A Fuzzy TOPSIS Approach for Big Data Analytics Platform Selection
محورهای موضوعی : Fuzzy SystemsSalah Uddin 1 , Mizanur Rahman 2 , Samaun Hasan 3 , S.M. Irfan Rana 4 , Shaikh Muhammad Allayear 5
1 - Multimedia & Creative Technology, Daffodil International University
2 - Department of Multimedia and Creative Technology, Daffodil International University, Dhaka, Bangladesh
3 - Department of Multimedia and Creative Technology, Daffodil International University, Dhaka, Bangladesh
4 - Department of Multimedia and Creative Technology, Daffodil International University, Dhaka, Bangladesh
5 - Department of Multimedia and Creative Technology, Daffodil International University, Dhaka, Bangladesh
کلید واژه: Fuzzy TOPSIS, Multiple Criteria Decision Making, Big data analytics,
چکیده مقاله :
Big data sizes are constantly increasing. Big data analytics is where advanced analytic techniques are applied on big data sets. Analytics based on large data samples reveals and leverages business change. The popularity of big data analytics platforms, which are often available as open-source, has not remained unnoticed by big companies. Google uses MapReduce for PageRank and inverted indexes. Facebook uses Apache Hadoop to analyse their data and created Hive. eBay uses Apache Hadoop for search optimization and Twitter uses Apache Hadoop for log file analysis and other generated data[ 1]. Different Big data analytics platform providers are providing different types of facilities. To select those analytics platform for our business and public sector institutions purpose we follow multiple criteria. Multiple criteria decision making (MCDM) is mostly used in ranking one or more alternatives from finite set of available alternatives with respect to multiple criteria. Among many multi-criteria techniques, MAXMIN, MAXMAX, SAW, AHP, TOPSIS, SMART, ELECTRE are the most frequently used methods. The TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) methods are simplicity, rationality, comprehensibility, good computational efficiency and ability to measure the relative performance for each alternative in a simple mathematical form.
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