Big Data, Data Mining & Artificial Intelligence

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Big Data, Data Mining & Artificial Intelligence

Massimiliano Minaudo, Int J Genom Data Min 2019, Volume 5 DOI: 10.29011/2577-0616-C1-002 International Conference on Big Data, Data Mining & Artificial Intelligence November 20-21, 2019 | Milan, Italy Computational process, Statistics and Economics through new tools or software for Data Mining Massimiliano Minaudo University of Palermo, Italy For the analysis of Big Data, specific tools and applications are generally necessary, many of these should be designed to help companies to extract precise and therefore detailed information in order to classify and outline the data with scientific rigor. The research and therefore the experimentation I did wanted to highlight the main problems faced today by companies to provide the fundamental tools and adequate criteria for data analysis. Of course, every company is called to focus on customer behavior and pursue the most suitable strategy. My goal is to provide, through the analysis carried out, a picture of the main applications and the software that can best help companies to improve their management and productivity results: from the simple use of the spreadsheet for small to medium sample to large set of data or Big Data. The most common and least known tools will be reviewed, starting immediately to consider the best known Open Source tools which are: Rapid Miner, Orange, Knime, Data Melt, Apache Mahout. Among the Data Mining Software as well as R Software Environment, SpagoBI Business Intelligence, Anaconda, Shogun, DataMelt, Natural Language Toolkit, Lavastorm Analytics Engine, Apache Mahout, GNU Octave, Rapid Miner Starter Edition, GraphLab Create, Weka Data Mining, Scikit-learn, ELKI, KNIME Analytics, the most recent and innovative ones will be introduced. The conclusion will therefore be a report on the best tested solutions. Biography Massimiliano Minaudo completed his studies at the University of Palermo and specialized in Computer Science at the Milan Polytechnic where, after a 2nd level Master, he became an expert in Teaching Technologies with a final assessment of 110/110 cum laude. He is an Italian regional referent for Coding, Collaborator in the development of computational thinking, FipGrid Ambassador - Microsoft Education Platform - and Edmodo Ambassador. [email protected] Data Mining & Artificial Intelligence 2019 November 20-21 | Milan, Italy Page 34.

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