. Analysis of public hospital implementation revealed that comprehensive IM systems reduce unauthorized access, attend by 97%, while processing an average of 500,000 authentication requests daily encryption service. Utilizing industry standard protocols have demonstrated for robust protections for sensitive health information. Research indicate that modern encryption implementation in healthcare settings can secure up to 35 terabyte of percent data daily while maintaining processing over at below 3%. Once we talk about how to design data model for healthcare system, designing data model of healthcare system, we can talk about percent centric schema, FHI compliant structure, flexible. Storage approaches and versioning and audit control. PE centric schema. Modern healthcare information system requires sophisticated data modeling approach to handle the increasing complexity of PE data. The research analyzing healthcare data architecture has demonstrate the implementation of higher schemas. With optimizing index strategic can reduce query response time by 35% while maintaining data integrity across the system. A study of healthcare facilities revealed that properly structured percent centric schema can handle up to 2,500 concurrent ES per second while maintaining response time. 100 millisecond data duplication strategy. We talk about term matching approach, and we talk about istic matching approach, deterministic matching and probabilistic matching. Deterministic matching like combining identifier matching and probabilistic is basically we talk about machine learning based approach. Healthcare automation face significant challenge in maintaining accurate percent. Identify across multiple system research indicate in deterministic matching algorithm has shown that combining traditional identifier matching. With advanced correlation techniques can achieve equal rate up to 97.8%. In identifying duplicated course, the study of 15 healthcare institutions demonstrate that implementing multifactor determinating matching reduce false positive rate to 0.03% while processing approximately 600,000 records comparison per hour. The effectiveness of deterministic matching significant improve when incorporating temporal data analysis. What exactly? Temporary data analysis. Analyzing historical pattern alongside by accuracy of 24%. Once we talk about PROTIC matching implementation, that advanced processing matching techniques have immersed as a component in modern healthcare data management. Analysis of machine learning based systems has demonstrated accuracy improvement of up to 28% compared to traditional deterministic methods. Particularly when dealing with incomplete or inconsistent data. The research across multiple healthcare networks has shown that sophisticated probability algorithm can achieve a match rate of 92.4%, even with particularly complete demographic data. Once we talk. Once we talk about to how to F-H-I-R-A-P-I layer implementation, this is basically, you can see the numbers, 42% of integration simplification, 31% data accuracy, 89% security enhancement, 850 K daily API request how it manage a lot of data. The implementation of FHI based. Solutions has demonstrated significant impact on healthcare data action Efficiency analysis of healthcare organization has shown that F-H-I-R-R for implementation can reduce data integration complexity by up to 42% while improving data accuracy by 31%. Compared to the legacy systems, the adoption office SMART on FHIR authorization framework has ized secure healthcare data access. Studies indicate that implementing comprehensive FHIR based security protocol reduce unauthorized access by 89% while processing authentication request with an average latency of 180 milliseconds. Data accuracy daily a I request and security enhancement. You can see the numbers, how it match when talk about real time simulation architecture, we talk about. Change data capture that is also called as a CDC event publication Data Synchronization and Conflict Resolutions. CDC. The implementation of change data capture mechanism in healthcare environment has so remarkable improvement in data consistency maintenance. The research demonstrate that modern CDC systems can effectively process approximate 500 changes per second during peak operational hours, with average end to end latency remaining under 150 millisecond. Healthcare facilities implementing CDC architecture have reported a 57% reduction in data ation errors, and a 43% improvement in the real time recoverability. Event publication system integrate with masses Q had demonstrated robust performance improvement, conflict resolution mechanism. Modern healthcare data system requires sophisticated conflict, re resolution strategy to maintain data integrity across distributed environment. Our research indicates that implementing a version based vector based solution mechanism can successfully handle up to seven 50 concurrent updates per second, while maintaining data consistency across distributed healthcare network event publications. And data ation is also two major part, talking about real time synchronization architecture, how we behave. Data protections, measures, encryption, implementations. They all are a part of this. Our whole architecture, security and compliance in healthcare system, data protection, encryption, implementation, access control system, and audit. Implementation. If we talk about data production first, when talk about data production measures, the security landscape in healthcare information system has evolved significantly with the increasing digitization of percent calls. Analysis of healthcare security incident has revealed that approximately 63% of data breaches occur due to unauthorized access, while 27% reserve form system vulnerabilities. Research indicate that healthcare organizations. Implementing comprehensive security framework experience a 71% reduction in successful breach attempt with modern encryption strategy, sewing particular effectiveness in protecting sensitive present data encryption implementation. Implementation we can say we are implementing. A S 2 56 Encryption for data address had demonstrated 99.9% success rate implementing unauthorized data access. With performance overhead, everything only 3.2% compared to encrypted system. Unencrypted system, sorry. So health ation must maintain robust in encrypts mechanism to protect percent data throughout lifecycle. Studies of healthcare facilities implementing standard encryption protocol source, that modern system can process up to 500,000 encrypted transactions daily while maintaining response time under 150 millisecond. We are implementing ass 2 56. Research across multiple healthcare institution has shown that TLS 1.3 implementation for data in transit can effectively secure network communication while adding only 38 millisecond of parallel latency. Implementing feed label encryption report the ability to product sensitive data element with 99.99% reliability while maintain database query performance within 94% of the Israel measurement access control system, modern health environment request, sophisticated access control mechanism to ensure appropriate data access. Rule-based access control system successfully manage an average of 15,000 unique rule across distributed network with authorized and decision process under 85 milliseconds. The integration of attribute based access control has shown it 76% improvement in access season compared to the traditional R BSC only implementation. Emergency access procedures have become increasingly crucial in healthcare environment. Research demonstrate that properly implemented break glass procedure can provide emergency access to critical PE data within 30 seconds while maintaining. Maintaining global robust security protocol, audit tail implementation. Comprehensive audit tail forms a clinical component of healthcare security fracture. The studies indicate that healthcare system generate between 4.2 and 5.8 million. Tamper evident logging mechanism ensure complete traceability of all data access and modification. Organizations implementing blockchain based audit trail report a hundred percent success rate in maintaining audit log integrity across more than 1.8 billion logged EV events over a typical six months period. Once we talk about. The performance optimization in healthcare systems, it is again, go with the query performance. Advanced indexing, casting systems and horizontal scanning query optimizing strategy. The optimization of query performance in healthcare require EHR system has become increasingly crucial. L Health cognition manage growing data volumes. Research, analyze query pattern in large scale ER implementing has shown optimized database engines can reduce an average query response time by 64% while supporting concurrent access from multiple clinic applications. A system process up to 15,000 clinical queries per second. While maintaining average response time on 150 millisecond, we should advance indexing implementation. Very important part. It reduced the query execution time by 74% for complex database joins. Implementation of a s indexing approach has demonstrated significant impact. Analysis shows that data health database utilizing composite index for frequently accessed clinical data path, reduce query execution times by average 21% for complex wines evolving. And clinical observation. Health ation reports that implementing partial indexes for filtered query result in 38% reduction in storage requirements. Text search optimization has emerged as a critical requirement for managing unstructured clinical documentation. The response time from 1.8 second to 3 24 milliseconds. Healthcare facility. Utilizing optimizing task ing strategy report the ability to process up to 750,000 clinical notices daily while maintaining consistent sub second response time. The casting system architecture modern EHR system requires sophisticated casting mechanism. 450,000 requests per second. Wide latency under five milliseconds. Casting consistency management through write through policies has shown particular effectiveness in health environment. The research demonstrated that EHR system implementing a write through casing, maintain 99.95% data consistency while processing an average of 8,000 write operation per second. The scalability strategy is basically horizontal skeleton and load management. Once we talk about horizontal scanning. Scanning implement has demonstrate significant improvement in system capability. Research indicate that percent ID based sing enables ER system to effectively manage data up to 2.5 million active percent while maintaining query response time under 200 milliseconds. Auto scanning mechanism based on clinical workflow patterns have proven particularly effective in healthcare environment. Once we talk about implement consideration for healthcare system cloud infrastructure for healthcare systems. If you see here, we can see infrastructure, cost deployment time, the socialization, compute, cost reduction, storage ion, and security incident improvement. Monitoring and operations is one very important part that how healthcare matters is database monitoring, alerting system, and compliance. Compliance monitoring will help healthcare health matters. Implementation effective monitoring system plays a crucial role in maintaining healthcare system liability. The compressing application performance monitoring reduced mean time to detection by 62% compared to the traditional monitoring approaches. Healthcare recognition. Implementing detailed performance monitoring capture approximately 6.2 million. Metrices daily database monitoring has become increasingly sophisticated. In healthcare environment is a source that organization implementing comprehensive database monitoring, identify potential performance issues and average of 32. Minutes before user impact with 91% accuracy, problem identification, alerting system confirmation. The modern health environment requires robust alerting mechanism to maintain system reliability analysis indicate that organization implementing a multilevel alert system reduce mean time to resolution by 58% while maintaining a false positive rates below 3%. The study shows that properly configured alerting system successfully identify 95% of critical issues within 45 second occurrence. The implementation of compliance monitoring alert has become re for maintaining adherence. Once we talk about the final words, if I want to say here. Today as a conclusion, the implementation of centralized data repository represents a complex but essential undertaking for modern health coordination. The success of system relies on the careful integration of multiple components, from robust data governance policies to comprehensive security measures and continuous monitoring protocols. By adopting a centralized framework like FHIR and implementing sophisticated security controls organization can create systems that effectively balance data accessibility with irregularity comprehensive, the ongoing evolution of healthcare technology, necessities, commitment to continuous improvement, the regular security assessment and strong partnership with healthcare providers. Implementation of the system ultimately leads to improved patient care outcomes, enhance operational efficiency and better healthcare service delivery through seamless data exchange and access capabilities. Thank you so much.