Building Advanced Web Applications Using Data Ingestion and Data Processing Tools

被引:1
作者
Sprem, Simun [1 ]
Tomazin, Nikola [1 ]
Matecic, Jelena [1 ]
Horvat, Marko [2 ]
机构
[1] Agrokor Energija Doo, Trg Drazena Petrovica 3, HR-10000 Zagreb, Croatia
[2] Univ Zagreb, Fac Elect Engn & Comp, Dept Appl Comp, Unska 3, HR-10000 Zagreb, Croatia
关键词
data engineering; big data analytics; big data management; data acquisition; data ingestion; change data capture (CDC); data analysis tools; real-time data stream processing;
D O I
10.3390/electronics13040709
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Today, advanced websites serve as robust data repositories that constantly collect various user-centered information and prepare it for subsequent processing. The data collected can include a wide range of important information from email addresses, usernames, and passwords to demographic information such as age, gender, and geographic location. User behavior metrics are also collected, including browsing history, click patterns, and time spent on pages, as well as different preferences like product selection, language preferences, and individual settings. Interactions, device information, transaction history, authentication data, communication logs, and various analytics and metrics contribute to the comprehensive range of user-centric information collected by websites. A method to systematically ingest and transfer such differently structured information to a central message broker is thoroughly described. In this context, a novel tool-Dataphos Publisher-for the creation of ready-to-digest data packages is presented. Data acquired from the message broker are employed for data quality analysis, storage, conversion, and downstream processing. A brief overview of the commonly used and freely available tools for data ingestion and processing is also provided.
引用
收藏
页数:23
相关论文
共 50 条
  • [31] Big Data Analytics for Power Distribution Systems using AMI and Open Source Tools
    Duggan, Gerald P.
    Zimmerle, Daniel
    Upadhyay, Sonu
    2020 IEEE/PES TRANSMISSION AND DISTRIBUTION CONFERENCE AND EXPOSITION (T&D), 2020,
  • [32] Real Time Streaming Data Storage and Processing using Storm and Analytics with Hive
    Surekha, D.
    Swamy, G.
    Venkatramaphanikumar, S.
    PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES (ICACCCT), 2016, : 606 - 610
  • [33] Integrated data acquisition, storage, retrieval and processing using the COMPASS DataBase (CDB)
    Urban, J.
    Pipek, J.
    Hron, M.
    Janky, F.
    Paprok, R.
    Peterka, M.
    Duarte, A. S.
    FUSION ENGINEERING AND DESIGN, 2014, 89 (05) : 712 - 716
  • [34] Big Data Processing using Internet of Software Defined Things in Smart Cities
    Murad Khan
    Javed Iqbal
    Muhammad Talha
    Muhammad Arshad
    Muhammad Diyan
    Kijun Han
    International Journal of Parallel Programming, 2020, 48 : 178 - 191
  • [35] Big Data Processing using Internet of Software Defined Things in Smart Cities
    Khan, Murad
    Iqbal, Javed
    Talha, Muhammad
    Arshad, Muhammad
    Diyan, Muhammad
    Han, Kijun
    INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING, 2020, 48 (02) : 178 - 191
  • [36] DATA ACQUISITION AND SIGNAL-PROCESSING USING A LAPTOP PERSONAL-COMPUTER
    IMAINO, W
    MUNCE, C
    YERRY, M
    MCDONALD, N
    TRAN, N
    REVIEW OF SCIENTIFIC INSTRUMENTS, 1991, 62 (02) : 516 - 521
  • [37] Urban Planning and Smart City Decision Management Empowered by Real-Time Data Processing Using Big Data Analytics
    Silva, Bhagya Nathali
    Khan, Murad
    Jung, Changsu
    Seo, Jihun
    Muhammad, Diyan
    Han, Jihun
    Yoon, Yongtak
    Han, Kijun
    SENSORS, 2018, 18 (09)
  • [39] Real-time data processing scheme using big data analytics in internet of things based smart transportation environment
    Muhammad Babar
    Fahim Arif
    Journal of Ambient Intelligence and Humanized Computing, 2019, 10 : 4167 - 4177
  • [40] Developing the Profiles of Business Analytics Adopters and Non-adopters Using Data Mining Tools
    Min, Hokey
    Lea, Bih-Ru
    JOURNAL OF COMPUTER INFORMATION SYSTEMS, 2022, 62 (05) : 1048 - 1060