Big Data Analytics Framework using Machine Learning on Multiple Datasets
Abstract: Over 2.5 quintillion bytes of data have been created in last two years alone. These kinds of data comes from various sources such as healthcare informatics, weather information, sensors data, cell phone GPS signals, social media, digital images and videos, transactional information, etc. Big Data refers to huge collection of data sets that are so complex that it becomes so difficult to process using traditional data processing applications. Therefore it requires new set of framework to manage and process Big Data. Map Reduce plays a significant role in processing Big Data. In this paper, the multiple datasets such as data from healthcare organization, weather dataset and movie ratings dataset are stored and organized directly to distributed file system like HDFS. Then finally data is analyzed using Apache Hive for faster query access. In this paper Machine learning techniques are used to solve a big data analytics in a better and simple way.
Keywords: Big data, Hive, Hadoop, HDFS, Machine Learning, COBWEB
How to Cite?: Surekha Sharad Muzumdar, Jharna Majumdar, "Big Data Analytics Framework using Machine Learning on Multiple Datasets", Volume 4 Issue 8, August 2015, International Journal of Science and Research (IJSR), Pages: 414-418, https://www.ijsr.net/getabstract.php?paperid=SUB157332, DOI: https://dx.doi.org/10.21275/SUB157332