论文信息 - In-Memory Business Intelligence: Concepts and Performance

In-Memory Business Intelligence: Concepts and Performance

This research aims to discuss in-memory Business Intelligent (BI) and to model the business analysis questions to know the performance of the in-memory BI. By using, the Qlickview application found BI dashboards that easily accessed and modified. The dashboards are developed together using an agile development approach such as pre-study, planning, iterative execution, implementation, and evaluation. At the end, this research helping analyzer in choosing a right implementation for BI solution.

[1] Zhi Cai,et al. Ranking of Object Summaries , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[2] Mihaela Muntean. Toward Agile BI By Using In-Memory Analytics , 2014 .

[3] Beng Chin Ooi,et al. In-memory Databases: Challenges and Opportunities From Software and Hardware Perspectives , 2015, SGMD.

[4] Alexander Zeier,et al. In-Memory Data Management: Technology and Applications , 2012 .

[5] Gottfried Vossen,et al. In-memory Databases in Business Information Systems , 2011, Bus. Inf. Syst. Eng..

[6] Veda C. Storey,et al. Business Intelligence and Analytics: From Big Data to Big Impact , 2012, MIS Q..

[7] Alvaro A. Cárdenas,et al. Big Data Analytics for Security , 2013, IEEE Security & Privacy.

[8] Mihaela Muntean,et al. Agile BI - the Future of BI , 2013 .

[9] M. Ivan. Characteristics of In-Memory Business Intelligence , 2014 .

[10] Jan vom Brocke,et al. How In-memory Technology Can Create Business Value: Insights from the Hilti Case , 2014, Commun. Assoc. Inf. Syst..

[11] Saru Dhir,et al. Tools for Data Visualization in Business Intelligence: Case Study Using the Tool Qlikview , 2016 .

[12] Martin L. Kersten,et al. Optimizing Main-Memory Join on Modern Hardware , 2002, IEEE Trans. Knowl. Data Eng..

[13] Beng Chin Ooi,et al. In-Memory Big Data Management and Processing: A Survey , 2015, IEEE Transactions on Knowledge and Data Engineering.