scholarly journals Kajian Pendekatan Binary Log dalam Change Data Capture

2017 ◽  
pp. 11
Author(s):  
Muhammad Febrian Rachmadhan Amri ◽  
I Made Sukarsa ◽  
I Ketut Adi Purnawan
Keyword(s):  
Data Management ◽  
Real Time ◽  
Data Warehouse ◽  
Data Capture ◽  
Problem Solution ◽  
Time Data ◽  
Quality Of Data ◽  
Data Manipulation ◽  
Change Data Capture ◽  
Real Time Data

The online business era causes the form of transactions to occur so quickly that the information stored in the data warehouse becomes invalid. Companies are required to have a strong system, which is a system that is real time in order to be able to perform data loading into the media repository that resides on different hosts in the near-real time. Data Warehouse is used as a media repository of data that has the nature of subject-oriented, integrated, time-variant, and is fixed. Data Warehouse can be built into real time management with the advantages possessed and utilize Change Data Capture. Change Data Capture (CDC) is a technique that can be used as problem solution to build real time data warehousing (RTDW). The binary log approach in change data capture is made to record any data manipulation activity that occurs at the OLTP level and is managed back before being stored into the Data Warehouse (loading process). This can improve the quality of data management so that the creation of the right information, because the information available is always updated. Testing shows that Binary Log approach in Change Data Capture (BinlogCDC) is able to generate real time data management, valid current information, dynamic communication between systems, and data management without losing any information from data manipulation.

scholarly journals Change Data Capture on OLTP Staging Area for Nearly Real Time Data Warehouse Base on Database Trigger

2012 ◽  
Vol 52 (11) ◽  
pp. 32-37
Author(s):  
I MadeSukarsa ◽  
Ni Wayan Wisswani ◽  
I K. Gd. Darma Putra ◽  
Linawati Linawati
Keyword(s):  
Real Time ◽  
Data Warehouse ◽  
Data Capture ◽  
Time Data ◽  
Change Data Capture ◽  
Staging Area ◽  
Real Time Data

scholarly journals QoS Management for Embedded Databases in Multicore-Based Embedded Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Woochul Kang ◽  
Jaeyong Chung
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Control Method ◽  
Network Connectivity ◽  
Time Data ◽  
Quality Of Data ◽  
Multiple Control ◽  
Data Intensive ◽  
Real Time Data

With ubiquitous deployment of sensors and network connectivity, amounts of real-time data for embedded systems are increasing rapidly and database capability is required for many embedded systems for systematic management of real-time data. In such embedded systems, supporting the timeliness of tasks accessing databases is an important problem. However, recent multicore-based embedded architectures pose a significant challenge for such data-intensive real-time tasks since the response time of accessing data can be significantly affected by potential intercore interferences. In this paper, we propose a novel feedback control scheme that supports the timeliness of data-intensive tasks against unpredictable intercore interferences. In particular, we use multiple inputs/multiple outputs (MIMO) control method that exploits multiple control knobs, for example, CPU frequency and the Quality-of-Data (QoD) to handle highly unpredictable workloads in multicore systems. Experimental results, using actual implementation, show that the proposed approach achieves the target Quality-of-Service (QoS) goals, such as task timeliness and Quality-of-Data (QoD) while consuming less energy compared to baseline approaches.

scholarly journals Issues and Handy Solutions Addressed at Every Stage in Real Time Data Warehousing, I.E. ETL (Extraction, Transformation & Loading)

2019 ◽  
Vol 8 (5S3) ◽  
pp. 344-348
Keyword(s):  
Real Time ◽  
Data Warehouse ◽  
Data Warehousing ◽  
Time Data ◽  
Processing Load ◽  
Real Time Data ◽  
Data Source

In the standard ETL (Extract Processing Load), the data warehouse refreshment must be performed outside of peak hours. i It implies i that the i functioning and i analysis has stopped in their iall actions. iIt causes the iamount of icleanness of i data from the idata Warehouse which iisn't suggesting ithe latest i operational transections. This i issue is i known as i data i latency. The data warehousing is iemployed to ibe a iremedy for ithis iissue. It updates the idata warehouse iat a inear real-time iFashion, instantly after data found from the data source. Therefore, data i latency could i be reduced. Hence the near real time data warehousing was having issues which was not identified in traditional ETL. This paper claims to communicate the issues and accessible options at every point iin the i near real-time i data warehousing, i.e. i The i issues and Available alternatives iare based ion ia literature ireview by additional iStudy that ifocus ion near real-time data iwarehousing issue

Using Text Messages for Critical Real-time Data Capture in the ANISA Study

2016 ◽  
Vol 35 ◽  
pp. S35-S38 ◽  
Author(s):  
Mohammad Shahidul Islam ◽  
Qazi Sadeq-ur Rahman ◽  
Tanvir Hossain ◽  
Nicholas E. Connor ◽  
Belal Hossain ◽  
...  
Keyword(s):  
Real Time ◽  
Text Messages ◽  
Data Capture ◽  
Time Data ◽  
Real Time Data
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