RELATIONAL DATABASE MANAGEMENT SYSTEM (RDBMS)

Stored Procedure ◽

Buku berjudul "Relational Database Management System" ini mencoba membahas MySQL secara praktis, disajikan secara terstruktur dan disertai contoh‐contoh dan latihan untuk membantu pemahaman. Buku ini diharapkan dapat membantu Anda menguasai MySQL hingga mahir. Buku ini sangat cocok bagi Anda yang baru mempelajari MySQL maupun bagi Anda yang ingin lebih memperdalam MySQL sebagai salah satu software database terkemuka saat ini. Buku ini terbagi menjadi 4 (empat) bagian. Bagian pertama merupakan bagian pendahuluan yang membahas mengenai penjelasan singkat MySQL dan juga langkah instalasi MySQL serta software pendukung lainnya. Bagian kedua adalah Dasar‐dasar MySQL yang menjelaskan mengenai perintah‐perintah dasar dari MySQL termasuk fungsi‐fungsi di dalam MySQL. Pada bagian ketiga dipaparkan mengenai perintah‐perintah MySQL yang lebih kompleks seperti penggabungan antar tabel, trigger, views dan stored procedure. Selanjutnya pada bagian yang terakhir akan dijelaskan mengenai penyajian laporan dan proses backup, restore database MySQL.

DEVELOPING A RELATIONAL DATABASE MANAGEMENT SYSTEM (PACS) FOR MANIPULATING TEXT, IMAGE AND VIDEO OF ULTRASOUND DATA, BASED ON HL7 AND DICOM STANDARDS

Ultraschall in der Medizin - European Journal of Ultrasound ◽

10.1055/s-2005-917283 ◽

2005 ◽

Vol 26 (S 1) ◽

Author(s):

PS Zoumpoulis ◽

D Dalakostas ◽

C Athinaios ◽

S Faitaki ◽

...

Keyword(s):

Relational Database ◽

Management System ◽

Database Management ◽

Combined Graph/Relational Database Management System for Calculated Chemical Reaction Pathway Data

Journal of Chemical Information and Modeling ◽

10.1021/acs.jcim.0c01280 ◽

2021 ◽

Vol 61 (2) ◽

pp. 554-559

Author(s):

Timur Gimadiev ◽

Ramil Nugmanov ◽

Dinar Batyrshin ◽

Timur Madzhidov ◽

Satoshi Maeda ◽

...

Keyword(s):

Chemical Reaction ◽

Relational Database ◽

Management System ◽

Database Management ◽

Reaction Pathway ◽

Pathway Data ◽

Text storage and retrieval in the ORACLE relational database management system: design study and intended applications

Program electronic library and information systems ◽

10.1108/eb046963 ◽

1987 ◽

Vol 21 (2) ◽

pp. 108-123 ◽

Cited By ~ 6

Author(s):

John H Ashford

Keyword(s):

System Design ◽

Relational Database ◽

Management System ◽

Database Management ◽

Design Study ◽

Storage And Retrieval ◽

Engineering Data Management through a Relational Database Management System

Advances in Engineering Data Handling ◽

10.1007/978-1-4613-2817-9_26 ◽

1984 ◽

pp. 274-296

Author(s):

Atul C. Patel

Keyword(s):

Data Management ◽

Relational Database ◽

Management System ◽

Database Management ◽

Engineering Data ◽

Relational Database Management ◽

Engineering Data Management

THE PROCESS STRUCTURE OF DISTRIBUTED RELATIONAL DATABASE MANAGEMENT SYSTEM C-POREL

Advances in Chinese Computer Science ◽

10.1142/9789814503358_0007 ◽

1989 ◽

pp. 81-92 ◽

Cited By ~ 1

Author(s):

Chen Weimin ◽

Zhou Longxiang

Keyword(s):

Relational Database ◽

Management System ◽

Database Management ◽

Process Structure ◽

Relational Database Management System

10.1201/9780429282843-3 ◽

2021 ◽

pp. 47-78

Author(s):

Jagdish Chandra Patni ◽

Hitesh Kumar Sharma ◽

Ravi Tomar ◽

Avita Katal

Keyword(s):

Relational Database ◽

Management System ◽

Database Management ◽

Automating Quality Oncology Practice Initiative Quality Measure NHL78a

JCO Clinical Cancer Informatics ◽

10.1200/cci.17.00038 ◽

2017 ◽

pp. 1-6

Author(s):

Richard Mansour ◽

Samip Master

Keyword(s):

Hepatitis B ◽

Relational Database ◽

Management System ◽

Database Management ◽

Quality Measurement ◽

Quality Measure ◽

Oncology Practice ◽

Purpose Quality measurement and improvement is a focus of ASCO. In the era of electronic health records (EHRs), computerized order entry, and medication administration records, quality monitoring can be an automated process. The EHR data are usually stored within tables in a relational database management system. ASCO Quality Oncology Practice Initiative measure NHL78a (hepatitis B virus antigen test and hepatitis B core antibody test within 3 months before initiation of obinutuzumab, ofatumumab, or rituximab for patients with non-Hodgkin lymphoma) presents an opportunity for automation of a quality measure using existing data in the EHR. Methods We used a locally developed Structured Query Language (SQL) language procedure in the Microsoft SQL Query Manager to access the EPIC CLARITY database. Access to the relational database management system of the EHR permits rapid case identification (the denominator set) of the unique ID of all of the patients who have received one of the target medications (ie, obinutuzumab, ofatumumab, or rituximab). Then, we went through a six-step process to find the number of patients who passed or failed the quality measure. Results When the final SQL procedure executes, it takes < 5 seconds to see the result set for a 12-month period. The procedure can be changed to incorporate a desired date range. Once the SQL procedure is created, there is essentially no labor and low costs to run the procedure at specific time intervals. Conclusion Our method of quality measurement using EHRs is cost effective, fast, and precise, and can be reproduced at other centers.